drug analysis based: Topics by Science.gov

Sample records for drug analysis based

Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.

PubMed

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2018-06-07

Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Previously, we identified and ontologically modeled over 240 drugs that can induce peripheral neuropathy through mining public drug-related databases and drug labels. However, the ADR mechanisms of these drugs are still unclear. In this study, we aimed to develop an ontology-based literature mining system to identify ADRs from drug labels and to elucidate potential mechanisms of the neuropathy-inducing drugs (NIDs). We developed and applied an ontology-based SciMiner literature mining strategy to mine ADRs from the drug labels provided in the Text Analysis Conference (TAC) 2017, which included drug labels for 53 neuropathy-inducing drugs (NIDs). We identified an average of 243 ADRs per NID and constructed an ADR-ADR network, which consists of 29 ADR nodes and 149 edges, including only those ADR-ADR pairs found in at least 50% of NIDs. Comparison to the ADR-ADR network of non-NIDs revealed that the ADRs such as pruritus, pyrexia, thrombocytopenia, nervousness, asthenia, acute lymphocytic leukaemia were highly enriched in the NID network. Our ChEBI-based ontology analysis identified three benzimidazole NIDs (i.e., lansoprazole, omeprazole, and pantoprazole), which were associated with 43 ADRs. Based on ontology-based drug class effect definition, the benzimidazole drug group has a drug class effect on all of these 43 ADRs. Many of these 43 ADRs also exist in the enriched NID ADR network. Our Ontology of Adverse Events (OAE) classification further found that these 43 benzimidazole-related ADRs were distributed in many systems, primarily in behavioral and neurological, digestive, skin, and immune systems. Our study demonstrates that ontology-based literature mining and network analysis can efficiently identify and study specific group of drugs and their associated ADRs. Furthermore, our analysis of drug class effects identified 3 benzimidazole drugs sharing 43 ADRs, leading to new hypothesis generation and possible mechanism understanding of drug-induced peripheral neuropathy.
Method Development for Clinical Comprehensive Evaluation of Pediatric Drugs Based on Multi-Criteria Decision Analysis: Application to Inhaled Corticosteroids for Children with Asthma.

PubMed

Yu, Yuncui; Jia, Lulu; Meng, Yao; Hu, Lihua; Liu, Yiwei; Nie, Xiaolu; Zhang, Meng; Zhang, Xuan; Han, Sheng; Peng, Xiaoxia; Wang, Xiaoling

2018-04-01

Establishing a comprehensive clinical evaluation system is critical in enacting national drug policy and promoting rational drug use. In China, the 'Clinical Comprehensive Evaluation System for Pediatric Drugs' (CCES-P) project, which aims to compare drugs based on clinical efficacy and cost effectiveness to help decision makers, was recently proposed; therefore, a systematic and objective method is required to guide the process. An evidence-based multi-criteria decision analysis model that involved an analytic hierarchy process (AHP) was developed, consisting of nine steps: (1) select the drugs to be reviewed; (2) establish the evaluation criterion system; (3) determine the criterion weight based on the AHP; (4) construct the evidence body for each drug under evaluation; (5) select comparative measures and calculate the original utility score; (6) place a common utility scale and calculate the standardized utility score; (7) calculate the comprehensive utility score; (8) rank the drugs; and (9) perform a sensitivity analysis. The model was applied to the evaluation of three different inhaled corticosteroids (ICSs) used for asthma management in children (a total of 16 drugs with different dosage forms and strengths or different manufacturers). By applying the drug analysis model, the 16 ICSs under review were successfully scored and evaluated. Budesonide suspension for inhalation (drug ID number: 7) ranked the highest, with comprehensive utility score of 80.23, followed by fluticasone propionate inhaled aerosol (drug ID number: 16), with a score of 79.59, and budesonide inhalation powder (drug ID number: 6), with a score of 78.98. In the sensitivity analysis, the ranking of the top five and lowest five drugs remains unchanged, suggesting this model is generally robust. An evidence-based drug evaluation model based on AHP was successfully developed. The model incorporates sufficient utility and flexibility for aiding the decision-making process, and can be a useful tool for the CCES-P.
The Shift in Emphasis From Risk-Based to Age-Based Hepatitis C Virus (HCV) Testing in the US Tends to Remove Injection Drug Use From Discourse on HCV.

PubMed

Jordan, Ashly E; Perlman, David C

2017-02-23

Hepatitis C virus (HCV) infection is hyperendemic among people who inject drugs; nonsterile drug injection is the principle risk for HCV acquisition. Due to gaps in the HCV care continuum, there have been recommendations in the United States emphasizing age-rather than risk-based testing strategies. The central research focus of this project is to explore the meanings and implications of the shift in emphasis from risk-based to age-based HCV testing with regard to people who use drugs. Content analysis and critical discourse analysis, informed by eco-social theory, were used to examine relevant documents. Fifteen documents were assessed for eligibility; 6 documents comprised the final set reviewed. In content analysis, age-based testing was both mentioned more frequently and was supported more strongly than risk-based testing. Risk-based testing was frequently mentioned in terms minimizing its use and drug use was often mentioned only euphemistically. The reframed emphasis largely removed discussion of injection drug use from discussion of HCV risks. Shifting the emphasis of HCV testing from testing based on specific routes of transmission and risk to testing based on age removes injection drug use from HCV discourse. This has the potential to either facilitate HCV care for drug users or to further stigmatize and marginalize drug use and people who use drugs. The potential implications of this shift in testing emphasis for public health merit further investigation.
The Social Construction of "Evidence-Based" Drug Prevention Programs: A Reanalysis of Data from the Drug Abuse Resistance Education (DARE) Program

ERIC Educational Resources Information Center

Gorman, Dennis M.; Huber, J. Charles, Jr.

2009-01-01

This study explores the possibility that any drug prevention program might be considered "evidence-based" given the use of data analysis procedures that optimize the chance of producing statistically significant results by reanalyzing data from a Drug Abuse Resistance Education (DARE) program evaluation. The analysis produced a number of…
GraphSAW: a web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data.

PubMed

Shoshi, Alban; Hoppe, Tobias; Kormeier, Benjamin; Ogultarhan, Venus; Hofestädt, Ralf

2015-02-28

Adverse drug reactions are one of the most common causes of death in industrialized Western countries. Nowadays, empirical data from clinical studies for the approval and monitoring of drugs and molecular databases is available. The integration of database information is a promising method for providing well-based knowledge to avoid adverse drug reactions. This paper presents our web-based decision support system GraphSAW which analyzes and evaluates drug interactions and side effects based on data from two commercial and two freely available molecular databases. The system is able to analyze single and combined drug-drug interactions, drug-molecule interactions as well as single and cumulative side effects. In addition, it allows exploring associative networks of drugs, molecules, metabolic pathways, and diseases in an intuitive way. The molecular medication analysis includes the capabilities of the upper features. A statistical evaluation of the integrated data and top 20 drugs concerning drug interactions and side effects is performed. The results of the data analysis give an overview of all theoretically possible drug interactions and side effects. The evaluation shows a mismatch between pharmaceutical and molecular databases. The concordance of drug interactions was about 12% and 9% of drug side effects. An application case with prescribed data of 11 patients is presented in order to demonstrate the functionality of the system under real conditions. For each patient at least two interactions occured in every medication and about 8% of total diseases were possibly induced by drug therapy. GraphSAW (http://tunicata.techfak.uni-bielefeld.de/graphsaw/) is meant to be a web-based system for health professionals and researchers. GraphSAW provides comprehensive drug-related knowledge and an improved medication analysis which may support efforts to reduce the risk of medication errors and numerous drastic side effects.
Collaborative Core Research Program for Chemical-Biological Warfare Defense

DTIC Science & Technology

2015-01-04

Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that
A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

PubMed

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.
The social construction of "evidence-based'' drug prevention programs: a reanalysis of data from the Drug Abuse Resistance Education (DARE) program.

PubMed

Gorman, Dennis M; Huber, J Charles

2009-08-01

This study explores the possibility that any drug prevention program might be considered ;;evidence-based'' given the use of data analysis procedures that optimize the chance of producing statistically significant results by reanalyzing data from a Drug Abuse Resistance Education (DARE) program evaluation. The analysis produced a number of statistically significant differences between the DARE and control conditions on alcohol and marijuana use measures. Many of these differences occurred at cutoff points on the assessment scales for which post hoc meaningful labels were created. Our results are compared to those from evaluations of programs that appear on evidence-based drug prevention lists.
Gene-set analysis based on the pharmacological profiles of drugs to identify repurposing opportunities in schizophrenia.

PubMed

de Jong, Simone; Vidler, Lewis R; Mokrab, Younes; Collier, David A; Breen, Gerome

2016-08-01

Genome-wide association studies (GWAS) have identified thousands of novel genetic associations for complex genetic disorders, leading to the identification of potential pharmacological targets for novel drug development. In schizophrenia, 108 conservatively defined loci that meet genome-wide significance have been identified and hundreds of additional sub-threshold associations harbour information on the genetic aetiology of the disorder. In the present study, we used gene-set analysis based on the known binding targets of chemical compounds to identify the 'drug pathways' most strongly associated with schizophrenia-associated genes, with the aim of identifying potential drug repositioning opportunities and clues for novel treatment paradigms, especially in multi-target drug development. We compiled 9389 gene sets (2496 with unique gene content) and interrogated gene-based p-values from the PGC2-SCZ analysis. Although no single drug exceeded experiment wide significance (corrected p<0.05), highly ranked gene-sets reaching suggestive significance including the dopamine receptor antagonists metoclopramide and trifluoperazine and the tyrosine kinase inhibitor neratinib. This is a proof of principle analysis showing the potential utility of GWAS data of schizophrenia for the direct identification of candidate drugs and molecules that show polypharmacy. © The Author(s) 2016.
Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.
Conformational Analysis of Drug Molecules: A Practical Exercise in the Medicinal Chemistry Course

ERIC Educational Resources Information Center

Yuriev, Elizabeth; Chalmers, David; Capuano, Ben

2009-01-01

Medicinal chemistry is a specialized, scientific discipline. Computational chemistry and structure-based drug design constitute important themes in the education of medicinal chemists. This problem-based task is associated with structure-based drug design lectures. It requires students to use computational techniques to investigate conformational…
Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.
System of Objectified Judgement Analysis (SOJA) as a tool in rational and transparent drug-decision making.

PubMed

Janknegt, Robert; Scott, Mike; Mairs, Jill; Timoney, Mark; McElnay, James; Brenninkmeijer, Rob

2007-10-01

Drug selection should be a rational process that embraces the principles of evidence-based medicine. However, many factors may affect the choice of agent. It is against this background that the System of Objectified Judgement Analysis (SOJA) process for rational drug-selection was developed. This article describes how the information on which the SOJA process is based, was researched and processed.
Network-based machine learning and graph theory algorithms for precision oncology.

PubMed

Zhang, Wei; Chien, Jeremy; Yong, Jeongsik; Kuang, Rui

2017-01-01

Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be better understood through mutated or dysregulated pathways or networks rather than individual mutations and that the efficacy of repositioned drugs can be inferred from disease modules in molecular networks. This article reviews network-based machine learning and graph theory algorithms for integrative analysis of personal genomic data and biomedical knowledge bases to identify tumor-specific molecular mechanisms, candidate targets and repositioned drugs for personalized treatment. The review focuses on the algorithmic design and mathematical formulation of these methods to facilitate applications and implementations of network-based analysis in the practice of precision oncology. We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning drugs in drug-disease-gene networks. In addition, we perform a comprehensive subnetwork/pathway analysis of mutations in 31 cancer genome projects in the Cancer Genome Atlas and present a detailed case study on ovarian cancer. Finally, we discuss interesting observations, potential pitfalls and future directions in network-based precision oncology.
A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Non-Small Cell Lung Cancer.

PubMed

Raju, G K; Gurumurthi, K; Domike, R; Kazandjian, D; Blumenthal, G; Pazdur, R; Woodcock, J

2016-12-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analyses. There is much interest in quantifying regulatory approaches to benefit and risk. In this work the use of a quantitative benefit-risk analysis was applied to regulatory decision-making about new drugs to treat advanced non-small cell lung cancer (NSCLC). Benefits and risks associated with 20 US Food and Drug Administration (FDA) decisions associated with a set of candidate treatments submitted between 2003 and 2015 were analyzed. For benefit analysis, the median overall survival (OS) was used where available. When not available, OS was estimated based on overall response rate (ORR) or progression-free survival (PFS). Risks were analyzed based on magnitude (or severity) of harm and likelihood of occurrence. Additionally, a sensitivity analysis was explored to demonstrate analysis of systematic uncertainty. FDA approval decision outcomes considered were found to be consistent with the benefit-risk logic. © 2016 American Society for Clinical Pharmacology and Therapeutics.
Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism.

PubMed

Liu, Qingping; Wang, Jiahao; Zhu, Yan; He, Yongqun

2017-12-21

Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. An ontology for anti-rheumatism traditional Chinese drugs would strongly support the representation, analysis, and understanding of these drugs. In this study, we first systematically collected reported information about 26 traditional Chinese decoction pieces drugs, including their chemical ingredients and adverse events (AEs). By mostly reusing terms from existing ontologies (e.g., TCMDPO for traditional Chinese medicines, NCBITaxon for taxonomy, ChEBI for chemical elements, and OAE for adverse events) and making semantic axioms linking different entities, we developed the Ontology of Chinese Medicine for Rheumatism (OCMR) that includes over 3000 class terms. Our OCMR analysis found that these 26 traditional Chinese decoction pieces are made from anatomic entities (e.g., root and stem) from 3 Bilateria animals and 23 Mesangiospermae plants. Anti-inflammatory and antineoplastic roles are important for anti-rheumatism drugs. Using the total of 555 unique ChEBI chemical entities identified from these drugs, our ChEBI-based classification analysis identified 18 anti-inflammatory, 33 antineoplastic chemicals, and 9 chemicals (including 3 diterpenoids and 3 triterpenoids) having both anti-inflammatory and antineoplastic roles. Furthermore, our study detected 22 diterpenoids and 23 triterpenoids, including 16 pentacyclic triterpenoids that are likely bioactive against rheumatism. Six drugs were found to be associated with 184 unique AEs, including three AEs (i.e., dizziness, nausea and vomiting, and anorexia) each associated with 5 drugs. Several chemical entities are classified as neurotoxins (e.g., diethyl phthalate) and allergens (e.g., eugenol), which may explain the formation of some TCD AEs. The OCMR could be efficiently queried for useful information using SPARQL scripts. The OCMR ontology was developed to systematically represent 26 traditional anti-rheumatism Chinese drugs and their related information. The OCMR analysis identified possible anti-rheumatism and AE mechanisms of these drugs. Our novel ontology-based approach can also be applied to systematic representation and analysis of other traditional Chinese drugs.
Using Statistics and Data Mining Approaches to Analyze Male Sexual Behaviors and Use of Erectile Dysfunction Drugs Based on Large Questionnaire Data.

PubMed

Qiao, Zhi; Li, Xiang; Liu, Haifeng; Zhang, Lei; Cao, Junyang; Xie, Guotong; Qin, Nan; Jiang, Hui; Lin, Haocheng

2017-01-01

The prevalence of erectile dysfunction (ED) has been extensively studied worldwide. Erectile dysfunction drugs has shown great efficacy in preventing male erectile dysfunction. In order to help doctors know drug taken preference of patients and better prescribe, it is crucial to analyze who actually take erectile dysfunction drugs and the relation between sexual behaviors and drug use. Existing clinical studies usually used descriptive statistics and regression analysis based on small volume of data. In this paper, based on big volume of data (48,630 questionnaires), we use data mining approaches besides statistics and regression analysis to comprehensively analyze the relation between male sexual behaviors and use of erectile dysfunction drugs for unravelling the characteristic of patients who take erectile dysfunction drugs. We firstly analyze the impact of multiple sexual behavior factors on whether to use the erectile dysfunction drugs. Then, we explore to mine the Decision Rules for Stratification to discover patients who are more likely to take drugs. Based on the decision rules, the patients can be partitioned into four potential groups for use of erectile dysfunction: high potential group, intermediate potential-1 group, intermediate potential-2 group and low potential group. Experimental results show 1) the sexual behavior factors, erectile hardness and time length to prepare (how long to prepares for sexual behaviors ahead of time), have bigger impacts both in correlation analysis and potential drug taking patients discovering; 2) odds ratio between patients identified as low potential and high potential was 6.098 (95% confidence interval, 5.159-7.209) with statistically significant differences in taking drug potential detected between all potential groups.
Inquiry-based Laboratory Activities on Drugs Analysis for High School Chemistry Learning

NASA Astrophysics Data System (ADS)

Rahmawati, I.; Sholichin, H.; Arifin, M.

2017-09-01

Laboratory activity is an important part of chemistry learning, but cookbook instructions is still commonly used. However, the activity with that way do not improve students thinking skill, especially students creativity. This study aims to improve high school students creativity through inquiry-based laboratory on drugs analysis activity. Acid-base titration is used to be method for drugs analysis involving a color changing indicator. The following tools were used to assess the activity achievement: creative thinking test on acid base titration, creative attitude and action observation sheets, questionnaire of inquiry-based lab activities, and interviews. The results showed that the inquiry-based laboratory activity improving students creative thinking, creative attitude and creative action. The students reacted positively to this teaching strategy as demonstrated by results from questionnaire responses and interviews. This result is expected to help teachers to overcome the shortcomings in other laboratory learning.
Priority setting for orphan drugs: an international comparison.

PubMed

Rosenberg-Yunger, Zahava R S; Daar, Abdallah S; Thorsteinsdóttir, Halla; Martin, Douglas K

2011-04-01

To describe the process of priority setting for two orphan drugs - Cerezyme and Fabrazyme - in Canada, Australia and Israel, in order to understand and improve the process based on stakeholder perspectives. We conducted qualitative case studies of how three independent drug advisory committees made decisions relating to the funding of Cerezyme and Fabrazyme. Interviews were conducted with 22 informants, including committee members, patient groups and industry representatives. (1) DESCRIPTION: Orphan drugs reimbursement recommendations by expert panels were based on clinical evidence, cost and cost-effectiveness analysis. (2) EVALUATION: Committee members expressed an overall preference for the current drug review process used by their own committee, but were concerned with the fairness of the process particularly for orphan drugs. Other informants suggested the inclusion of other relevant values (e.g. lack of alternative treatments) in order to improve the priority setting process. Some patient groups suggested the use of an alternative funding mechanism for orphan drugs. Priority setting for drugs is not solely a technical process (involving cost-effective analysis, evidence-based medicine, etc.). Understanding the process by which reimbursement decisions are made for orphan drugs may help improve the system for future orphan drugs. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

PubMed

Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

2011-05-30

Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

Investigating the correlation between wastewater analysis and roadside drug testing in South Australia.

PubMed

Bade, Richard; Tscharke, Benjamin J; Longo, Marie; Cooke, Richard; White, Jason M; Gerber, Cobus

2018-06-01

The societal impact of drug use is well known. An example is when drug-intoxicated drivers increase the burden on policing and healthcare services. This work presents the correlation of wastewater analysis (using UHPLC-MS/MS) and positive roadside drug testing results for methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA) and cannabis from December 2011-December 2016 in South Australia. Methamphetamine and MDMA showed similar trends between the data sources with matching increases and decreases, respectively. Cannabis was relatively steady based on wastewater analysis, but the roadside drug testing data started to diverge in the final part of the measurement period. The ability to triangulate data as shown here validates both wastewater analysis and roadside drug testing. This suggests that changes in overall population drug use revealed by WWA is consistent and proportional with changes in drug-driving behaviours. The results show that, at higher levels of drug use as measured by wastewater analysis, there is an increase in drug driving in the community and therefore more strain on health services and police. Copyright © 2018 Elsevier B.V. All rights reserved.
78 FR 15894 - Draft Qualitative Risk Assessment of Risk of Activity/Food Combinations for Activities (Outside...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-13

... science-based risk analysis of those activity/food combinations that would be considered low risk. We... proposed requirements of the Federal Food, Drug, and Cosmetic Act for hazard analysis and risk-based... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration 21 CFR Part 117 [Docket No...
Lipid-associated Oral Delivery: Mechanisms and Analysis of Oral Absorption Enhancement

PubMed Central

Rezhdo, Oljora; Speciner, Lauren; Carrier, Rebecca L.

2016-01-01

The majority of newly discovered oral drugs are poorly water soluble, and co-administration with lipids has proven effective in significantly enhancing bioavailability of some compounds with low aqueous solubility. Yet, lipid-based delivery technologies have not been widely employed in commercial oral products. Lipids can impact drug transport and fate in the gastrointestinal (GI) tract through multiple mechanisms including enhancement of solubility and dissolution kinetics, enhancement of permeation through the intestinal mucosa, and triggering drug precipitation upon lipid emulsion depletion (e.g., by digestion). The effect of lipids on drug absorption is currently not quantitatively predictable, in part due to the multiple complex dynamic processes that can be impacted by lipids. Quantitative mechanistic analysis of the processes significant to lipid system function and overall impact on drug absorption can aid understanding of drug-lipid interactions in the GI tract and exploitation of such interactions to achieve optimal lipid-based drug delivery. In this review, we discuss the impact of co-delivered lipids and lipid digestion on drug dissolution, partitioning, and absorption in the context of the experimental tools and associated kinetic expressions used to study and model these processes. The potential benefit of a systems-based consideration of the concurrent multiple dynamic processes occurring upon co-dosing lipids and drugs to predict the impact of lipids on drug absorption and enable rational design of lipid-based delivery systems is presented. PMID:27520734
Text mining-based in silico drug discovery in oral mucositis caused by high-dose cancer therapy.

PubMed

Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C

2018-08-01

Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.
Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing.

PubMed

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-09-07

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications.
Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

PubMed Central

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-01-01

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications. PMID:27599720
Improving the assessment of prescribing: use of a 'substitution index'.

PubMed

Kunisawa, Susumu; Otsubo, Tetsuya; Lee, Jason; Imanaka, Yuichi

2013-07-01

To analyse the current and potential utilization of generic drugs in Japan, to examine the maximum possible cost savings from generic drug use and to develop a fairer measure to assess the level of generic drug substitution. We conducted a cross-sectional retrospective analysis of nine million dispensing records during January to March 2010 in Kyoto Prefecture. Maximum potential quantity-based shares were defined as the quantity of generic drugs used plus the quantity of branded drugs that could have been replaced by generic drugs divided by the quantity of all drugs dispensed. We developed a 'substitution index', defined as the proportion of generic drugs out of the total drugs substitutable with generic drugs (based on quantity rather than cost). Generic drugs had a quantity-based share of 17.9%, a cost-based share of 8.9% and a maximum potential quantity-based share of 50.1%, which is lower than the actual generic drug shares of some other countries. The maximum possible cost savings as a result of generic drug substitution was 16.5%. We also observed wide variations in maximum potential quantity-based shares between health care sectors and health care institutions. Simple comparisons based on quantity-based shares may misrepresent the actual generic drug use. A substitution index that takes into account the maximum potential quantity-based share of generic drugs as a fairer measure may promote more realistic goals and encourage generic drug usage.
Budget impact analysis of drugs for ultra-orphan non-oncological diseases in Europe.

PubMed

Schlander, Michael; Adarkwah, Charles Christian; Gandjour, Afschin

2015-02-01

Ultra-orphan diseases (UODs) have been defined by a prevalence of less than 1 per 50,000 persons. However, little is known about budget impact of ultra-orphan drugs. For analysis, the budget impact analysis (BIA) had a time horizon of 10 years (2012-2021) and a pan-European payer's perspective, based on prevalence data for UODs for which patented drugs are available and/or for which drugs are in clinical development. A total of 18 drugs under patent protection or orphan drug designation for non-oncological UODs were identified. Furthermore, 29 ultra-orphan drugs for non-oncological diseases under development that have the potential of reaching the market by 2021 were found. Total budget impact over 10 years was estimated to be €15,660 and €4965 million for approved and pipeline ultra-orphan drugs, respectively (total: €20,625 million). The analysis does not support concerns regarding an uncontrolled growth in expenditures for drugs for UODs.
Preparation of silica nanoparticles loaded with nootropics and their in vivo permeation through blood-brain barrier.

PubMed

Jampilek, Josef; Zaruba, Kamil; Oravec, Michal; Kunes, Martin; Babula, Petr; Ulbrich, Pavel; Brezaniova, Ingrid; Opatrilova, Radka; Triska, Jan; Suchy, Pavel

2015-01-01

The blood-brain barrier prevents the passage of many drugs that target the central nervous system. This paper presents the preparation and characterization of silica-based nanocarriers loaded with piracetam, pentoxifylline, and pyridoxine (drugs from the class of nootropics), which are designed to enhance the permeation of the drugs from the circulatory system through the blood-brain barrier. Their permeation was compared with non-nanoparticle drug substances (bulk materials) by means of an in vivo model of rat brain perfusion. The size and morphology of the nanoparticles were characterized by transmission electron microscopy. The content of the drug substances in silica-based nanocarriers was analysed by elemental analysis and UV spectrometry. Microscopic analysis of visualized silica nanocarriers in the perfused brain tissue was performed. The concentration of the drug substances in the tissue was determined by means of UHPLC-DAD/HRMS LTQ Orbitrap XL. It was found that the drug substances in silica-based nanocarriers permeated through the blood brain barrier to the brain tissue, whereas bulk materials were not detected in the brain.
Preparation of Silica Nanoparticles Loaded with Nootropics and Their In Vivo Permeation through Blood-Brain Barrier

PubMed Central

Zaruba, Kamil; Kunes, Martin; Ulbrich, Pavel; Brezaniova, Ingrid; Triska, Jan; Suchy, Pavel

2015-01-01

The blood-brain barrier prevents the passage of many drugs that target the central nervous system. This paper presents the preparation and characterization of silica-based nanocarriers loaded with piracetam, pentoxifylline, and pyridoxine (drugs from the class of nootropics), which are designed to enhance the permeation of the drugs from the circulatory system through the blood-brain barrier. Their permeation was compared with non-nanoparticle drug substances (bulk materials) by means of an in vivo model of rat brain perfusion. The size and morphology of the nanoparticles were characterized by transmission electron microscopy. The content of the drug substances in silica-based nanocarriers was analysed by elemental analysis and UV spectrometry. Microscopic analysis of visualized silica nanocarriers in the perfused brain tissue was performed. The concentration of the drug substances in the tissue was determined by means of UHPLC-DAD/HRMS LTQ Orbitrap XL. It was found that the drug substances in silica-based nanocarriers permeated through the blood brain barrier to the brain tissue, whereas bulk materials were not detected in the brain. PMID:26075264
GDA, a web-based tool for Genomics and Drugs integrated analysis.

PubMed

Caroli, Jimmy; Sorrentino, Giovanni; Forcato, Mattia; Del Sal, Giannino; Bicciato, Silvio

2018-05-25

Several major screenings of genetic profiling and drug testing in cancer cell lines proved that the integration of genomic portraits and compound activities is effective in discovering new genetic markers of drug sensitivity and clinically relevant anticancer compounds. Despite most genetic and drug response data are publicly available, the availability of user-friendly tools for their integrative analysis remains limited, thus hampering an effective exploitation of this information. Here, we present GDA, a web-based tool for Genomics and Drugs integrated Analysis that combines drug response data for >50 800 compounds with mutations and gene expression profiles across 73 cancer cell lines. Genomic and pharmacological data are integrated through a modular architecture that allows users to identify compounds active towards cancer cell lines bearing a specific genomic background and, conversely, the mutational or transcriptional status of cells responding or not-responding to a specific compound. Results are presented through intuitive graphical representations and supplemented with information obtained from public repositories. As both personalized targeted therapies and drug-repurposing are gaining increasing attention, GDA represents a resource to formulate hypotheses on the interplay between genomic traits and drug response in cancer. GDA is freely available at http://gda.unimore.it/.
MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development

PubMed Central

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/. PMID:25928885
Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

PubMed

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing

PubMed Central

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A.; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space. PMID:29545755
Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing.

PubMed

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.
Development of a general method for quantifying IgG-based therapeutic monoclonal antibodies in human plasma using protein G purification coupled with a two internal standard calibration strategy using LC-MS/MS.

PubMed

Chiu, Huai-Hsuan; Liao, Hsiao-Wei; Shao, Yu-Yun; Lu, Yen-Shen; Lin, Ching-Hung; Tsai, I-Lin; Kuo, Ching-Hua

2018-08-17

Monoclonal antibody (mAb) drugs have generated much interest in recent years for treating various diseases. Immunoglobulin G (IgG) represents a high percentage of mAb drugs that have been approved by the Food and Drug Administration (FDA). To facilitate therapeutic drug monitoring and pharmacokinetic/pharmacodynamic studies, we developed a general liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify the concentration of IgG-based mAbs in human plasma. Three IgG-based drugs (bevacizumab, nivolumab and pembrolizumab) were selected to demonstrate our method. Protein G beads were used for sample pretreatment due to their universal ability to trap IgG-based drugs. Surrogate peptides that were obtained after trypsin digestion were quantified by using LC-MS/MS. To calibrate sample preparation errors and matrix effects that occur during LC-MS/MS analysis, we used two internal standards (IS) method that include the IgG-based drug-IS tocilizumab and post-column infused IS. Using two internal standards was found to effectively improve quantification accuracy, which was within 15% for all mAb drugs that were tested at three different concentrations. This general method was validated in term of its precision, accuracy, linearity and sensitivity for 3 demonstration mAb drugs. The successful application of the method to clinical samples demonstrated its' applicability in clinical analysis. It is anticipated that this general method could be applied to other mAb-based drugs for use in precision medicine and clinical studies. Copyright © 2018 Elsevier B.V. All rights reserved.
Cheminformatic comparison of approved drugs from natural product versus synthetic origins.

PubMed

Stratton, Christopher F; Newman, David J; Tan, Derek S

2015-11-01

Despite the recent decline of natural product discovery programs in the pharmaceutical industry, approximately half of all new drug approvals still trace their structural origins to a natural product. Herein, we use principal component analysis to compare the structural and physicochemical features of drugs from natural product-based versus completely synthetic origins that were approved between 1981 and 2010. Drugs based on natural product structures display greater chemical diversity and occupy larger regions of chemical space than drugs from completely synthetic origins. Notably, synthetic drugs based on natural product pharmacophores also exhibit lower hydrophobicity and greater stereochemical content than drugs from completely synthetic origins. These results illustrate that structural features found in natural products can be successfully incorporated into synthetic drugs, thereby increasing the chemical diversity available for small-molecule drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.
Lipid-associated oral delivery: Mechanisms and analysis of oral absorption enhancement.

PubMed

Rezhdo, Oljora; Speciner, Lauren; Carrier, Rebecca

2016-10-28

The majority of newly discovered oral drugs are poorly water soluble, and co-administration with lipids has proven effective in significantly enhancing bioavailability of some compounds with low aqueous solubility. Yet, lipid-based delivery technologies have not been widely employed in commercial oral products. Lipids can impact drug transport and fate in the gastrointestinal (GI) tract through multiple mechanisms including enhancement of solubility and dissolution kinetics, enhancement of permeation through the intestinal mucosa, and triggering drug precipitation upon lipid emulsion depletion (e.g., by digestion). The effect of lipids on drug absorption is currently not quantitatively predictable, in part due to the multiple complex dynamic processes that can be impacted by lipids. Quantitative mechanistic analysis of the processes significant to lipid system function and overall impact on drug absorption can aid in the understanding of drug-lipid interactions in the GI tract and exploitation of such interactions to achieve optimal lipid-based drug delivery. In this review, we discuss the impact of co-delivered lipids and lipid digestion on drug dissolution, partitioning, and absorption in the context of the experimental tools and associated kinetic expressions used to study and model these processes. The potential benefit of a systems-based consideration of the concurrent multiple dynamic processes occurring upon co-dosing lipids and drugs to predict the impact of lipids on drug absorption and enable rational design of lipid-based delivery systems is presented. Copyright © 2016 Elsevier B.V. All rights reserved.
Relative costs of anesthesiologist prepared, hospital pharmacy prepared and outsourced anesthesia drugs.

PubMed

Jelacic, Srdjan; Craddick, Karen; Nair, Bala G; Bounthavong, Mark; Yeung, Kai; Kusulos, Dolly; Knutson, Jennifer A; Somani, Shabir; Bowdle, Andrew

2017-02-01

Anesthesia drugs can be prepared by anesthesia providers, hospital pharmacies or outsourcing facilities. The decision whether to outsource all or some anesthesia drugs is challenging since the costs associated with different anesthesia drug preparation methods remain poorly described. The costs associated with preparation of 8 commonly used anesthesia drugs were analyzed using a budget impact analysis for 4 different syringe preparation strategies: (1) all drugs prepared by anesthesiologist, (2) drugs prepared by anesthesiologist and hospital pharmacy, (3) drugs prepared by anesthesiologist and outsourcing facility, and (4) all drugs prepared by outsourcing facility. A strategy combining anesthesiologist and hospital pharmacy prepared drugs was associated with the lowest estimated annual cost in the base-case budget impact analysis with an annual cost of $225 592, which was lower than other strategies by a margin of greater than $86 000. A combination of anesthesiologist and hospital pharmacy prepared drugs resulted in the lowest annual cost in the budget impact analysis. However, the cost of drugs prepared by an outsourcing facility maybe lower if the capital investment needed for the establishment and maintenance of the US Pharmacopeial Convention Chapter <797> compliant facility is included in the budget impact analysis. Copyright © 2016 Elsevier Inc. All rights reserved.
The mass-action law based algorithm for cost-effective approach for cancer drug discovery and development.

PubMed

Chou, Ting-Chao

2011-01-01

The mass-action law based system analysis via mathematical induction and deduction lead to the generalized theory and algorithm that allows computerized simulation of dose-effect dynamics with small size experiments using a small number of data points in vitro, in animals, and in humans. The median-effect equation of the mass-action law deduced from over 300 mechanism specific-equations has been shown to be the unified theory that serves as the common-link for complicated biomedical systems. After using the median-effect principle as the common denominator, its applications are mechanism-independent, drug unit-independent, and dynamic order-independent; and can be used generally for single drug analysis or for multiple drug combinations in constant-ratio or non-constant ratios. Since the "median" is the common link and universal reference point in biological systems, these general enabling lead to computerized quantitative bio-informatics for econo-green bio-research in broad disciplines. Specific applications of the theory, especially relevant to drug discovery, drug combination, and clinical trials, have been cited or illustrated in terms of algorithms, experimental design and computerized simulation for data analysis. Lessons learned from cancer research during the past fifty years provide a valuable opportunity to reflect, and to improve the conventional divergent approach and to introduce a new convergent avenue, based on the mass-action law principle, for the efficient cancer drug discovery and the low-cost drug development.

The mass-action law based algorithm for cost-effective approach for cancer drug discovery and development

PubMed Central

Chou, Ting-Chao

2011-01-01

The mass-action law based system analysis via mathematical induction and deduction lead to the generalized theory and algorithm that allows computerized simulation of dose-effect dynamics with small size experiments using a small number of data points in vitro, in animals, and in humans. The median-effect equation of the mass-action law deduced from over 300 mechanism specific-equations has been shown to be the unified theory that serves as the common-link for complicated biomedical systems. After using the median-effect principle as the common denominator, its applications are mechanism-independent, drug unit-independent, and dynamic order-independent; and can be used generally for single drug analysis or for multiple drug combinations in constant-ratio or non-constant ratios. Since the “median” is the common link and universal reference point in biological systems, these general enabling lead to computerized quantitative bio-informatics for econo-green bio-research in broad disciplines. Specific applications of the theory, especially relevant to drug discovery, drug combination, and clinical trials, have been cited or illustrated in terms of algorithms, experimental design and computerized simulation for data analysis. Lessons learned from cancer research during the past fifty years provide a valuable opportunity to reflect, and to improve the conventional divergent approach and to introduce a new convergent avenue, based on the mass-action law principle, for the efficient cancer drug discovery and the low-cost drug development. PMID:22016837
Predicting new drug indications from network analysis

NASA Astrophysics Data System (ADS)

Mohd Ali, Yousoff Effendy; Kwa, Kiam Heong; Ratnavelu, Kurunathan

This work adapts centrality measures commonly used in social network analysis to identify drugs with better positions in drug-side effect network and drug-indication network for the purpose of drug repositioning. Our basic hypothesis is that drugs having similar phenotypic profiles such as side effects may also share similar therapeutic properties based on related mechanism of action and vice versa. The networks were constructed from Side Effect Resource (SIDER) 4.1 which contains 1430 unique drugs with side effects and 1437 unique drugs with indications. Within the giant components of these networks, drugs were ranked based on their centrality scores whereby 18 prominent drugs from the drug-side effect network and 15 prominent drugs from the drug-indication network were identified. Indications and side effects of prominent drugs were deduced from the profiles of their neighbors in the networks and compared to existing clinical studies while an optimum threshold of similarity among drugs was sought for. The threshold can then be utilized for predicting indications and side effects of all drugs. Similarities of drugs were measured by the extent to which they share phenotypic profiles and neighbors. To improve the likelihood of accurate predictions, only profiles such as side effects of common or very common frequencies were considered. In summary, our work is an attempt to offer an alternative approach to drug repositioning using centrality measures commonly used for analyzing social networks.
Employment-based abstinence reinforcement promotes opiate and cocaine abstinence in out-of-treatment injection drug users.

PubMed

Holtyn, August F; Koffarnus, Mikhail N; DeFulio, Anthony; Sigurdsson, Sigurdur O; Strain, Eric C; Schwartz, Robert P; Silverman, Kenneth

2014-01-01

We examined the use of employment-based abstinence reinforcement in out-of-treatment injection drug users, in this secondary analysis of a previously reported trial. Participants (N = 33) could work in the therapeutic workplace, a model employment-based program for drug addiction, for 30 weeks and could earn approximately $10 per hr. During a 4-week induction, participants only had to work to earn pay. After induction, access to the workplace was contingent on enrollment in methadone treatment. After participants met the methadone contingency for 3 weeks, they had to provide opiate-negative urine samples to maintain maximum pay. After participants met those contingencies for 3 weeks, they had to provide opiate- and cocaine-negative urine samples to maintain maximum pay. The percentage of drug-negative urine samples remained stable until the abstinence reinforcement contingency for each drug was applied. The percentage of opiate- and cocaine-negative urine samples increased abruptly and significantly after the opiate- and cocaine-abstinence contingencies, respectively, were applied. These results demonstrate that the sequential administration of employment-based abstinence reinforcement can increase opiate and cocaine abstinence among out-of-treatment injection drug users. © Society for the Experimental Analysis of Behavior.
Drug target inference through pathway analysis of genomics data

PubMed Central

Ma, Haisu; Zhao, Hongyu

2013-01-01

Statistical modeling coupled with bioinformatics is commonly used for drug discovery. Although there exist many approaches for single target based drug design and target inference, recent years have seen a paradigm shift to system-level pharmacological research. Pathway analysis of genomics data represents one promising direction for computational inference of drug targets. This article aims at providing a comprehensive review on the evolving issues is this field, covering methodological developments, their pros and cons, as well as future research directions. PMID:23369829
Characterizing Cancer Drug Response and Biological Correlates: A Geometric Network Approach.

PubMed

Pouryahya, Maryam; Oh, Jung Hun; Mathews, James C; Deasy, Joseph O; Tannenbaum, Allen R

2018-04-23

In the present work, we apply a geometric network approach to study common biological features of anticancer drug response. We use for this purpose the panel of 60 human cell lines (NCI-60) provided by the National Cancer Institute. Our study suggests that mathematical tools for network-based analysis can provide novel insights into drug response and cancer biology. We adopted a discrete notion of Ricci curvature to measure, via a link between Ricci curvature and network robustness established by the theory of optimal mass transport, the robustness of biological networks constructed with a pre-treatment gene expression dataset and coupled the results with the GI50 response of the cell lines to the drugs. Based on the resulting drug response ranking, we assessed the impact of genes that are likely associated with individual drug response. For genes identified as important, we performed a gene ontology enrichment analysis using a curated bioinformatics database which resulted in biological processes associated with drug response across cell lines and tissue types which are plausible from the point of view of the biological literature. These results demonstrate the potential of using the mathematical network analysis in assessing drug response and in identifying relevant genomic biomarkers and biological processes for precision medicine.
Data science approaches to pharmacogenetics.

PubMed

Penrod, N M; Moore, J H

2014-01-01

Pharmacogenetic studies rely on applied statistics to evaluate genetic data describing natural variation in response to pharmacotherapeutics such as drugs and vaccines. In the beginning, these studies were based on candidate gene approaches that specifically focused on efficacy or adverse events correlated with variants of single genes. This hypothesis driven method required the researcher to have a priori knowledge of which genes or gene sets to investigate. According to rational design, the focus of these studies has been on drug metabolizing enzymes, drug transporters, and drug targets. As technology has progressed, these studies have transitioned to hypothesis-free explorations where markers across the entire genome can be measured in large scale, population based, genome-wide association studies (GWAS). This enables identification of novel genetic biomarkers, therapeutic targets, and analysis of gene-gene interactions, which may reveal molecular mechanisms of drug activities. Ultimately, the challenge is to utilize gene-drug associations to create dosing algorithms based individual genotypes, which will guide physicians and ensure they prescribe the correct dose of the correct drug the first time eliminating trial-and-error and adverse events. We review here basic concepts and applications of data science to the genetic analysis of pharmacologic outcomes.
Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.

PubMed

Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K

2018-02-01

Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.
Development and Evaluation of Cefadroxil Drug Loaded Biopolymeric Films Based on Chitosan-Furfural Schiff Base

PubMed Central

Dixit, Ritu B.; Uplana, Rahul A.; Patel, Vishnu A.; Dixit, Bharat C.; Patel, Tarosh S.

2010-01-01

Cefadroxil drug loaded biopolymeric films of chitosan-furfural schiff base were prepared by reacting chitosan with furfural in presence of acetic acid and perchloric acid respectively for the external use. Prepared films were evaluated for their strength, swelling index, thickness, drug content, uniformity, tensile strength, percent elongation, FTIR spectral analysis and SEM. The results of in vitro diffusion studies revealed that the films exhibited enhanced drug diffusion as compared to the films prepared using untreated chitosan. The films also demonstrated good to moderate antibacterial activities against selective gram positive and gram negative bacteria. PMID:21179325
SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

PubMed

Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

2013-03-01

Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Impact of Modified System of Objectified Judgement Analysis (SOJA) methodology on prescribing costs of ACE inhibitors.

PubMed

Alabbadi, Ibrahim; Crealey, Grainne; Scott, Michael; Baird, Simon; Trouton, Tom; Mairs, Jill; McElnay, James

2006-01-01

System of Objectified Judgement Analysis (SOJA) is a structured approach to the selection of drugs for formulary inclusion. How- ever, while SOJA is a very important advance in drug selection for formulary purposes, it is hospital based and can only be applied to one indication at a time. In SOJA, cost has been given a primary role in the selection process as it has been included as a selection criterion from the start. Cost may therefore drive the selection of a particular drug product at the expense of other basic criteria such as safety or efficacy. The aims of this study were to use a modified SOJA approach in the selection of ACE inhibitors (ACEIs) for use in a joint formulary that bridges primary and secondary care within a health board in Northern Ireland, and to investigate the potential impact of the joint formulary on prescribing costs of ACEIs in that health board. The modified SOJA approach involved four phases in sequence: an evidence-based pharmacotherapeutic evaluation of all available ACEI drug entities, a separate safety/risk assessment analysis of products containing agents that exceeded the pharmacotherapeutic threshold, a budget-impact analysis and, finally, the selection of product lines. A comprehensive literature review and expert panel judgement informed the selection of criteria (and their relative weighting) for the pharmacotherapeutic evaluation. The resultant criteria/scoring system was circulated (in questionnaire format) to prescribers and stakeholders for comment. Based on statistical analysis of the latter survey results, the final scoring system was developed. Drug entities that exceeded the evidence threshold were sequentially entered into the second and third phases of the process. Five drug entities (11 currently available in the UK) exceeded the evidence threshold and 22 of 26 submitted product lines containing these drug entities satisfied the safety/risk assessment criteria. Three product lines, each containing a different drug entity, were selected for formulary inclusion after budget impact analysis was performed. The estimated potential annual cost savings for ACEIs (based on estimated annual usage in defined daily doses) for this particular health board was 42%. The modified SOJA approach has a significant contribution to make in containing the costs of ACEIs. Applying modified SOJA as a practical method for all indications will allow the development of a unified formulary that bridges secondary and primary care.
Effects of 99mTc-TRODAT-1 drug template on image quantitative analysis

PubMed Central

Yang, Bang-Hung; Chou, Yuan-Hwa; Wang, Shyh-Jen; Chen, Jyh-Cheng

2018-01-01

99mTc-TRODAT-1 is a type of drug that can bind to dopamine transporters in living organisms and is often used in SPCT imaging for observation of changes in the activity uptake of dopamine in the striatum. Therefore, it is currently widely used in studies on clinical diagnosis of Parkinson’s disease (PD) and movement-related disorders. In conventional 99mTc-TRODAT-1 SPECT image evaluation, visual inspection or manual selection of ROI for semiquantitative analysis is mainly used to observe and evaluate the degree of striatal defects. However, these methods are dependent on the subjective opinions of observers, which lead to human errors, have shortcomings such as long duration, increased effort, and have low reproducibility. To solve this problem, this study aimed to establish an automatic semiquantitative analytical method for 99mTc-TRODAT-1. This method combines three drug templates (one built-in SPECT template in SPM software and two self-generated MRI-based and HMPAO-based TRODAT-1 templates) for the semiquantitative analysis of the striatal phantom and clinical images. At the same time, the results of automatic analysis of the three templates were compared with results from a conventional manual analysis for examining the feasibility of automatic analysis and the effects of drug templates on automatic semiquantitative analysis results. After comparison, it was found that the MRI-based TRODAT-1 template generated from MRI images is the most suitable template for 99mTc-TRODAT-1 automatic semiquantitative analysis. PMID:29543874
Drug use to resistance exercise-induced fatigue based on diclofenac diethylamine emulgel efficacy analysis.

PubMed

Gu, Qi

2017-05-01

In this paper, the author study on the effect of drug treatment on sports injury, and makes a comparative analysis of drug effects. In sports, the incidence of various types of injuries is increasing, especially in muscle injury. In the experiment, we compared the effects of three different drugs on the treatment and relief of muscle loss. After 3 weeks, the average optical density of desmin in muscle fiber positive region have decreased, as xiaotong plaster (0.4708±0.0126), votalin (0.5124±0.0264) and placebo (0.3856±0.0312). It has a certain effect to promote the repair and regeneration of desmin expression by drugs. Through the analysis of the effect of drug intervention on sports injury repair, we can effectively improve the therapeutic effect of sports injury.
A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.
Drug Synthesis and Analysis on a Dime: A Capstone Medicinal Chemistry Experience for the Undergraduate Biochemistry Laboratory

ERIC Educational Resources Information Center

Streu, Craig N.; Reif, Randall D.; Neiles, Kelly Y.; Schech, Amanda J.; Mertz, Pamela S.

2016-01-01

Integrative, research-based experiences have shown tremendous potential as effective pedagogical approaches. Pharmaceutical development is an exciting field that draws heavily on organic chemistry and biochemistry techniques. A capstone drug synthesis/analysis laboratory is described where biochemistry students synthesize azo-stilbenoid compounds…
Analysis of a Suspected Drug Sample

ERIC Educational Resources Information Center

Schurter, Eric J.; Zook-Gerdau, Lois Anne; Szalay, Paul

2011-01-01

This general chemistry laboratory uses differences in solubility to separate a mixture of caffeine and aspirin while introducing the instrumental analysis methods of GCMS and FTIR. The drug mixture is separated by partitioning aspirin and caffeine between dichloromethane and aqueous base. TLC and reference standards are used to identify aspirin…
Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods.

PubMed

Salvatore, Stefania; Bramness, Jørgen Gustav; Reid, Malcolm J; Thomas, Kevin Victor; Harman, Christopher; Røislien, Jo

2015-01-01

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.
Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery.

PubMed

Hall, David R; Kozakov, Dima; Whitty, Adrian; Vajda, Sandor

2015-11-01

Analysis of binding energy hot spots at protein surfaces can provide crucial insights into the prospects for successful application of fragment-based drug discovery (FBDD), and whether a fragment hit can be advanced into a high-affinity, drug-like ligand. The key factor is the strength of the top ranking hot spot, and how well a given fragment complements it. We show that published data are sufficient to provide a sophisticated and quantitative understanding of how hot spots derive from a protein 3D structure, and how their strength, number, and spatial arrangement govern the potential for a surface site to bind to fragment-sized and larger ligands. This improved understanding provides important guidance for the effective application of FBDD in drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.
Tenofovir-based regimens associated with less drug resistance in HIV-1-infected Nigerians failing first-line antiretroviral therapy.

PubMed

Etiebet, Mary-Ann A; Shepherd, James; Nowak, Rebecca G; Charurat, Man; Chang, Harry; Ajayi, Samuel; Elegba, Olufunmilayo; Ndembi, Nicaise; Abimiku, Alashle; Carr, Jean K; Eyzaguirre, Lindsay M; Blattner, William A

2013-02-20

In resource-limited settings, HIV-1 drug resistance testing to guide antiretroviral therapy (ART) selection is unavailable. We retrospectively conducted genotypic analysis on archived samples from Nigerian patients who received targeted viral load testing to confirm treatment failure and report their drug resistance mutation patterns. Stored plasma from 349 adult patients on non-nucleoside reverse transcriptase inhibitor (NNRTI) regimens was assayed for HIV-1 RNA viral load, and samples with more than 1000 copies/ml were sequenced in the pol gene. Analysis for resistance mutations utilized the IAS-US 2011 Drug Resistance Mutation list. One hundred and seventy-five samples were genotyped; the majority of the subtypes were G (42.9%) and CRF02_AG (33.7%). Patients were on ART for a median of 27 months. 90% had the M184V/I mutation, 62% had at least one thymidine analog mutation, and 14% had the K65R mutation. 97% had an NNRTI resistance mutation and 47% had at least two etravirine-associated mutations. In multivariate analysis tenofovir-based regimens were less likely to have at least three nucleoside reverse transcriptase inhibitor (NRTI) mutations after adjusting for subtype, previous ART, CD4, and HIV viral load [P < 0.001, odds ratio (OR) 0.04]. 70% of patients on tenofovir-based regimens had at least two susceptible NRTIs to include in a second-line regimen compared with 40% on zidovudine-based regimens (P = 0.04, OR = 3.4). At recognition of treatment failure, patients on tenofovir-based first-line regimens had fewer NRTI drug-resistant mutations and more active NRTI drugs available for second-line regimens. These findings can inform strategies for ART regimen sequencing to optimize long-term HIV treatment outcomes in low-resource settings.
Mechanism-based risk assessment strategy for drug-induced cholestasis using the transcriptional benchmark dose derived by toxicogenomics.

PubMed

Kawamoto, Taisuke; Ito, Yuichi; Morita, Osamu; Honda, Hiroshi

2017-01-01

Cholestasis is one of the major causes of drug-induced liver injury (DILI), which can result in withdrawal of approved drugs from the market. Early identification of cholestatic drugs is difficult due to the complex mechanisms involved. In order to develop a strategy for mechanism-based risk assessment of cholestatic drugs, we analyzed gene expression data obtained from the livers of rats that had been orally administered with 12 known cholestatic compounds repeatedly for 28 days at three dose levels. Qualitative analyses were performed using two statistical approaches (hierarchical clustering and principle component analysis), in addition to pathway analysis. The transcriptional benchmark dose (tBMD) and tBMD 95% lower limit (tBMDL) were used for quantitative analyses, which revealed three compound sub-groups that produced different types of differential gene expression; these groups of genes were mainly involved in inflammation, cholesterol biosynthesis, and oxidative stress. Furthermore, the tBMDL values for each test compound were in good agreement with the relevant no observed adverse effect level. These results indicate that our novel strategy for drug safety evaluation using mechanism-based classification and tBMDL would facilitate the application of toxicogenomics for risk assessment of cholestatic DILI.
Towards a Consistent and Scientifically Accurate Drug Ontology.

PubMed

Hogan, William R; Hanna, Josh; Joseph, Eric; Brochhausen, Mathias

2013-01-01

Our use case for comparative effectiveness research requires an ontology of drugs that enables querying National Drug Codes (NDCs) by active ingredient, mechanism of action, physiological effect, and therapeutic class of the drug products they represent. We conducted an ontological analysis of drugs from the realist perspective, and evaluated existing drug terminology, ontology, and database artifacts from (1) the technical perspective, (2) the perspective of pharmacology and medical science (3) the perspective of description logic semantics (if they were available in Web Ontology Language or OWL), and (4) the perspective of our realism-based analysis of the domain. No existing resource was sufficient. Therefore, we built the Drug Ontology (DrOn) in OWL, which we populated with NDCs and other classes from RxNorm using only content created by the National Library of Medicine. We also built an application that uses DrOn to query for NDCs as outlined above, available at: http://ingarden.uams.edu/ingredients. The application uses an OWL-based description logic reasoner to execute end-user queries. DrOn is available at http://code.google.com/p/dr-on.

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis.

PubMed

Lee, Hyokyeong; Moody-Davis, Asher; Saha, Utsab; Suzuki, Brian M; Asarnow, Daniel; Chen, Steven; Arkin, Michelle; Caffrey, Conor R; Singh, Rahul

2012-01-01

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind.
Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis

PubMed Central

2012-01-01

Background Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. Method We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. Results We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. Conclusions The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind. PMID:22369037
Lifetime use of illicit drugs and associated factors among Brazilian schoolchildren, National Adolescent School-based Health Survey (PeNSE 2012).

PubMed

Horta, Rogério Lessa; Horta, Bernardo Lessa; da Costa, Andre Wallace Nery; do Prado, Rogério Ruscitto; Oliveira-Campos, Maryane; Malta, Deborah Carvalho

2014-01-01

This study aimed at describing the prevalence of illicit drug use among 9th grade students in the morning period of public and private schools in Brazil, and assessing associated factors. The Brazilian survey PeNSE (National Adolescent School-based Health Survey) 2012 evaluated a representative sample of 9th grade students in the morning period, in Brazil and its five regions. The use of illicit drugs at least once in life was assessed for the most commonly used drugs, such as marijuana, cocaine, crack, solvent-based glue, general ether-based inhalants, ecstasy and oxy. Data were subjected to descriptive analysis, and Pearson's χ² test and logistic regression was used in the multivariate analysis. The use of illicit drugs at least once in life was reported by 7.3% (95%CI 5.3 - 9.4) of the respondents. Logistic regression was used for multivariate analysis and the evidences suggest that illicit drug use is associated to social conditions of greater consumption power, the use of alcohol and tobacco, behaviors related to socialization, such as having friends or sexual activity, and also the perception of loneliness, loose contact between school and parents and experiences of abuse in the family environment. The outcome was inversely associated with close contact with parents and parental supervision. In addition to the association with the processes of socialization and consumption, the influence of family and school is expressed in a particularly protective manner in different records of direct supervision and care.
Prioritizing Therapeutics for Lung Cancer: An Integrative Meta-analysis of Cancer Gene Signatures and Chemogenomic Data

PubMed Central

Fortney, Kristen; Griesman, Joshua; Kotlyar, Max; Pastrello, Chiara; Angeli, Marc; Sound-Tsao, Ming; Jurisica, Igor

2015-01-01

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain. PMID:25786242
Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.
A New Carbon Nanotube-Based Breast Cancer Drug Delivery System: Preparation and In Vitro Analysis Using Paclitaxel.

PubMed

Shao, Wei; Paul, Arghya; Rodes, Laetitia; Prakash, Satya

2015-04-01

Paclitaxel (PTX) is one of the most important drugs for breast cancer; however, the drug effects are limited by its systematic toxicity and poor water solubility. Nanoparticles have been applied for delivery of cancer drugs to overcome their limitations. Toward this goal, a novel single-walled carbon nanotube (SWNT)-based drug delivery system was developed by conjugation of human serum albumin (HSA) nanoparticles for loading of antitumor agent PTX. The nanosized macromolecular SWNT-drug carrier (SWNT-HSA) was characterized by TEM, UV-Vis-NIR spectrometry, and TGA. The SWNT-based drug carrier displayed high intracellular delivery efficiency (cell uptake rate of 80%) in breast cancer MCF-7 cells, as examined by fluorescence-labeled drug carriers, suggesting the needle-shaped SWNT-HSA drug carrier was able to transport drugs across cell membrane despite its macromolecular structure. The drug loading on SWNT-based drug carrier was through high binding affinity of PTX to HSA proteins. The PTX formulated with SWNT-HSA showed greater growth inhibition activity in MCF-7 breast cancer cells than PTX formulated with HSA nanoparticle only (cell viability of 63 vs 70% in 48 h and 53 vs 62% in 72 h). The increased drug efficacy could be driven by SWNT-mediated cell internalization. These data suggest that the developed SWNT-based antitumor agent is functional and effective. However, more studies for in vivo drug delivery efficacy and other properties are needed before this delivery system can be fully realized.
Anti-inflammatory drugs and prediction of new structures by comparative analysis.

PubMed

Bartzatt, Ronald

2012-01-01

Nonsteroidal anti-inflammatory drugs (NSAIDs) are a group of agents important for their analgesic, anti-inflammatory, and antipyretic properties. This study presents several approaches to predict and elucidate new molecular structures of NSAIDs based on 36 known and proven anti-inflammatory compounds. Based on 36 known NSAIDs the mean value of Log P is found to be 3.338 (standard deviation= 1.237), mean value of polar surface area is 63.176 Angstroms2 (standard deviation = 20.951 A2), and the mean value of molecular weight is 292.665 (standard deviation = 55.627). Nine molecular properties are determined for these 36 NSAID agents, including Log P, number of -OH and -NHn, violations of Rule of 5, number of rotatable bonds, and number of oxygens and nitrogens. Statistical analysis of these nine molecular properties provides numerical parameters to conform to in the design of novel NSAID drug candidates. Multiple regression analysis is accomplished using these properties of 36 agents followed with examples of predicted molecular weight based on minimum and maximum property values. Hierarchical cluster analysis indicated that licofelone, tolfenamic acid, meclofenamic acid, droxicam, and aspirin are substantially distinct from all remaining NSAIDs. Analysis of similarity (ANOSIM) produced R = 0.4947, which indicates low to moderate level of dissimilarity between these 36 NSAIDs. Non-hierarchical K-means cluster analysis separated the 36 NSAIDs into four groups having members of greatest similarity. Likewise, discriminant analysis divided the 36 agents into two groups indicating the greatest level of distinction (discrimination) based on nine properties. These two multivariate methods together provide investigators a means to compare and elucidate novel drug designs to 36 proven compounds and ascertain to which of those are most analogous in pharmacodynamics. In addition, artificial neural network modeling is demonstrated as an approach to predict numerous molecular properties of new drug designs that is based on neural training from 36 proven NSAIDs. Comprehensive and effective approaches are presented in this study for the design of new NSAID type agents which are so very important for inhibition of COX-2 and COX-1 isoenzymes.
Relating drug–protein interaction network with drug side effects

PubMed Central

Mizutani, Sayaka; Pauwels, Edouard; Stoven, Véronique; Goto, Susumu; Yamanishi, Yoshihiro

2012-01-01

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles. Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/. Availability: Software is available at the above supplementary website. Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp PMID:22962476
A Chemogenomic Analysis of Ionization Constants - Implications for Drug Discovery

PubMed Central

Manallack, David T.; Prankerd, Richard J.; Nassta, Gemma C.; Ursu, Oleg; Oprea, Tudor I.; Chalmers, David K.

2013-01-01

Chemogenomics methods seek to characterize the interaction between drugs and biological systems and are an important guide for the selection of screening compounds. The acid/base character of drugs has a profound influence on their affinity for the receptor, on their absorption, distribution, metabolism, excretion and toxicity (ADMET) profile and the way the drug can be formulated. In particular, the charge state of a molecule greatly influences its lipophilicity and biopharmaceutical characteristics. This study investigates the acid/base profile of human small molecule drugs, chemogenomics datasets and screening compounds including a natural products set. We estimate the ionization constants (pKa values) of these compounds and determine the identity of the ionizable functional groups in each set. We find substantial differences in acid/base profiles of the chemogenomic classes. In many cases, these differences can be linked to the nature of the target binding site and the corresponding functional groups needed for recognition of the ligand. Clear differences are also observed between the acid/base characteristics of drugs and screening compounds. For example, the proportion of drugs containing a carboxylic acid was 20%, in stark contrast to a value of 2.4% for the screening set sample. The proportion of aliphatic amines was 27% for drugs and only 3.4% for screening compounds. This suggests that there is a mismatch between commercially available screening compounds and the compounds that are likely to interact with a given chemogenomic target family. Our analysis provides a guide for the selection of screening compounds to better target specific chemogenomic families with regard to the overall balance of acids, bases and pKa distributions. PMID:23303535
Are Evidence Standards Different for Genomic- vs. Clinical-Based Precision Medicine? A Quantitative Analysis of Individualized Warfarin Therapy.

PubMed

Dhanda, D S; Guzauskas, G F; Carlson, J J; Basu, A; Veenstra, D L

2017-11-01

Evidence requirements for implementation of precision medicine (PM), whether informed by genomic or clinical data, are not well defined. Evidence requirements are driven by uncertainty and its attendant consequences; these aspects can be quantified by a novel technique in health economics: value of information analysis (VOI). We utilized VOI analysis to compare the evidence levels over time for warfarin dosing based on pharmacogenomic vs. amiodarone-warfarin drug-drug interaction information. The primary outcome was the expected value of perfect information (EVPI), which is an estimate of the upper limit of the societal value of conducting future research. Over the past decade, the EVPI for the pharmacogenomic strategy decreased from $1,550 to $140 vs. $1,220 to $280 per patient for the drug-interaction strategy. Evidence levels thus appear to be higher for pharmacogenomic-guided vs. drug-interaction-guided warfarin dosing. Clinical guidelines and reimbursement policies for warfarin PM could be informed by these findings. © 2017 American Society for Clinical Pharmacology and Therapeutics.
In vitro FTIR microspectroscopy analysis of primary oral squamous carcinoma cells treated with cisplatin and 5-fluorouracil: a new spectroscopic approach for studying the drug-cell interaction.

PubMed

Giorgini, Elisabetta; Sabbatini, Simona; Rocchetti, Romina; Notarstefano, Valentina; Rubini, Corrado; Conti, Carla; Orilisi, Giulia; Mitri, Elisa; Bedolla, Diana E; Vaccari, Lisa

2018-06-22

In the present study, human primary oral squamous carcinoma cells treated with cisplatin and 5-fluorouracil were analyzed, for the first time, by in vitro FTIR Microspectroscopy (FTIRM), to improve the knowledge on the biochemical pathways activated by these two chemotherapy drugs. To date, most of the studies regarding FTIRM cellular analysis have been executed on fixed cells from immortalized cell lines. FTIRM analysis performed on primary tumor cells under controlled hydrated conditions provides more reliable information on the biochemical processes occurring in in vivo tumor cells. This spectroscopic analysis allows to get on the same sample and at the same time an overview of the composition and structure of the most remarkable cellular components. In vitro FTIRM analysis of primary oral squamous carcinoma cells evidenced a time-dependent drug-specific cellular response, also including apoptosis triggering. Furthermore, the univariate and multivariate analyses of IR data evidenced meaningful spectroscopic differences ascribable to alterations affecting cellular proteins, lipids and nucleic acids. These findings suggest for the two drugs different pathways and extents of cellular damage, not provided by conventional cell-based assays (MTT assay and image-based cytometry).
Examination of the regulatory frameworks applicable to biologic drugs (including stem cells and their progeny) in Europe, the U.S., and Australia: part I--a method of manual documentary analysis.

PubMed

Ilic, Nina; Savic, Snezana; Siegel, Evan; Atkinson, Kerry; Tasic, Ljiljana

2012-12-01

Recent development of a wide range of regulatory standards applicable to production and use of tissues, cells, and other biologics (or biologicals), as advanced therapies, indicates considerable interest in the regulation of these products. The objective of this study was to analyze and compare high-tier documents within the Australian, European, and U.S. biologic drug regulatory environments using qualitative methodology. Cohort 1 of the selected 18 high-tier regulatory documents from the European Medicines Agency (EMA), the U.S. Food and Drug Administration (FDA), and the Therapeutic Goods Administration (TGA) regulatory frameworks were subject to a manual documentary analysis. These documents were consistent with the legal requirements for manufacturing and use of biologic drugs in humans and fall into six different categories. Manual analysis included a terminology search. The occurrence, frequency, and interchangeable use of different terms and phrases were recorded in the manual documentary analysis. Despite obvious differences, manual documentary analysis revealed certain consistency in use of terminology across analyzed frameworks. Phrase search frequencies have shown less uniformity than the search of terms. Overall, the EMA framework's documents referred to "medicinal products" and "marketing authorization(s)," the FDA documents discussed "drug(s)" or "biologic(s)," and the TGA documents referred to "biological(s)." Although high-tier documents often use different terminology they share concepts and themes. Documents originating from the same source have more conjunction in their terminology although they belong to different frameworks (i.e., Good Clinical Practice requirements based on the Declaration of Helsinki, 1964). Automated (software-based) documentary analysis should be obtained for the conceptual and relational analysis.
[Analysis of Late AMNOG Benefit Assessments].

PubMed

Rieder, Veronika; Hammerschmidt, Thomas

2018-04-26

Since 2011, new drugs are assessed at the time of launch in Germany (AMNOG). Based on this early benefit assessment (EBA), drug prices are negotiated. At this time, the evidence base might be weak. A later benefit assessment (LBA) is not done on a regular basis except for selected drugs. Our objective was to analyze the impact of LBAs of drugs for the same indication. Analysis of all completed LBAs between 2011 and 2016. 228 benefit assessments have been performed since 2011. 26 drugs were assessed twice for the same indication. Oncology and diabetes were the most common therapeutic areas in LBA and more pronounced than in EBA. 15 LBAs were due to the EBAs having a time limitation because of insufficient evidence base partially based on conditional approval. Time between EBA and LBA was 2.6 years. All 15 drugs had added benefit in the EBA, 4 got a better, 5 a worse assessment in the LBA. Seven drugs without added benefit in the EBA were assessed at the request of the manufacturer because of new data after 1.7 years. Three drugs could show added benefit in the LBA. Finally, 4 orphan drugs were reassessed according to the AMNOG regulation after achieving annual sales of 50 million euros. One got a better, 2 got a worse benefit assessment. Average improvement of benefit was +1.5 on a scale between - 3 (worst negative benefit) and +9 (highest positive benefit). Average deterioration of added benefit was - 1.4. Negotiated prices were significantly correlated with the change in the benefit assessment. LBA on a broader evidence base did not result in a significantly changed outcome. A general LBA for all drugs does not appear to be necessary because of the limited effect on the benefit assessment and the price when considering cost and administrative burden of the AMNOG benefit assessment. The selective approach of LBA for specific drugs is sufficient in cases in which the evidence base was limited at launch. © Georg Thieme Verlag KG Stuttgart · New York.
Drug Resistance Strategies Rural Hawaiian Youth of as a Function of Drug Offerers and Substances: A Community Stakeholder Analysis

PubMed Central

Okamoto, Scott K.; Helm, Susana; Kulis, Stephen; Delp, Justin A.; Dinson, Ay-Laina

2012-01-01

This study examined the variations in drug resistance strategies endorsed by community members for rural Native Hawaiian youth in drug-related problem situations. Community stakeholders completed a Web-based survey focused on drug-related problem scenarios and their matched set of responses developed by middle/intermediate school youth in prior research. Mean differences were examined based on drug offerers described in the scenarios (i.e., peers/friends, cousins, and parents) and the substances offered in the scenarios (i.e., marijuana and alcohol). Compared with other strategies, Refuse had the highest mean scores within two offerer subgroups (peers/friends and cousins) and within both substances (alcohol and marijuana). Leave had the highest mean score within scenarios describing drug offers from parents. The endorsement of different resistance strategies varied based on drug offerers and substances offered in the selected scenarios. This study suggests that resistance skills in prevention should be tailored to youths’ social context in rural Hawai‘i. PMID:24212171
Drug Target Mining and Analysis of the Chinese Tree Shrew for Pharmacological Testing

PubMed Central

Liu, Jie; Lee, Wen-hui; Zhang, Yun

2014-01-01

The discovery of new drugs requires the development of improved animal models for drug testing. The Chinese tree shrew is considered to be a realistic candidate model. To assess the potential of the Chinese tree shrew for pharmacological testing, we performed drug target prediction and analysis on genomic and transcriptomic scales. Using our pipeline, 3,482 proteins were predicted to be drug targets. Of these predicted targets, 446 and 1,049 proteins with the highest rank and total scores, respectively, included homologs of targets for cancer chemotherapy, depression, age-related decline and cardiovascular disease. Based on comparative analyses, more than half of drug target proteins identified from the tree shrew genome were shown to be higher similarity to human targets than in the mouse. Target validation also demonstrated that the constitutive expression of the proteinase-activated receptors of tree shrew platelets is similar to that of human platelets but differs from that of mouse platelets. We developed an effective pipeline and search strategy for drug target prediction and the evaluation of model-based target identification for drug testing. This work provides useful information for future studies of the Chinese tree shrew as a source of novel targets for drug discovery research. PMID:25105297
Managed Entry Agreements for Oncology Drugs: Lessons from the European Experience to Inform the Future

PubMed Central

Pauwels, Kim; Huys, Isabelle; Vogler, Sabine; Casteels, Minne; Simoens, Steven

2017-01-01

Objectives: The aim of this study is to conduct an analysis on the regulation and application of managed entry agreements (MEA) for oncology drugs across different European countries. Methods: Literature search and document analysis were performed between September 2015 and June 2016 to collect information on the regulatory framework and practice of MEA in Belgium, The Netherlands, Scotland, England and Wales, Sweden, Italy, Czech Republic and France. An overview of the content and typology of MEA applied for oncology drugs between 2008 and 2015 was generated based on publically available sources and contributions by national health authorities. Semi-structured interviews were conducted with representatives of national health authorities involved in the management or negotiation of MEA. Results: The application of MEA differs across countries and across different indications for the same drug. Financial based agreements are prevailing due to their simplicity compared to performance-based agreements. Performance-based agreements are less commonly applied in the European countries except for Italy. In the Netherlands, application of performance-based agreements was stopped due to their inability to deal with dynamics in the market, which is highly relevant for oncology drugs. Conclusions: MEA constitute a common policy tool that public payers in European countries use to ensure early access to highly priced oncology drugs. In light of strengths and weaknesses observed for MEA and the expected developments in the oncology area, the importance of MEA is likely to grow in the future. PMID:28420990
Investigation of the Study Characteristics Affecting Clinical Trial Quality Using the Protocol Deviations Leading to Exclusion of Subjects From the Per Protocol Set Data in Studies for New Drug Application: A Retrospective Analysis.

PubMed

Kohara, Norihito; Kaneko, Masayuki; Narukawa, Mamoru

2018-01-01

The concept of the risk-based approach has been introduced as an effort to secure the quality of clinical trials. In the risk-based approach, identification and evaluation of risk in advance are considered important. For recently completed clinical trials, we investigated the relationship between study characteristics and protocol deviations leading to the exclusion of subjects from Per Protocol Set (PPS) efficacy analysis. New drugs approved in Japan in the fiscal year 2014-2015 were targeted in the research. The reasons for excluding subjects from the PPS efficacy analysis were described in 102 trials out of 492 in the summary of new drug application documents, which was publicly disclosed after the drug's regulatory approval. The author extracted these reasons along with the numbers of the cases and the study characteristics of each clinical trial. Then, the direct comparison, univariate regression analysis, and multivariate regression analysis was carried out based on the exclusion rate. The study characteristics for which exclusion of subjects from the PPS efficacy analysis were frequently observed was multiregional clinical trials in study region; inhalant and external use in administration route; Anti-infective for systemic use; Respiratory system, Dermatologicals, and Nervous system in therapeutic drug under the Anatomical Therapeutic Chemical Classification. In the multivariate regression analysis, the clinical trial variables of inhalant, Respiratory system, or Dermatologicals were selected as study characteristics leading to a higher exclusion rate. The characteristics of the clinical trial that is likely to cause protocol deviations that will affect efficacy analysis were suggested. These studies should be considered for specific attention and priority observation in the trial protocol or its monitoring plan and execution, such as a clear description of inclusion/exclusion criteria in the protocol, development of training materials to site staff, and/or trial subjects as specific risk-alleviating measures.
From "herbal highs" to the "heroin of cannabis": Exploring the evolving discourse on synthetic cannabinoid use in a Norwegian Internet drug forum.

PubMed

Bilgrei, Ola Røed

2016-03-01

In the early 2000s, online vendors began selling an array of so-called "legal highs"--apparently organic produce made from exotic herbs. Simultaneously, members of online drug discussion forums began to debate the alleged effects of the new drugs, creating an enormous base of user-derived information based on personal experiences. This study combines the historical data spanning a seven-year period derived from a Norwegian drug discussion forum about synthetic cannabinoids and interviews with 14 male forum members who all had experience with the drug. By combining the two sources, this study reveals not only the evolving discourse on synthetic cannabinoid use but also how forum members related to the online information that they gathered and co-produced. Analysis of the evolving online discourse revealed three distinct phases. The first was an enthusiastic phase, with users embracing the new drugs. The second was a phase characterized by growing ambivalence and scepticism towards use of the drugs. The third was one in which members of the community rejected the new drugs based on negative reviews from users. The analysis displays the communal process whereby members co-operate in the exchange of an extensive body of knowledge accumulated about synthetic cannabinoids, and the way in which this evolving discourse influences members of the forum in their views and representations of the drugs. Paradoxically, the online discussions of synthetic cannabinoids, which had great significance for their proliferation when they were initially introduced to the market, now seem to be a deterrent. The role of online drug communities in the development of new drug trends should receive renewed attention. Copyright © 2016 Elsevier B.V. All rights reserved.
Can Disproportionality Analysis of Post-marketing Case Reports be Used for Comparison of Drug Safety Profiles?

PubMed

Michel, Christiane; Scosyrev, Emil; Petrin, Michael; Schmouder, Robert

2017-05-01

Clinical trials usually do not have the power to detect rare adverse drug reactions. Spontaneous adverse reaction reports as for example available in post-marketing safety databases such as the FDA Adverse Event Reporting System (FAERS) are therefore a valuable source of information to detect new safety signals early. To screen such large data-volumes for safety signals, data-mining algorithms based on the concept of disproportionality have been developed. Because disproportionality analysis is based on spontaneous reports submitted for a large number of drugs and adverse event types, one might consider using these data to compare safety profiles across drugs. In fact, recent publications have promoted this practice, claiming to provide guidance on treatment decisions to healthcare decision makers. In this article we investigate the validity of this approach. We argue that disproportionality cannot be used for comparative drug safety analysis beyond basic hypothesis generation because measures of disproportionality are: (1) missing the incidence denominators, (2) subject to severe reporting bias, and (3) not adjusted for confounding. Hypotheses generated by disproportionality analyses must be investigated by more robust methods before they can be allowed to influence clinical decisions.
Choice of generic antihypertensive drugs for the primary prevention of cardiovascular disease--a cost-effectiveness analysis.

PubMed

Wisløff, Torbjørn; Selmer, Randi M; Halvorsen, Sigrun; Fretheim, Atle; Norheim, Ole F; Kristiansen, Ivar Sønbø

2012-04-04

Hypertension is one of the leading causes of cardiovascular disease (CVD). A range of antihypertensive drugs exists, and their prices vary widely mainly due to patent rights. The objective of this study was to explore the cost-effectiveness of different generic antihypertensive drugs as first, second and third choice for primary prevention of cardiovascular disease. We used the Norwegian Cardiovascular Disease model (NorCaD) to simulate the cardiovascular life of patients from hypertension without symptoms until they were all dead or 100 years old. The risk of CVD events and costs were based on recent Norwegian sources. In single-drug treatment, all antihypertensives are cost-effective compared to no drug treatment. In the base-case analysis, the first, second and third choice of antihypertensive were calcium channel blocker, thiazide and angiotensin-converting enzyme inhibitor. However the sensitivity and scenario analyses indicated considerable uncertainty in that angiotensin receptor blockers as well as, angiotensin-converting enzyme inhibitors, beta blockers and thiazides could be the most cost-effective antihypertensive drugs. Generic antihypertensives are cost-effective in a wide range of risk groups. There is considerable uncertainty, however, regarding which drug is the most cost-effective.

Investigation of drug products received for analysis in the Swedish STRIDA project on new psychoactive substances.

PubMed

Bäckberg, Matilda; Jönsson, Karl-Henrik; Beck, Olof; Helander, Anders

2018-02-01

The web-based open sale of unregulated new psychoactive substances (NPS) has shown a steady increase in recent years. Analysis of drug products sold as NPS is useful to confirm the true chemical contents, for comparison with the substances detected in corresponding body fluids, but also to study drug trends. This work describes the examination of 251 drug products that were randomly submitted for analysis in 173 cases of suspected NPS-related intoxications in the Swedish STRIDA project in 2010-2015. Of the products, 39% were powders/crystals, 32% tablets/capsules, 16% herbal materials, 8% liquids, 1% blotters, and 4% others. The analysis involved tandem mass spectrometry and nuclear magnetic resonance spectroscopy. In 88 products (35%), classic psychoactive substances, prescription pharmaceuticals, dietary supplements, or doping agents were found; however, in none of these cases had an NPS-related intoxication been indicated from product markings or patient self-reports. Another 12 products tested negative for psychoactive substances. The remaining 151 products contained 86 different NPS (30% contained ≥2 substances). In 104 drug products, a specific NPS ingredient was indicated based on labelling (69%) or patient self-report; in 92 cases this was also analytically confirmed to be correct. Overall, the NPS products submitted for analysis in the STRIDA project showed a high degree of consistency between suspected and actual content (88%). The results of related urine and/or blood analysis further demonstrated that the patients commonly (89%) tested positive for the indicated NPS, but also revealed that polysubstance intoxication was common (83%), indicating use of additional drug products. Copyright © 2017 John Wiley & Sons, Ltd.
Population-based studies of antithyroid drugs and sudden cardiac death

PubMed Central

van Noord, Charlotte; Sturkenboom, Miriam C J M; Straus, Sabine M J M; Hofman, Albert; Witteman, Jacqueline C M; Stricker, Bruno H Ch

2009-01-01

AIM Thyroid free T4 is associated with QTc-interval prolongation, which is a risk factor for sudden cardiac death (SCD). Hyperthyroidism has been associated with SCD in case reports, but there are no population-based studies confirming this. The aim was to investigate whether use of antithyroid drugs (as a direct cause or as an indicator of poorly controlled hyperthyroidism) is associated with an increased risk of SCD. METHODS We studied the occurrence of SCD in a two-step procedure in two different Dutch populations. First, the prospective population-based Rotterdam Study including 7898 participants (≥55 years old). Second, we used the Integrated Primary Care Information (IPCI) database, which is a longitudinal general practice research database to see whether we could replicate results from the first study. Drug use at the index date was assessed with prescription information from automated pharmacies (Rotterdam Study) or drug prescriptions from general practices (IPCI). We used a Cox proportional hazards model in a cohort analysis, adjusted for age, gender and use of QTc prolonging drugs (Rotterdam Study) and conditional logistic regression analysis in a case–control analysis, matched for age, gender, practice and calendar time and adjusted for arrhythmia and cerebrovascular ischaemia (IPCI). RESULTS In the Rotterdam Study, 375 participants developed SCD during follow-up. Current use of antithyroid drugs was associated with SCD [adjusted hazard ratio 3.9; 95% confidence interval (CI) 1.7, 8.7]. IPCI included 1424 cases with SCD and 14 443 controls. Also in IPCI, current use of antithyroid drugs was associated with SCD (adjusted odds ratio 2.9; 95% CI 1.1, 7.4). CONCLUSIONS Use of antithyroid drugs was associated with a threefold increased risk of SCD. Although this might be directly caused by antithyroid drug use, it might be more readily explained by underlying poorly controlled hyperthyroidism, since treated patients who developed SCD still had low thyroid-stimulating hormone levels shortly before death. PMID:19740403
Developing an Integrated, Brief Biobehavioral HIV Prevention Intervention for High-Risk Drug Users in Treatment: The Process and Outcome of Formative Research

PubMed Central

Shrestha, Roman; Altice, Frederick; Karki, Pramila; Copenhaver, Michael

2017-01-01

To date, HIV prevention efforts have largely relied on singular strategies (e.g., behavioral or biomedical approaches alone) with modest HIV risk-reduction outcomes for people who use drugs (PWUD), many of whom experience a wide range of neurocognitive impairments (NCI). We report on the process and outcome of our formative research aimed at developing an integrated biobehavioral approach that incorporates innovative strategies to address the HIV prevention and cognitive needs of high-risk PWUD in drug treatment. Our formative work involved first adapting an evidence-based behavioral intervention—guided by the Assessment–Decision–Administration–Production–Topical experts–Integration–Training–Testing model—and then combining the behavioral intervention with an evidence-based biomedical intervention for implementation among the target population. This process involved eliciting data through structured focus groups (FGs) with key stakeholders—members of the target population (n = 20) and treatment providers (n = 10). Analysis of FG data followed a thematic analysis approach utilizing several qualitative data analysis techniques, including inductive analysis and cross-case analysis. Based on all information, we integrated the adapted community-friendly health recovery program—a brief evidence-based HIV prevention behavioral intervention—with the evidence-based biomedical component [i.e., preexposure prophylaxis (PrEP)], an approach that incorporates innovative strategies to accommodate individuals with NCI. This combination approach—now called the biobehavioral community-friendly health recovery program—is designed to address HIV-related risk behaviors and PrEP uptake and adherence as experienced by many PWUD in treatment. This study provides a complete example of the process of selecting, adapting, and integrating the evidence-based interventions—taking into account both empirical evidence and input from target population members and target organization stakeholders. The resultant brief evidence-based biobehavioral approach could significantly advance primary prevention science by cost-effectively optimizing PrEP adherence and HIV risk reduction within common drug treatment settings. PMID:28553295
Quantitative analysis of the effect of supersaturation on in vivo drug absorption.

PubMed

Takano, Ryusuke; Takata, Noriyuki; Saito, Ryoichi; Furumoto, Kentaro; Higo, Shoichi; Hayashi, Yoshiki; Machida, Minoru; Aso, Yoshinori; Yamashita, Shinji

2010-10-04

The purpose of this study is to clarify the effects of intestinal drug supersaturation on solubility-limited nonlinear absorption. Oral absorption of a novel farnesyltransferase inhibitor (FTI-2600) from its crystalline free base and its HCl salt was determined in dogs. To clarify the contribution of supersaturation on improving drug absorption, in vivo intraluminal concentration of FTI-2600 after oral administration was estimated from the pharmacokinetics data using a physiologically based model. Dissolution and precipitation characteristics of FTI-2600 in a biorelevant media were investigated in vitro using a miniscale dissolution test and powder X-ray diffraction analysis. In the in vitro study, the HCl salt immediately dissolved but precipitated rapidly. The metastable amorphous free base precipitant, which did not convert into the stable crystalline free base in the simulated intestinal fluids for several hours, generated a 5-fold increase in dissolved concentration compared to the equilibrium solubility of the crystalline free base. By computer simulation, the intraluminal drug concentration after administration of the free base was estimated to reach the saturated solubility, indicating solubility-limited absorption. On the other hand, administration of the HCl salt resulted in an increased intraluminal concentration and the plasma concentration was 400% greater than that after administration of the free base. This in vivo/in vitro correlation of the increased drug concentrations in the small intestine provide clear evidence that not only the increase in the dissolution rate, but also the supersaturation phenomenon, improved the solubility-limited absorption of FTI-2600. These results indicate that formulation technologies that can induce supersaturation may be of great assistance to the successful development of poorly water-soluble drugs.
Root Cause Analysis of Quality Defects Using HPLC-MS Fingerprint Knowledgebase for Batch-to-batch Quality Control of Herbal Drugs.

PubMed

Yan, Binjun; Fang, Zhonghua; Shen, Lijuan; Qu, Haibin

2015-01-01

The batch-to-batch quality consistency of herbal drugs has always been an important issue. To propose a methodology for batch-to-batch quality control based on HPLC-MS fingerprints and process knowledgebase. The extraction process of Compound E-jiao Oral Liquid was taken as a case study. After establishing the HPLC-MS fingerprint analysis method, the fingerprints of the extract solutions produced under normal and abnormal operation conditions were obtained. Multivariate statistical models were built for fault detection and a discriminant analysis model was built using the probabilistic discriminant partial-least-squares method for fault diagnosis. Based on multivariate statistical analysis, process knowledge was acquired and the cause-effect relationship between process deviations and quality defects was revealed. The quality defects were detected successfully by multivariate statistical control charts and the type of process deviations were diagnosed correctly by discriminant analysis. This work has demonstrated the benefits of combining HPLC-MS fingerprints, process knowledge and multivariate analysis for the quality control of herbal drugs. Copyright © 2015 John Wiley & Sons, Ltd.
78 FR 24693 - Draft Qualitative Risk Assessment of Risk of Activity/Food Combinations for Activities (Outside...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-26

... Analysis and Risk-Based Preventive Controls for Human Food'' (the proposed preventive controls rule) and... Farm.'' The purpose of the draft RA is to provide a science-based risk analysis of those activity/food... Food, Drug, and Cosmetic Act for hazard analysis and risk-based preventive controls (the proposed...
Estimating the budget impact of orphan medicines in Europe: 2010 - 2020.

PubMed

Schey, Carina; Milanova, Tsveta; Hutchings, Adam

2011-09-27

Orphan drugs are a growing issue of importance to European healthcare policy makers. The success of orphan drug legislation in Europe has resulted in an increasing number of licensed medicines for rare diseases, and many more yet unlicensed products have received orphan drug designation. Increasingly the concerns amongst policy makers relate to issues of patient access and affordability, yet few studies have sought to estimate the future budget impact of orphan drugs. The aim of this study was to predict the total cost of orphan medicines in Europe between 2010 and 2020 as a percentage of total European pharmaceutical expenditure. A disease-based epidemiological model was created based upon trends in the designation and approval of new orphan medicines, prevalence estimates for orphan diseases, and historical price and sales data for orphan drugs in Europe (defined as Eurozone + UK). The analysis incorporated two stages: 1) Predicting the number of diseases for which new orphan drugs will be approved over the next decade, based on an analysis of trends from the EU registry of orphan medicines; 2) Estimating the average ex-factory drug cost across an orphan disease life cycle, from the year in which the first orphan medicine is launched to the point where the first medicine loses marketing exclusivity. The two sets of information were combined to quantify the annual cost of orphan drugs from 2010 through 2020. The results from the model predicted a steady increase in the cumulative number of diseases for which an orphan drug is approved, averaging just over 5 new diseases per year over the next 10 years. The annual per patient cost of existing orphan drugs was seen to vary between €1,251 and €407,631, with the median cost being €32,242 per year. The share of the total pharmaceutical market represented by orphan drugs is predicted to increase from 3.3% in 2010 to a peak of 4.6% in 2016 after which it is expected to level off through 2020, as growth falls into line with that in the wider pharmaceutical market. In sensitivity analysis peak-year orphan drug budget impact ranged between 3% - 6.6%. Although European orphan drug legislation has led to an increase in the number of approved orphan drugs, the growth in cost, as a proportion of total pharmaceutical expenditure, is likely to plateau over the next decade as orphan growth rates converge on those in the broader pharmaceutical market. Given the assumptions and simplifications inherent in such a projection, there is uncertainty around the base case forecast and further research is needed to monitor how trends develop. However, fears that growth in orphan drug expenditure will lead to unsustainable cost escalation do not appear to be justified. Furthermore, based on the results of this budget impact forecast, the European orphan drug legislation is not leading to a disproportionate impact on pharmaceutical expenditure.
Estimating the budget impact of orphan medicines in Europe: 2010 - 2020

PubMed Central

2011-01-01

Background Orphan drugs are a growing issue of importance to European healthcare policy makers. The success of orphan drug legislation in Europe has resulted in an increasing number of licensed medicines for rare diseases, and many more yet unlicensed products have received orphan drug designation. Increasingly the concerns amongst policy makers relate to issues of patient access and affordability, yet few studies have sought to estimate the future budget impact of orphan drugs. The aim of this study was to predict the total cost of orphan medicines in Europe between 2010 and 2020 as a percentage of total European pharmaceutical expenditure. Methods A disease-based epidemiological model was created based upon trends in the designation and approval of new orphan medicines, prevalence estimates for orphan diseases, and historical price and sales data for orphan drugs in Europe (defined as Eurozone + UK). The analysis incorporated two stages: 1) Predicting the number of diseases for which new orphan drugs will be approved over the next decade, based on an analysis of trends from the EU registry of orphan medicines; 2) Estimating the average ex-factory drug cost across an orphan disease life cycle, from the year in which the first orphan medicine is launched to the point where the first medicine loses marketing exclusivity. The two sets of information were combined to quantify the annual cost of orphan drugs from 2010 through 2020. Results The results from the model predicted a steady increase in the cumulative number of diseases for which an orphan drug is approved, averaging just over 5 new diseases per year over the next 10 years. The annual per patient cost of existing orphan drugs was seen to vary between €1,251 and €407,631, with the median cost being €32,242 per year. The share of the total pharmaceutical market represented by orphan drugs is predicted to increase from 3.3% in 2010 to a peak of 4.6% in 2016 after which it is expected to level off through 2020, as growth falls into line with that in the wider pharmaceutical market. In sensitivity analysis peak-year orphan drug budget impact ranged between 3% - 6.6%. Conclusions Although European orphan drug legislation has led to an increase in the number of approved orphan drugs, the growth in cost, as a proportion of total pharmaceutical expenditure, is likely to plateau over the next decade as orphan growth rates converge on those in the broader pharmaceutical market. Given the assumptions and simplifications inherent in such a projection, there is uncertainty around the base case forecast and further research is needed to monitor how trends develop. However, fears that growth in orphan drug expenditure will lead to unsustainable cost escalation do not appear to be justified. Furthermore, based on the results of this budget impact forecast, the European orphan drug legislation is not leading to a disproportionate impact on pharmaceutical expenditure. PMID:21951518
School Bullying and Drug Use Later in Life: A Meta-Analytic Investigation

ERIC Educational Resources Information Center

Ttofi, Maria M.; Farrington, David P.; Lösel, Friedrich; Crago, Rebecca V.; Theodorakis, Nikolaos

2016-01-01

The main aim of this article is to investigate whether there is a significant long-term association between bullying at school and drug use later in life. A meta-analysis is presented based on results from major prospective longitudinal studies with available unadjusted and adjusted effect sizes. Results are based on thorough systematic searches…
An Ounce of Prevention, a Pound of Uncertainty: The Cost-Effectiveness of School-Based Drug Prevention Programs.

ERIC Educational Resources Information Center

Caulkins, Jonathan P.; Rydell, C. Peter; Everingham, Susan S.; Chiesa, James; Bushway, Shawn

This book describes an analysis of the cost-effectiveness of model school-based drug prevention programs at reducing cocaine consumption. It compares prevention's cost-effectiveness with that of several enforcement programs and with that of treating heavy cocaine users. It also assesses the cost of nationwide implementation of model prevention…
Chemoinformatic Analysis of Combinatorial Libraries, Drugs, Natural Products and Molecular Libraries Small Molecule Repository

PubMed Central

Singh, Narender; Guha, Rajarshi; Giulianotti, Marc; Pinilla, Clemencia; Houghten, Richard; Medina-Franco, Jose L.

2009-01-01

A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR and natural products collections. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different to current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries are located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space. PMID:19301827
Inferring protein domains associated with drug side effects based on drug-target interaction network.

PubMed

Iwata, Hiroaki; Mizutani, Sayaka; Tabei, Yasuo; Kotera, Masaaki; Goto, Susumu; Yamanishi, Yoshihiro

2013-01-01

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.
Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery

PubMed Central

2018-01-01

Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively in malaria parasites for target discovery and chemical validation is in vitro evolution and whole genome analysis (IVIEWGA). Here, small molecules from phenotypic screens with demonstrated antiparasitic activity are used in genome-based target discovery methods. In this Review, we discuss the newest, most promising druggable targets discovered or further validated by evolution-based methods, as well as some exceptions. PMID:29451780
Research on Optimization of Pooling System and Its Application in Drug Supply Chain Based on Big Data Analysis

PubMed Central

2017-01-01

Reform of drug procurement is being extensively implemented and expanded in China, especially in today's big data environment. However, the pattern of supply mode innovation lags behind procurement improvement. Problems in financial strain and supply break frequently occur, which affect the stability of drug supply. Drug Pooling System is proposed and applied in a few pilot cities to resolve these problems. From the perspective of supply chain, this study analyzes the process of setting important parameters and sets out the tasks of involved parties in a pooling system according to the issues identified in the pilot run. The approach is based on big data analysis and simulation using system dynamic theory and modeling of Vensim software to optimize system performance. This study proposes a theoretical framework to resolve problems and attempts to provide a valuable reference for future application of pooling systems. PMID:28293258
Injection molding as a one-step process for the direct production of pharmaceutical dosage forms from primary powders.

PubMed

Eggenreich, K; Windhab, S; Schrank, S; Treffer, D; Juster, H; Steinbichler, G; Laske, S; Koscher, G; Roblegg, E; Khinast, J G

2016-05-30

The objective of the present study was to develop a one-step process for the production of tablets directly from primary powder by means of injection molding (IM), to create solid-dispersion based tablets. Fenofibrate was used as the model API, a polyvinyl caprolactame-polyvinyl acetate-polyethylene glycol graft co-polymer served as a matrix system. Formulations were injection-molded into tablets using state-of-the-art IM equipment. The resulting tablets were physico-chemically characterized and the drug release kinetics and mechanism were determined. Comparison tablets were produced, either directly from powder or from pre-processed pellets prepared via hot melt extrusion (HME). The content of the model drug in the formulations was 10% (w/w), 20% (w/w) and 30% (w/w), respectively. After 120min, both powder-based and pellet-based injection-molded tablets exhibited a drug release of 60% independent of the processing route. Content uniformity analysis demonstrated that the model drug was homogeneously distributed. Moreover, analysis of single dose uniformity also revealed geometric drug homogeneity between tablets of one shot. Copyright © 2016 Elsevier B.V. All rights reserved.
Rational drug therapy education in clinical phase carried out by task-based learning

PubMed Central

Bilge, S. Sırrı; Akyüz, Bahar; Ağrı, Arzu Erdal; Özlem, Mıdık

2017-01-01

Objectives: Irrational drug use results in drug interactions, treatment noncompliance, and drug resistance. Rational pharmacotherapy education is being implemented in many faculties of medicine. Our aim is to introduce rational pharmacotherapy education by clinicians and to evaluate task-based rational drug therapy education in the clinical context. Methods: The Kirkpatrick's evaluation model was used for the evaluation of the program. The participants evaluated the program in terms of constituents of the program, utilization, and contribution to learning. Voluntary participants responded to the evaluation forms after the educational program. Data are evaluated using both quantitative and qualitative tools. SPSS (version 21) used for quantitative data for determining mean and standard deviation values. Descriptive qualitative analysis approach is used for the analysis of open-ended questions. Results: It was revealed that the program and its components have been favorable. A total 95.9% of the students consider the education to be beneficial. Simulated patients practice and personal drug choice/problem-based learning sessions were appreciated by the students in particular. 93.9% of the students stated that all students of medicine should undergo this educational program. Among the five presentations contained in the program, “The Principles of Prescribing” received the highest points (9 ± 1.00) from participating students in general evaluation of the educational program. Conclusion: This study was carried out to improve task-based rational drug therapy education. According to feedback from the students concerning content, method, resource, assessment, and program design; some important changes, especially in number of facilitators and indications, are made in rational pharmacotherapy education in clinical task-based learning program. PMID:28458432
Label-free integrative pharmacology on-target of drugs at the β2-adrenergic receptor

NASA Astrophysics Data System (ADS)

Ferrie, Ann M.; Sun, Haiyan; Fang, Ye

2011-07-01

We describe a label-free integrative pharmacology on-target (iPOT) method to assess the pharmacology of drugs at the β2-adrenergic receptor. This method combines dynamic mass redistribution (DMR) assays using an array of probe molecule-hijacked cells with similarity analysis. The whole cell DMR assays track cell system-based, ligand-directed, and kinetics-dependent biased activities of the drugs, and translates their on-target pharmacology into numerical descriptors which are subject to similarity analysis. We demonstrate that the approach establishes an effective link between the label-free pharmacology and in vivo therapeutic indications of drugs.
A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations

PubMed Central

Thiel, Christoph; Cordes, Henrik; Fabbri, Lorenzo; Aschmann, Hélène Eloise; Baier, Vanessa; Atkinson, Francis; Blank, Lars Mathias; Kuepfer, Lars

2017-01-01

Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application. PMID:28151932
Lessons from hot spot analysis for fragment-based drug discovery

PubMed Central

Hall, David R.; Vajda, Sandor

2015-01-01

Analysis of binding energy hot spots at protein surfaces can provide crucial insights into the prospects for successful application of fragment-based drug discovery (FBDD), and whether a fragment hit can be advanced into a high affinity, druglike ligand. The key factor is the strength of the top ranking hot spot, and how well a given fragment complements it. We show that published data are sufficient to provide a sophisticated and quantitative understanding of how hot spots derive from protein three-dimensional structure, and how their strength, number and spatial arrangement govern the potential for a surface site to bind to fragment-sized and larger ligands. This improved understanding provides important guidance for the effective application of FBDD in drug discovery. PMID:26538314
Mathematical modeling of coupled drug and drug-encapsulated nanoparticle transport in patient-specific coronary artery walls

NASA Astrophysics Data System (ADS)

Hossain, Shaolie S.; Hossainy, Syed F. A.; Bazilevs, Yuri; Calo, Victor M.; Hughes, Thomas J. R.

2012-02-01

The majority of heart attacks occur when there is a sudden rupture of atherosclerotic plaque, exposing prothrombotic emboli to coronary blood flow, forming clots that can cause blockages of the arterial lumen. Diseased arteries can be treated with drugs delivered locally to vulnerable plaques. The objective of this work was to develop a computational tool-set to support the design and analysis of a catheter-based nanoparticulate drug delivery system to treat vulnerable plaques and diffuse atherosclerosis. A three-dimensional mathematical model of coupled mass transport of drug and drug-encapsulated nanoparticles was developed and solved numerically utilizing isogeometric finite element analysis. Simulations were run on a patient-specific multilayered coronary artery wall segment with a vulnerable plaque and the effect of artery and plaque inhomogeneity was analyzed. The method captured trends observed in local drug delivery and demonstrated potential for optimizing drug design parameters, including delivery location, nanoparticle surface properties, and drug release rate.

Identifying and Preventing Health Problems among Young Drug-Misusing Offenders

ERIC Educational Resources Information Center

Bennett, Trevor; Holloway, Katy

2008-01-01

Purpose: The purpose of this paper is to identify the health problems and treatment needs of drug-misusing offenders and to draw out the implications of the findings for health education and prevention. Design/methodology/approach: This analysis is based on data collected as part of the New English and Welsh Arrestee Drug Abuse Monitoring…
Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients.

PubMed

Buatois, Simon; Retout, Sylvie; Frey, Nicolas; Ueckert, Sebastian

2017-10-01

This manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power. An item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects. The IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power. IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.
New era in drug interaction evaluation: US Food and Drug Administration update on CYP enzymes, transporters, and the guidance process.

PubMed

Huang, Shiew-Mei; Strong, John M; Zhang, Lei; Reynolds, Kellie S; Nallani, Srikanth; Temple, Robert; Abraham, Sophia; Habet, Sayed Al; Baweja, Raman K; Burckart, Gilbert J; Chung, Sang; Colangelo, Philip; Frucht, David; Green, Martin D; Hepp, Paul; Karnaukhova, Elena; Ko, Hon-Sum; Lee, Jang-Ik; Marroum, Patrick J; Norden, Janet M; Qiu, Wei; Rahman, Atiqur; Sobel, Solomon; Stifano, Toni; Thummel, Kenneth; Wei, Xiao-Xiong; Yasuda, Sally; Zheng, Jenny H; Zhao, Hong; Lesko, Lawrence J

2008-06-01

Predicting clinically significant drug interactions during drug development is a challenge for the pharmaceutical industry and regulatory agencies. Since the publication of the US Food and Drug Administration's (FDA's) first in vitro and in vivo drug interaction guidance documents in 1997 and 1999, researchers and clinicians have gained a better understanding of drug interactions. This knowledge has enabled the FDA and the industry to progress and begin to overcome these challenges. The FDA has continued its efforts to evaluate methodologies to study drug interactions and communicate recommendations regarding the conduct of drug interaction studies, particularly for CYP-based and transporter-based drug interactions, to the pharmaceutical industry. A drug interaction Web site was established to document the FDA's current understanding of drug interactions (http://www.fda.gov/cder/drug/drugInteractions/default.htm). This report provides an overview of the evolution of the drug interaction guidances, includes a synopsis of the steps taken by the FDA to revise the original drug interaction guidance documents, and summarizes and highlights updated sections in the current guidance document, Drug Interaction Studies-Study Design, Data Analysis, and Implications for Dosing and Labeling.
Ad hoc versus standardized admixtures for continuous infusion drugs in neonatal intensive care: cognitive task analysis of safety at the bedside.

PubMed

Brannon, Timothy S

2006-01-01

Continuous infusion intravenous (IV) drugs in neonatal intensive care are usually prepared based on patient weight so that the dose is readable as a simple multiple of the infusion pump rate. New safety guidelines propose that hospitals switch to using standardized admixtures of these drugs to prevent calculation errors during ad hoc preparation. Extended hierarchical task analysis suggests that switching to standardized admixtures may lead to more errors in programming the pump at the bedside.
Ad Hoc versus Standardized Admixtures for Continuous Infusion Drugs in Neonatal Intensive Care: Cognitive Task Analysis of Safety at the Bedside

PubMed Central

Brannon, Timothy S.

2006-01-01

Continuous infusion intravenous (IV) drugs in neonatal intensive care are usually prepared based on patient weight so that the dose is readable as a simple multiple of the infusion pump rate. New safety guidelines propose that hospitals switch to using standardized admixtures of these drugs to prevent calculation errors during ad hoc preparation. Extended hierarchical task analysis suggests that switching to standardized admixtures may lead to more errors in programming the pump at the bedside. PMID:17238482
[The present study situation and application prospect of nail analysis for abused drugs].

PubMed

Chen, Hang; Xiang, Ping; Shen, Min

2010-10-01

In forensic toxicology analysis, various types of biological samples have their own special characteristics and scope of applications. In this article, the physiological structure of nails, methods for collecting and pre-processing samples, and for analyzing some poisons and drugs in the nails are reviewed with details. This paper introduces the influence factors of drug abuse of the nails. The prospects of its further applications are concluded based on the research results. Nails, as an unconventional bio-sample without general application, show great potential and advantages in forensic toxicology.
Nucleic acid binding drugs. Part XIII. Molecular motion in a drug-nucleic acid model system: thermal motion analysis of a proflavine-dinucleoside crystal structure.

PubMed Central

Aggarwal, A K; Neidle, S

1985-01-01

The high-resolution crystal structure of the intercalation complex between proflavine and cytidylyl-3',5'-guanosine (CpG) has been studied by thermalmotion analysis. This has provided information on the translational and librational motions of individual groups in the complex. Many of these motions are similar to, though of larger magnitude than in uncomplexed dinucleosides. Pronounced librational effects were observed along the base pairs and in the plane of the drug chromophore. PMID:4034394
Buying drugs on a Darknet market: A better deal? Studying the online illicit drug market through the analysis of digital, physical and chemical data.

PubMed

Rhumorbarbe, Damien; Staehli, Ludovic; Broséus, Julian; Rossy, Quentin; Esseiva, Pierre

2016-10-01

Darknet markets, also known as cryptomarkets, are websites located on the Darknet and designed to allow the trafficking of illicit products, mainly drugs. This study aims at presenting the added value of combining digital, chemical and physical information to reconstruct sellers' activities. In particular, this research focuses on Evolution, one of the most popular cryptomarkets active from January 2014 to March 2015. Evolution source code files were analysed using Python scripts based on regular expressions to extract information about listings (i.e., sales proposals) and sellers. The results revealed more than 48,000 listings and around 2700 vendors claiming to send illicit drug products from 70 countries. The most frequent categories of illicit drugs offered by vendors were cannabis-related products (around 25%) followed by ecstasy (MDA, MDMA) and stimulants (cocaine, speed). The cryptomarket was then especially studied from a Swiss point of view. Illicit drugs were purchased from three sellers located in Switzerland. The purchases were carried out to confront digital information (e.g., the type of drug, the purity, the shipping country and the concealment methods mentioned on listings) with the physical analysis of the shipment packaging and the chemical analysis of the received product (purity, cutting agents, chemical profile based on minor and major alkaloids, chemical class). The results show that digital information, such as concealment methods and shipping country, seems accurate. But the illicit drugs purity is found to be different from the information indicated on their respective listings. Moreover, chemical profiling highlighted links between cocaine sold online and specimens seized in Western Switzerland. This study highlights that (1) the forensic analysis of the received products allows the evaluation of the accuracy of digital data collected on the website, and (2) the information from digital and physical/chemical traces are complementary to evaluate the practices of the online selling of illicit drugs on cryptomarkets. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Cost Effectiveness of Monoclonal Antibody Therapy for Rare Diseases: A Systematic Review.

PubMed

Park, Taehwan; Griggs, Scott K; Suh, Dong-Churl

2015-08-01

Monoclonal antibody (mAb)-based orphan drugs have led to advances in the treatment of diseases by selectively targeting molecule functions. However, their high treatment costs impose a substantial cost burden on patients and society. The study aimed to systematically review cost-effectiveness evidence of mAb orphan drugs. Ovid MEDLINE(®), EMBASE(®), and PsycINFO(®) were searched in June 2014 and articles were selected if they conducted economic evaluations of the mAb orphan drugs that had received marketing approval in the USA. The quality of the selected studies was assessed using the Quality of Health Economic Studies (QHES) instrument. We reviewed 16 articles that included 24 economic evaluations of nine mAb orphan drugs. Six of these nine drugs were included in cost-utility analysis studies, whereas three drugs were included in cost-effectiveness analysis studies. Previous cost-utility analysis studies revealed that four mAb orphan drugs (cetuximab, ipilimumab, rituximab, and trastuzumab) were found to be cost effective; one drug (bevacizumab) was not cost effective; and one drug (infliximab) was not consistent across the studies. Prior cost-effectiveness analysis studies which included three mAb orphan drugs (adalimumab, alemtuzumab, and basiliximab) showed that the incremental cost per effectiveness gained for these drugs ranged from $US4669 to $Can52,536 Canadian dollars. The quality of the included studies was good or fair with the exception of one study. Some mAb orphan drugs were reported as cost effective under the current decision-making processes. Use of these expensive drugs, however, can raise an equity issue which concerns fairness in access to treatment. The issue of equal access to drugs needs to be considered alongside other societal values in making the final health policy decisions.
Investigation into adamantane-based M2 inhibitors with FB-QSAR.

PubMed

Wei, Hang; Wang, Cheng-Hua; Du, Qi-Shi; Meng, Jianzong; Chou, Kuo-Chen

2009-07-01

Because of their high resistance rate to the existing drugs, influenza A viruses have become a threat to human beings. It is known that the replication of influenza A viruses needs a pH-gated proton channel, the so-called M2 channel. Therefore, to develop effective drugs against influenza A, the most logic strategy is to inhibit the M2 channel. Recently, the atomic structure of the M2 channel was determined by NMR spectroscopy (Schnell, J.R. and Chou, J.J., Nature, 2008, 451, 591-595). The high-resolution NMR structure has provided a solid basis for structure-based drug design approaches. In this study, a benchmark dataset has been constructed that contains 34 newly-developed adamantane-based M2 inhibitors and covers considerable structural diversities and wide range of bioactivities. Based on these compounds, an in-depth analysis was performed with the newly developed fragment-based quantitative structure-activity relationship (FB-QSAR) algorithm. The results thus obtained provide useful insights for dealing with the drug-resistant problem and designing effective adamantane-based antiflu drugs.
A prediction model-based algorithm for computer-assisted database screening of adverse drug reactions in the Netherlands.

PubMed

Scholl, Joep H G; van Hunsel, Florence P A M; Hak, Eelko; van Puijenbroek, Eugène P

2018-02-01

The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model-based approach. A logistic regression-based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug-ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations. A total of 25 026 unique drug-ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734-0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%). A prediction model-based approach can be a useful tool to create priority-based listings for signal detection in databases consisting of spontaneous ADRs. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.
Taro corms mucilage/HPMC based transdermal patch: an efficient device for delivery of diltiazem hydrochloride.

PubMed

Sarkar, Gunjan; Saha, Nayan Ranjan; Roy, Indranil; Bhattacharyya, Amartya; Bose, Madhura; Mishra, Roshnara; Rana, Dipak; Bhattacharjee, Debashis; Chattopadhyay, Dipankar

2014-05-01

The aim of this work is to examine the effectiveness of mucilage/hydroxypropylmethylcellulose (HPMC) based transdermal patch (matrix type) as a drug delivery device. We have successfully extracted mucilage from Colocasia esculenta (Taro) corms and prepared diltiazem hydrochloride incorporated mucilage/HPMC based transdermal patches using various wt% of mucilage by the solvent evaporation technique. Characterization of both mucilage and transdermal patches has been done by several techniques such as Molisch's test, organoleptic evaluation of mucilage, mechanical, morphological and thermal analysis of transdermal patches. Skin irritation test is studied on hairless Albino rat skin showing that transdermal patches are apparently free of potentially hazardous skin irritation. Fourier transform infrared analysis shows that there is no interaction between drug, mucilage and HPMC while scanning electron microscopy shows the surface morphology of transdermal patches. In vitro drug release time of mucilage-HPMC based transdermal patches is prolonged with increasing mucilage concentration in the formulation. Copyright © 2014 Elsevier B.V. All rights reserved.
Examination of the Regulatory Frameworks Applicable to Biologic Drugs (Including Stem Cells and Their Progeny) in Europe, the U.S., and Australia: Part I—A Method of Manual Documentary Analysis

PubMed Central

Savic, Snezana; Siegel, Evan; Atkinson, Kerry; Tasic, Ljiljana

2012-01-01

Recent development of a wide range of regulatory standards applicable to production and use of tissues, cells, and other biologics (or biologicals), as advanced therapies, indicates considerable interest in the regulation of these products. The objective of this study was to analyze and compare high-tier documents within the Australian, European, and U.S. biologic drug regulatory environments using qualitative methodology. Cohort 1 of the selected 18 high-tier regulatory documents from the European Medicines Agency (EMA), the U.S. Food and Drug Administration (FDA), and the Therapeutic Goods Administration (TGA) regulatory frameworks were subject to a manual documentary analysis. These documents were consistent with the legal requirements for manufacturing and use of biologic drugs in humans and fall into six different categories. Manual analysis included a terminology search. The occurrence, frequency, and interchangeable use of different terms and phrases were recorded in the manual documentary analysis. Despite obvious differences, manual documentary analysis revealed certain consistency in use of terminology across analyzed frameworks. Phrase search frequencies have shown less uniformity than the search of terms. Overall, the EMA framework's documents referred to “medicinal products” and “marketing authorization(s),” the FDA documents discussed “drug(s)” or “biologic(s),” and the TGA documents referred to “biological(s).” Although high-tier documents often use different terminology they share concepts and themes. Documents originating from the same source have more conjunction in their terminology although they belong to different frameworks (i.e., Good Clinical Practice requirements based on the Declaration of Helsinki, 1964). Automated (software-based) documentary analysis should be obtained for the conceptual and relational analysis. PMID:23283551
Use of illicit stimulant drugs in Finland: a wastewater study in ten major cities.

PubMed

Kankaanpää, Aino; Ariniemi, Kari; Heinonen, Mari; Kuoppasalmi, Kimmo; Gunnar, Teemu

2014-07-15

Estimations of drug use at the national level are generally based on various sources of information, such as drug seizures, socio-scientific studies, toxicological data and hospital records. Nevertheless, all of these approaches have limitations that cannot be overcome, even if conclusions are drawn from combined data retrieved from different sources. Drug epidemiology through wastewater analysis has the potential to provide unique perspectives, internationally comparable data, and up-to-date information on the use of both traditional illicit drugs and new psychoactive substances (NPSs). In Finland, no large-scale studies on regional illicit drug consumption, based on a wastewater approach, have been reported. In this study, 24-h influent composite samples were collected during two 1-week study periods from ten different wastewater treatment plants in May and November-December 2012. The cities included in the study represent the geographical areas throughout Finland and cover 40% of the Finnish population. The samples were analyzed with an in-house validated, ultra high-performance liquid-chromatography mass spectrometric (UHPLC-MS/MS) method for various common illicit drugs and some NPS type stimulant drugs. The results were also compared with available statistics, information on drug seizures and laboratory-confirmed toxicological data, as well as other studies available based on wastewater analysis. The data show that illicit stimulant drug use is more common in the larger cities of Southern Finland. Amphetamine was the most commonly used drug in all 10 cities during both collection periods (excluding the collection period in May in Lappeenranta). Cocaine consumption remains very low in Finland in comparison to other European countries; it was concentrated in the biggest cities in Southern Finland. This study shows interesting temporal and spatial differences in drug use in Finland, as well as the possibilities of using wastewater analytics to reveal local hotspots of NPS consumption. Copyright © 2013 Elsevier B.V. All rights reserved.
California drug courts: outcomes, costs and promising practices: an overview of Phase II in a statewide study.

PubMed

Carey, Shannon M; Finigan, Michael; Crumpton, Dave; Waller, Mark

2006-11-01

The rapid expansion of drug courts in California and the state's uncertain fiscal climate highlighted the need for definitive cost information on drug court programs. This study focused on creating a research design that can be utilized for statewide and national cost-assessment of drug courts by conducting in-depth case studies of the costs and benefits in nine adult drug courts in California. A Transactional Institutional Costs Analysis (TICA) approach was used, allowing researchers to calculate costs based on every individual's transactions within the drug court or the traditional criminal justice system. This methodology also allows the calculation of costs and benefits by agency (e.g., Public Defender's office, court, District Attorney). Results in the nine sites showed that the majority of agencies save money in processing an offender though drug court. Overall, for these nine study sites, participation in drug court saved the state over 9 million dollars in criminal justice and treatment costs due to lower recidivism in drug court participants. Based on the lessons learned in Phases I and II, Phase III of this study focuses on the creation of a web-based drug court cost self-evaluation tool (DC-CSET) that drug courts can use to determine their own costs and benefits.
Pharmacoeconomics and macular degeneration.

PubMed

Brown, Gary C; Brown, Melissa M; Brown, Heidi; Godshalk, Ashlee N

2007-05-01

To describe pharmacoeconomics and its relationship to drug interventions. Pharmacoeconomics is the branch of economics which applies cost-minimization, cost-benefit, cost-effectiveness and cost-utility analyses to compare the economics of different pharmaceutical products or to compare drug therapy to other treatments. Among the four instruments, cost-utility analysis is the most sophisticated, relevant and clinically applicable as it measures the value conferred by drugs for the monies expended. Value-based medicine incorporates cost-utility principles but with strict standardization of all input and output parameters to allow the comparability of analyses, unlike the current situation in the healthcare literature. Pharmacoeconomics is assuming an increasingly important role with regard to whether drugs are listed on the drug formulary of a country or province. It has been estimated that the application of standardized, value-based medicine drug analyses can save over 35% from a public healthcare insurer drug formulary while maintaining or improving patient care.
Drug pricing and reimbursement decision making systems in Mongolia.

PubMed

Dorj, Gereltuya; Sunderland, Bruce; Sanjjav, Tsetsegmaa; Dorj, Gantuya; Gendenragchaa, Byambatsogt

2017-01-01

It is essential to allocate available resources equitably in order to ensure accessibility and affordability of essential medicines, especially in less fortunate nations with limited health funding. Currently, transparent and evidence based research is required to evaluate decision making regarding drug registration, drug pricing and reimbursement processes in Mongolia. To assess the drug reimbursement system and discuss challenges faced by policy-makers and stakeholders. The study has examined Mongolian administrative documents and directives for stakeholders and analysed published statistics. Experts and decision-makers were interviewed about the drug pricing and reimbursement processes in Mongolia. Decisions regarding Mongolian drug registration were based on commonly used criteria of quality, safety, efficacy plus some economic considerations. A total of 11.32 billion Mongolian National Tugrugs (MNT) [5.6 million United States Dollars (USD)] or 12.1% of total health expenditure was spent on patient reimbursement of essential drugs. The highest reimbursed drugs with respect to cost in 2014 were the cardiovascular drug group. Health insurance is compulsory for all citizens; in addition all insured patients have access to reimbursed drugs. However, the decision making process, in particular the level of reimbursement was limited by various barriers, including lack of evidence based data regarding efficacy and comparative cost-effectiveness analysis of drugs and decisions regarding reimbursement. Drug registration, pricing and reimbursement process in Mongolia show an increasing trend of drug registration and reimbursement rates, along with lack of transparency. Limited available data indicate that more evidence-based research studies are required in Mongolia to evaluate and improve the effectiveness of drug pricing and reimbursement policies.
Preventing Drug Abuse Among Adolescent Girls: Outcome Data from an Internet-Based Intervention

PubMed Central

Schinke, Steven P.; Di Noia, Jennifer

2009-01-01

This study developed and tested an Internet-based gender-specific drug abuse prevention program for adolescent girls. A sample of seventh, eighth, and ninth grade girls (N = 236) from 42 states and 4 Canadian provinces were randomly assigned to an intervention or control group. All girls completed an online pretest battery. Following pretest, intervention girls interacted with a 12-session, Internet-based gender-specific drug prevention program. Girls in both groups completed the measurement battery at posttest and 6-month follow-up. Analysis of posttest scores revealed no differences between groups for 30-day reports of alcohol, marijuana, poly drug use, or total substance use (alcohol and drugs). At 6-month follow-up, between-group effects were found on measures of 30-day alcohol use, marijuana use, poly drug use, and total substance use. Relative to girls in the control group, girls exposed to the Internet-based intervention reported lower rates of use for these substances. Moreover, girls receiving the intervention achieved gains over girls in the control group on normative beliefs and self-efficacy at posttest and 6-month follow-up, respectively. PMID:19728091
Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds.

PubMed

Baurin, N; Baker, R; Richardson, C; Chen, I; Foloppe, N; Potter, A; Jordan, A; Roughley, S; Parratt, M; Greaney, P; Morley, D; Hubbard, R E

2004-01-01

We have implemented five drug-like filters, based on 1D and 2D molecular descriptors, and applied them to characterize the drug-like properties of commercially available chemical compounds. In addition to previously published filters (Lipinski and Veber), we implemented a filter for medicinal chemistry tractability based on lists of chemical features drawn up by a panel of medicinal chemists. A filter based on the modeling of aqueous solubility (>1 microM) was derived in-house, as well as another based on the modeling of Caco-2 passive membrane permeability (>10 nm/s). A library of 2.7 million compounds was collated from the 23 compound suppliers and analyzed with these filters, highlighting a tendency toward highly lipophilic compounds. The library contains 1.6 M unique structures, of which 37% (607,223) passed all five drug-like filters. None of the 23 suppliers provides all the members of the drug-like subset, emphasizing the benefit of considering compounds from various compound suppliers as a source of diversity for drug discovery.
Towards more realistic in vitro release measurement techniques for biodegradable microparticles.

PubMed

Klose, D; Azaroual, N; Siepmann, F; Vermeersch, G; Siepmann, J

2009-03-01

To better understand the importance of the environmental conditions for drug release from biodegradable microparticles allowing for the development of more appropriate in vitro release measurement techniques. Propranolol HCl diffusion in various agarose gels was characterized by NMR and UV analysis. Fick's law was used to theoretically predict the mass transport kinetics. Drug release from PLGA-based microparticles in such agarose gels was compared to that measured in agitated bulk fluids ("standard" method). NMR analysis revealed that the drug diffusivity was almost independent of the hydrogel concentration, despite of the significant differences in the systems' mechanical properties. This is due to the small size of the drug molecules/ions with respect to the hydrogel mesh size. Interestingly, the theoretically predicted drug concentration-distance-profiles could be confirmed by independent experiments. Most important from a practical point of view, significant differences in the release rates from the same batch of PLGA-based microparticles into a well agitated bulk fluid versus a semi-solid agarose gel were observed. Great care must be taken when defining the in vitro conditions for drug release measurements from biodegradable microparticles. The obtained new insight can help facilitating the development of more appropriate in vitro release testing procedures.

Harm reduction programmes in the Asia--Pacific Region.

PubMed

Reid, Gary; Devaney, Madonna L; Baldwin, Simon

2008-01-01

This paper reports on the public health intervention of harm reduction to address drug use issues in the Asia-Pacific region. It is based on the report 'Situational analysis of illicit drug issues and responses in Asia and the Pacific', commissioned by the Australian National Council on Drugs Asia Pacific Drug Issues Committee. A comprehensive desk-based review based on published and unpublished literature and key informant data. Drug use in the Asia--Pacific region is widespread, resulting in serious adverse health consequences. Needle and syringe programmes are found in some parts of Asia, but not in the six Pacific Island countries reviewed. Outreach and peer education programmes are implemented, but overall appear minor in size and scope. Substitution therapy programmes appear to be entering a new era of acceptance in some parts of Asia. Primary health care specifically for drug users overall is limited. Harm reduction programmes in the Asia--Pacific region are either small in scale or do not exist. Most programmes lack the technical capacity, human resources and a limited scope of operations to respond effectively to the needs of drug users. Governments in this region should be encouraged to endorse evidence-based harm reduction programmes.
Effect of amphiphilic graft co-polymer-carrier on physical stability of bosentan nanocomposite: Assessment of solubility, dissolution and bioavailability.

PubMed

Kendre, Prakash N; Chaudhari, Pravin D

2018-05-01

Bosentan is a dual endothelin receptor antagonist used in the treatment of pulmonary arterial hypertension (PAH). But the solubility and bioavailability of this drug are poor, which has restricted the design and development of dosage forms for efficient and successful therapy. The present study was carried out to develop nanocomposites using an amphiphilic graft co-polymer (Soluplus®) as a carrier to enhance the solubility and bioavailability of bosentan. The graft co-polymer-based nanocomposite formulation was prepared using the single-emulsion technique. The nanocomposite was characterised in terms of particle size analysis, solubility, percentage entrapment efficiency, drug-loading capacity, surface morphology, drug content, in vitro dissolution, stability and bioavailability. FT-IR study revealed that there was no interaction between the drug and Soluplus®. DSC analysis of the nanocomposite formulation confirmed that the bosentan was completely encapsulated within a Soluplus®. XRD analysis showed that the drug was converted to an amorphous form irreversibly. SEM images showed that the particles were of size 96-129μm and had slightly smooth to rough textured surface. TEM analysis indicated that the diameters of the prepared bosentan nanocomposite after dispersion in distilled water were 13.69-96.78nm. Statistically significant increases in the solubility, dissolution and bioavailability of the drug were observed. It was confirmed that the use of a graft co-polymer carrier-based nanocomposite formulation is a good approach for efficient delivery of bosentan, the solubility and bioavailability being increased manifold. Copyright © 2017 Elsevier B.V. All rights reserved.
From conventional towards new - natural surfactants in drug delivery systems design: current status and perspectives.

PubMed

Savić, Snezana; Tamburić, Slobodanka; Savić, Miroslav M

2010-03-01

Surfactants play an important role in the development of both conventional and advanced (colloidal) drug delivery systems. There are several commercial surfactants, but a proportionally small group of them is approved as pharmaceutical excipients, recognized in various pharmacopoeias and therefore widely accepted by the pharmaceutical industry. The review covers some of the main categories of natural, sugar-based surfactants (alkyl polyglucosides and sugar esters) as prospective pharmaceutical excipients. It provides analysis of the physicochemical characteristics of sugar-based surfactants and their possible roles in the design of conventional or advanced drug delivery systems for different routes of administration. Summary and analysis of recent data on functionality, applied concentrations and formulation improvements produced by alkyl polyglucosides and sugar esters in different conventional and advanced delivery systems could be of interest to researchers dealing with drug formulation. Recent FDA certification of an alkyl polyglucoside surfactant for topical formulation presents a significant step in the process of recognition of this relatively new group of surfactants. This could trigger further research into the potential benefits of naturally derived materials in both conventional and new drug delivery systems.
Host-guest interaction of ZnBDC-MOF + doxorubicin: A theoretical and experimental study

NASA Astrophysics Data System (ADS)

Vasconcelos, Iane B.; Wanderley, Kaline A.; Rodrigues, Nailton M.; da Costa, Nivan B.; Freire, Ricardo O.; Junior, Severino A.

2017-03-01

The incorporation of drugs in biodegradable polymeric particles is one of many processes that controllably and significantly increase their release and action. In this paper, we describe the synthesis and physicochemical characterization of ZnBDC-MOF + doxorubicin (DOXO@ZnBDC) and the system's effectiveness in the sustained release of the drug doxorubicin. An experimental and theoretical study is presented of the interaction between the [Zn(BDC)(H2O)2]n MOF and the drug doxorubicin (DOXO). The synthesis was characterized by elemental analysis and X-ray powder diffraction (XRPD). The experimental incorporation was accomplished and analyzed by Fourier transform infrared spectroscopy (FTIR), XRPD and UV-Vis (ultraviolet-visible) spectrophotometry. Based on an analysis of the doxorubicin release profile, our results suggest that the drug delivery system showed slower release than other systems under development. Studies of cytotoxicity by the MTT method showed good results for the system developed with antineoplastic doxorubicin, and together with the other results of this study, suggest the successful development of a MOF-based drug delivery system.
Silk Electrogel Based Gastroretentive Drug Delivery System

NASA Astrophysics Data System (ADS)

Wang, Qianrui

Gastric cancer has become a global pandemic and there is imperative to develop efficient therapies. Oral dosing strategy is the preferred route to deliver drugs for treating the disease. Recent studies suggested silk electro hydrogel, which is pH sensitive and reversible, has potential as a vehicle to deliver the drug in the stomach environment. The aim of this study is to establish in vitro electrogelation e-gel based silk gel as a gastroretentive drug delivery system. We successfully extended the duration of silk e-gel in artificial gastric juice by mixing silk solution with glycerol at different ratios before the electrogelation. Structural analysis indicated the extended duration was due to the change of beta sheet content. The glycerol mixed silk e-gel had good doxorubicin loading capability and could release doxorubicin in a sustained-release profile. Doxorubicin loaded silk e-gels were applied to human gastric cancer cells. Significant cell viability decrease was observed. We believe that with further characterization as well as functional analysis, the silk e-gel system has the potential to become an effective vehicle for gastric drug delivery applications.
Inferring protein domains associated with drug side effects based on drug-target interaction network

PubMed Central

2013-01-01

Background Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. PMID:24565527
Nanostructured surfaces for analysis of anticancer drug and cell diagnosis based on electrochemical and SERS tools.

PubMed

El-Said, Waleed A; Yoon, Jinho; Choi, Jeong-Woo

2018-01-01

Discovering new anticancer drugs and screening their efficacy requires a huge amount of resources and time-consuming processes. The development of fast, sensitive, and nondestructive methods for the in vitro and in vivo detection of anticancer drugs' effects and action mechanisms have been done to reduce the time and resources required to discover new anticancer drugs. For the in vitro and in vivo detection of the efficiency, distribution, and action mechanism of anticancer drugs, the applications of electrochemical techniques such as electrochemical cell chips and optical techniques such as surface-enhanced Raman spectroscopy (SERS) have been developed based on the nanostructured surface. Research focused on electrochemical cell chips and the SERS technique have been reviewed here; electrochemical cell chips based on nanostructured surfaces have been developed for the in vitro detection of cell viability and the evaluation of the effects of anticancer drugs, which showed the high capability to evaluate the cytotoxic effects of several chemicals at low concentrations. SERS technique based on the nanostructured surface have been used as label-free, simple, and nondestructive techniques for the in vitro and in vivo monitoring of the distribution, mechanism, and metabolism of different anticancer drugs at the cellular level. The use of electrochemical cell chips and the SERS technique based on the nanostructured surface should be good tools to detect the effects and action mechanisms of anticancer drugs.
Nanostructured surfaces for analysis of anticancer drug and cell diagnosis based on electrochemical and SERS tools

NASA Astrophysics Data System (ADS)

El-Said, Waleed A.; Yoon, Jinho; Choi, Jeong-Woo

2018-04-01

Discovering new anticancer drugs and screening their efficacy requires a huge amount of resources and time-consuming processes. The development of fast, sensitive, and nondestructive methods for the in vitro and in vivo detection of anticancer drugs' effects and action mechanisms have been done to reduce the time and resources required to discover new anticancer drugs. For the in vitro and in vivo detection of the efficiency, distribution, and action mechanism of anticancer drugs, the applications of electrochemical techniques such as electrochemical cell chips and optical techniques such as surface-enhanced Raman spectroscopy (SERS) have been developed based on the nanostructured surface. Research focused on electrochemical cell chips and the SERS technique have been reviewed here; electrochemical cell chips based on nanostructured surfaces have been developed for the in vitro detection of cell viability and the evaluation of the effects of anticancer drugs, which showed the high capability to evaluate the cytotoxic effects of several chemicals at low concentrations. SERS technique based on the nanostructured surface have been used as label-free, simple, and nondestructive techniques for the in vitro and in vivo monitoring of the distribution, mechanism, and metabolism of different anticancer drugs at the cellular level. The use of electrochemical cell chips and the SERS technique based on the nanostructured surface should be good tools to detect the effects and action mechanisms of anticancer drugs.
[Drug expenditures of pensioners in 1997-2000].

PubMed

Swistak, Piotr; Błońska-Fajfrowska, Barbara

2003-01-01

The general purpose of the study, carried out in the group of pensioners was to determine the relation between drug prices, household income and amounts of money spent on drugs in the years 1997-2000. The study was based on representative data gathered from annual household budgets review by Polish Statistical Office and data from pharmaceutical market published in 'Vitamina C++' magazine. The used method combined descriptive, comparative, table-descriptive analysis with graphical analysis. During studied period the real value of expenses on drugs in pensioners' households rose by 39.3% and available income decreased by 5.8%. Increased expenses on drugs caused the rise of the proportion of on spending on drugs in total household expenditure. It rose from 3.9% in 1997 to 5.2% in 2000. Throughout this time period the drug prices increased in real terms: the highest growth (approx. 49%) was noticed in patients' co-payment to reimbursed drugs. Despite rise in spending on drugs, due to the increase in drug retail prices and increasing patients co-payment, pensioners in comparison with 1997, could buy only approx. 93% units of reimbursed drugs in 2000. The possibility of buying drugs within OTC group increased by 18%.
Drug-Induced Dental Caries: A Disproportionality Analysis Using Data from VigiBase.

PubMed

de Campaigno, Emilie Patras; Kebir, Inès; Montastruc, Jean-Louis; Rueter, Manuela; Maret, Delphine; Lapeyre-Mestre, Maryse; Sallerin, Brigitte; Despas, Fabien

2017-12-01

Dental caries is defined as a pathological breakdown of the tooth. It is an infectious phenomenon involving a multifactorial aetiology. The impact of drugs on cariogenic risk has been poorly investigated. In this study, we identified drugs suspected to induce dental caries as adverse drug reactions (ADRs) and then studied a possible pathogenic mechanism for each drug that had a statistically significant disproportionality. We extracted individual case safety reports of dental caries associated with drugs from VigiBase ® (the World Health Organization global individual case safety report database). We calculated disproportionality for each drug with a reporting odds ratio (ROR) and 99% confidence interval. We analysed the pharmacodynamics of each drug that had a statistically significant disproportionality. In VigiBase ® , 5229 safety reports for dental caries concerning 733 drugs were identified. Among these drugs, 88 had a significant ROR, and for 65 of them (73.9%), no information about dental caries was found in the summaries of the product characteristics, the Micromedex ® DRUGDEX, or the Martindale databases. Regarding the pharmacological classes of drugs involved in dental caries, we identified bisphosphonates, atropinic drugs, antidepressants, corticoids, immunomodulating drugs, antipsychotics, antiepileptics, opioids and β 2 -adrenoreceptor agonist drugs. Regarding possible pathogenic mechanisms for these drugs, we identified changes in salivary flow/composition for 54 drugs (61.4%), bone metabolism changes for 31 drugs (35.2%), hyperglycaemia for 32 drugs (36.4%) and/or immunosuppression for 23 drugs (26.1%). For nine drugs (10.2%), the mechanism was unclear. We identified 88 drugs with a significant positive disproportionality for dental caries. Special attention has to be paid to bisphosphonates, atropinic drugs, immunosuppressants and drugs causing hyperglycaemia.
Porous silicon for drug delivery applications and theranostics: recent advances, critical review and perspectives.

PubMed

Kumeria, Tushar; McInnes, Steven J P; Maher, Shaheer; Santos, Abel

2017-12-01

Porous silicon (pSi) engineered by electrochemical etching has been used as a drug delivery vehicle to address the intrinsic limitations of traditional therapeutics. Biodegradability, biocompatibility, and optoelectronic properties make pSi a unique candidate for developing biomaterials for theranostics and photodynamic therapies. This review presents an updated overview about the recent therapeutic systems based on pSi, with a critical analysis on the problems and opportunities that this technology faces as well as highlighting pSi's growing potential. Areas covered: Recent progress in pSi-based research includes drug delivery systems, including biocompatibility studies, drug delivery, theranostics, and clinical trials with the most relevant examples of pSi-based systems presented here. A critical analysis about the technical advantages and disadvantages of these systems is provided along with an assessment on the challenges that this technology faces, including clinical trials and investors' support. Expert opinion: pSi is an outstanding material that could improve existing drug delivery and photodynamic therapies in different areas, paving the way for developing advanced theranostic nanomedicines and incorporating payloads of therapeutics with imaging capabilities. However, more extensive in-vivo studies are needed to assess the feasibility and reliability of this technology for clinical practice. The technical and commercial challenges that this technology face are still uncertain.
Increased dissolution rate and oral bioavailability of hydrophobic drug glyburide tablets produced using supercritical CO₂ silica dispersion technology.

PubMed

Guan, Jibin; Han, Jihong; Zhang, Dong; Chu, Chunxia; Liu, Hongzhuo; Sun, Jin; He, Zhonggui; Zhang, Tianhong

2014-04-01

The aim of this study was to design a silica-supported solid dispersion of a water-insoluble drug, glyburide, to increase its dissolution rate and oral absorption using supercritical fluid (SCF) technology. DSC and PXRD results indicated that the encapsulated drug in the optimal solid dispersion was in an amorphous state and the product was stable for 6 months. Glyburide was adsorbed onto the porous silica, as confirmed by the SEM images and BET analysis. Furthermore, FT-IR spectroscopy confirmed that there was no change in the chemical structure of glyburide after the application of SCF. The glyburide silica-based dispersion could also be compressed into tablet form. In vitro drug release analysis of the silica solid dispersion tablets demonstrated faster release of glyburide compared with the commercial micronized tablet. In an in vivo test, the AUC of the tablets composed of the new glyburide silica-based solid dispersion was 2.01 times greater than that of the commercial micronized glyburide tablets. In conclusion, SCF technology presents a promising approach to prepare silica-based solid dispersions of hydrophobic drugs because of its ability to increase their release and oral bioavailability. Copyright © 2013 Elsevier B.V. All rights reserved.
Prescriber preference for a particular tumour necrosis factor antagonist drug and treatment discontinuation: population-based cohort

PubMed Central

Fisher, Anat; Bassett, Ken; Wright, James M; Brookhart, M Alan; Freeman, Hugh J; Dormuth, Colin R

2014-01-01

Objective To assess the effect of physician preference for a particular tumour necrosis factor α (TNF) antagonist on the risk of treatment discontinuation in rheumatoid arthritis. Design Population-based cohort study. Setting British Columbia administrative health data (inpatients, outpatients and pharmacy). Participants 2742 British Columbia residents who initiated a first course of a TNF antagonist between 2001 and December 2008, had been diagnosed with rheumatoid arthritis, and were treated by 1 of 58 medium-volume to high-volume prescribers. Independent variable A level of physician preference for the drug (higher or lower) was assigned based on preceding prescribing records of the care-providing physician. Higher preference was defined as at least 60% of TNF antagonist courses initiated in the preceding year. Sensitivity analysis was conducted with different thresholds for higher preference. Main outcome measure Drug discontinuation was defined as a drug-free interval of 180 days or switching to another TNF antagonist, anakinra, rituximab or abatacept. The risk of discontinuation was compared between different levels of physician preference using survival analysis. Results Higher preference for the prescribed TNF antagonist was associated with improved persistence with the drug (4.28 years (95% CI 3.70 to 4.90) vs 3.27 (2.84 to 3.84), with log rank test p value of 0.017). The adjusted HR for discontinuation was significantly lower in courses of drugs with higher preference (0.85 (0.76 to 0.96)). The results were robust in a sensitivity analysis. Conclusions Higher physician preference was associated with decreased risk of discontinuing TNF antagonists in patients with rheumatoid arthritis. This finding suggests that physicians who strongly prefer a specific treatment help their patients to stay on treatment for a longer duration. Similar research on other treatments is warranted. PMID:25270855
Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania—Synthesis and Antibacterial Properties

PubMed Central

Svensson, Fredric G.; Agafonov, Alexander V.; Håkansson, Sebastian; Seisenbaeva, Gulaim A.

2018-01-01

Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC) production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II) solution in aqueous ammonia followed by acid hydrolysis with diluted H2SO4. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus. It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents. PMID:29642486
Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania-Synthesis and Antibacterial Properties.

PubMed

Evdokimova, Olga L; Svensson, Fredric G; Agafonov, Alexander V; Håkansson, Sebastian; Seisenbaeva, Gulaim A; Kessler, Vadim G

2018-04-08

Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC) production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II) solution in aqueous ammonia followed by acid hydrolysis with diluted H₂SO₄. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus . It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents.
Nanocrystal for ocular drug delivery: hope or hype.

PubMed

Sharma, Om Prakash; Patel, Viral; Mehta, Tejal

2016-08-01

The complexity of the structure and nature of the eye emanates a challenge for drug delivery to formulation scientists. Lower bioavailability concern of conventional ocular formulation provokes the interest of researchers in the development of novel drug delivery system. Nanotechnology-based formulations have been extensively investigated and found propitious in improving bioavailability of drugs by overcoming ocular barriers prevailing in the eye. The advent of nanocrystals helped in combating the problem of poorly soluble drugs specifically for oral and parenteral drug delivery and led to development of various marketed products. Nanocrystal-based formulations explored for ocular drug delivery have been found successful in achieving increase in retention time, bioavailability, and permeability of drugs across the corneal and conjunctival epithelium. In this review, we have highlighted the ocular physiology and barriers in drug delivery. A comparative analysis of various nanotechnology-based ocular formulations is done with their pros and cons. Consideration is also given to various methods of preparation of nanocrystals with their patented technology. This article highlights the success achieved in conquering various challenges of ocular delivery by the use of nanocrystals while emphasizing on its advantages and application for ocular formulation. The perspectives of nanocrystals as an emerging flipside to explore the frontiers of ocular drug delivery are discussed.
Prediction of drug synergy in cancer using ensemble-based machine learning techniques

NASA Astrophysics Data System (ADS)

Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

2018-04-01

Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.
Analysis of the Risks and Benefits of New Chemical Entities Approved by the US Food and Drug Administration (FDA) and Subsequently Withdrawn From the US Market.

PubMed

Patriarca, Peter A; Van Auken, R Michael; Kebschull, Scott A

2018-01-01

Benefit-risk evaluations of drugs have been conducted since the introduction of modern regulatory systems more than 50 years ago. Such judgments are typically made on the basis of qualitative or semiquantitative approaches, often without the aid of quantitative assessment methods, the latter having often been applied asymmetrically to place emphasis on benefit more so than harm. In an effort to preliminarily evaluate the utility of lives lost or saved, or quality-adjusted life-years (QALY) lost and gained as a means of quantitatively assessing the potential benefits and risks of a new chemical entity, we focused our attention on the unique scenario in which a drug was initially approved based on one set of data, but later withdrawn from the market based on a second set of data. In this analysis, a dimensionless risk to benefit ratio was calculated in each instance, based on the risk and benefit quantified in similar units. The results indicated that FDA decisions to approve the drug corresponded to risk to benefit ratios less than or equal to 0.136, and that decisions to withdraw the drug from the US market corresponded to risk to benefit ratios greater than or equal to 0.092. The probability of FDA approval was then estimated using logistic regression analysis. The results of this analysis indicated that there was a 50% probability of FDA approval if the risk to benefit ratio was 0.121, and that the probability approaches 100% for values much less than 0.121, and the probability approaches 0% for values much greater than 0.121. The large uncertainty in these estimates due to the small sample size and overlapping data may be addressed in the future by applying the methodology to other drugs.
Socializing in an open drug scene: the relationship between access to private space and drug-related street disorder.

PubMed

Debeck, Kora; Wood, Evan; Qi, Jiezhi; Fu, Eric; McArthur, Doug; Montaner, Julio; Kerr, Thomas

2012-01-01

Limited attention has been given to the potential role that the structure of housing available to people who are entrenched in street-based drug scenes may play in influencing the amount of time injection drug users (IDU) spend on public streets. We sought to examine the relationship between time spent socializing in Vancouver's drug scene and access to private space. Using multivariate logistic regression we evaluated factors associated with socializing (three+ hours each day) in Vancouver's open drug scene among a prospective cohort of IDU. We also assessed attitudes towards relocating socializing activities if greater access to private indoor space was provided. Among our sample of 1114 IDU, 43% fit our criteria for socializing in the open drug scene. In multivariate analysis, having limited access to private space was independently associated with socializing (adjusted odds ratio: 1.80, 95% confidence interval: 1.28-2.55). In further analysis, 65% of 'socializers' reported positive attitudes towards relocating socializing if they had greater access to private space. These findings suggest that providing IDU with greater access to private indoor space may reduce one component of drug-related street disorder. Low-threshold supportive housing based on the 'housing first' model that include safeguards to manage behaviors associated with illicit drug use appear to offer important opportunities to create the types of private spaces that could support a reduction in street disorder. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Predicting In Vivo Anti-Hepatofibrotic Drug Efficacy Based on In Vitro High-Content Analysis

PubMed Central

Zheng, Baixue; Tan, Looling; Mo, Xuejun; Yu, Weimiao; Wang, Yan; Tucker-Kellogg, Lisa; Welsch, Roy E.; So, Peter T. C.; Yu, Hanry

2011-01-01

Background/Aims Many anti-fibrotic drugs with high in vitro efficacies fail to produce significant effects in vivo. The aim of this work is to use a statistical approach to design a numerical predictor that correlates better with in vivo outcomes. Methods High-content analysis (HCA) was performed with 49 drugs on hepatic stellate cells (HSCs) LX-2 stained with 10 fibrotic markers. ∼0.3 billion feature values from all cells in >150,000 images were quantified to reflect the drug effects. A systematic literature search on the in vivo effects of all 49 drugs on hepatofibrotic rats yields 28 papers with histological scores. The in vivo and in vitro datasets were used to compute a single efficacy predictor (Epredict). Results We used in vivo data from one context (CCl4 rats with drug treatments) to optimize the computation of Epredict. This optimized relationship was independently validated using in vivo data from two different contexts (treatment of DMN rats and prevention of CCl4 induction). A linear in vitro-in vivo correlation was consistently observed in all the three contexts. We used Epredict values to cluster drugs according to efficacy; and found that high-efficacy drugs tended to target proliferation, apoptosis and contractility of HSCs. Conclusions The Epredict statistic, based on a prioritized combination of in vitro features, provides a better correlation between in vitro and in vivo drug response than any of the traditional in vitro markers considered. PMID:22073152

Socializing in an Open Drug Scene: The relationship Between Access to Private Space and Drug-Related Street Disorder

PubMed Central

DeBeck, Kora; Wood, Evan; Qi, Jiezhi; Fu, Eric; McArthur, Doug; Montaner, Julio; Kerr, Thomas

2011-01-01

Background Limited attention has been given to the potential role that the structure of housing available to people who are entrenched in street-based drug scenes may play in influencing the amount of time injection drug users (IDU) spend on public streets. We sought to examine the relationship between time spent socializing in Vancouver's drug scene and access to private space. Methods Using multivariate logistic regression we evaluated factors associated with socializing (three+ hours each day) in Vancouver's open drug scene among a prospective cohort of IDU. We also assessed attitudes towards relocating socializing activities if greater access to private indoor space was provided. Results Among our sample of 1114 IDU, 43% fit our criteria for socializing in the open drug scene. In multivariate analysis, having limited access to private space was independently associated with socializing (adjusted odds ratio: 1.80, 95% confidence interval: 1.28 – 2.55). In further analysis, 65% of ‘socializers’ reported positive attitudes towards relocating socializing if they had greater access to private space. Conclusion These findings suggest that providing IDU with greater access to private indoor space may reduce one component of drug-related street disorder. Low-threshold supportive housing based on the ‘housing first’ model that include safeguards to manage behaviors associated with illicit drug use appear to offer important opportunities to create the types of private spaces that could support a reduction in street disorder. PMID:21764528
A community stakeholder analysis of drug resistance strategies of rural native Hawaiian youth.

PubMed

Okamoto, Scott K; Helm, Susana; Delp, Justin A; Stone, Kristina; Dinson, Ay-Laina; Stetkiewicz, Jennifer

2011-08-01

This study examines and validates the drug resistance strategies identified by rural Hawaiian youth from prior research with a sample of community stakeholders on the Island of Hawai'i. One hundred thirty-eight stakeholders with a vested interest in reducing youth substance use (i.e., teachers, principals, social service agency providers, and older youth) completed a web-based survey comprised of 15 drug-related problem situations and 413 responses developed by Hawaiian youth. The findings corroborated the youth-focused findings from prior research. Differences in the endorsement of different strategies were examined based on gender, ethnicity, and age of the stakeholders. Implications for culturally grounded drug prevention in rural Hawaiian communities are discussed.
Droplet microfluidics with magnetic beads: a new tool to investigate drug-protein interactions.

PubMed

Lombardi, Dario; Dittrich, Petra S

2011-01-01

In this study, we give the proof of concept for a method to determine binding constants of compounds in solution. By implementing a technique based on magnetic beads with a microfluidic device for segmented flow generation, we demonstrate, for individual droplets, fast, robust and complete separation of the magnetic beads. The beads are used as a carrier for one binding partner and hence, any bound molecule is separated likewise, while the segmentation into small microdroplets ensures fast mixing, and opens future prospects for droplet-wise analysis of drug candidate libraries. We employ the method for characterization of drug-protein binding, here warfarin to human serum albumin. The approach lays the basis for a microfluidic droplet-based screening device aimed at investigating the interactions of drugs with specific targets including enzymes and cells. Furthermore, the continuous method could be employed for various applications, such as binding assays, kinetic studies, and single cell analysis, in which rapid removal of a reactive component is required.
Mexicans' use of illicit drugs in an era of drug reform: national comparative analysis by migrant status.

PubMed

Guerrero, Erick G; Villatoro, Jorge Ameth; Kong, Yinfei; Gamiño, Marycarmen Bustos; Vega, William A; Mora, Maria Elena Medina

2014-05-01

Although rates of illicit drug use are considerably lower in Mexico than in the United States, rates in Mexico have risen significantly. This increase has particular implications for Mexican women and US migrants, who are considered at increased risk of drug use. Due to drug reforms enacted in Mexico in 2008, it is critical to evaluate patterns of drug use among migrants who reside in both regions. We analysed a sample of Mexicans (N=16,249) surveyed during a national household survey in 2011, the Encuesta Nacional de Adicciones (National Survey of Addictions). Comparative analyses based on Mexicans' migrant status - (1) never in the United States, (2) visited the United States, or (3) lived in the United States (transnationals) - featured analysis of variance and Chi-square global tests. Two multilevel regressions were conducted to determine the relationships among migrant status, women, and illicit drug use. Comparative findings showed significant differences in type and number of drugs used among Mexicans by migrant status. The regression models showed that compared with Mexicans who had never visited the United States, Mexican transnationals were more likely to report having used drugs (OR=2.453, 95% CI=1.933, 3.113) and using more illicit drugs (IRR=2.061, 95% CI=1.626, 2.613). Women were less likely than men to report having used drugs (OR=0.187, 95% CI=0.146, 0.239) and using more illicit drugs (IRR=0.153, 95% CI=0.116, 0.202). Overall, the findings support further exploration of risk factors for illicit drug use among Mexican transnationals, who exhibit greater drug use behaviours than Mexicans never in the United States. Because drug reform mandates referrals to treatment for those with recurrent issues of drug use, it is critical for the Mexican government and civic society to develop the capacity to offer evidence-based substance abuse treatment for returning migrants with high-risk drug behaviours. Copyright © 2014 Elsevier B.V. All rights reserved.
Mexicans’ Use of Illicit Drugs in an Era of Drug Reform: National Comparative Analysis by Migrant Status

PubMed Central

Villatoro, Jorge Ameth; Kong, Yinfei; Gamiño, Marycarmen Bustos; Vega, William A.; Mora, Maria Elena Medina

2014-01-01

Although rates of illicit drug use are considerably lower in Mexico than in the United States, rates in Mexico have risen significantly. This increase has particular implications for Mexican women and U.S. migrants, who are considered at increased risk of drug use. Due to drug reforms enacted in Mexico in 2008, it is critical to evaluate patterns of drug use among migrants who reside in both regions. We analysed a sample of Mexicans (N = 16,249) surveyed during a national household survey in 2011, the Encuesta Nacional de Adicciones (National Survey of Addictions). Comparative analyses based on Mexicans’ migrant status—(1) never in the United States, (2) visited the United States, or (3) lived in the United States (transnationals)—featured analysis of variance and chi-square global tests. Two multilevel regressions were conducted to determine the relationships among migrant status, women, and illicit drug use. Comparative findings showed significant differences in type and number of drugs used among Mexicans by migrant status. The regression models showed that compared with Mexicans who had never visited the United States, Mexican transnationals were more likely to report having used drugs (OR = 2.453, 95% CI = 1.933, 3.113) and using more illicit drugs (IRR = 2.061, 95% CI = 1.626, 2.613). Women were less likely than men to report having used drugs (OR = 0.187, 95% CI = 0.146, 0.239) and using more illicit drugs (IRR = 0.153, 95% CI = 0.116, 0.202). Overall, the findings support further exploration of risk factors for illicit drug use among Mexican transnationals, who exhibit greater drug use behaviours than Mexicans never in the United States. Because drug reform mandates referrals to treatment for those with recurrent issues of drug use, it is critical for the Mexican government and civic society to develop the capacity to offer evidence-based substance abuse treatment for returning migrants with high-risk drug behaviours. PMID:24816376
Study of small-cell lung cancer cell-based sensor and its applications in chemotherapy effects rapid evaluation for anticancer drugs.

PubMed

Guohua, Hui; Hongyang, Lu; Zhiming, Jiang; Danhua, Zhu; Haifang, Wan

2017-11-15

Small cell lung cancer (SCLC) is a smoking-related cancer disease. Despite improvement in clinical survival, SCLC outcome remains extremely poor. Cisplatin (DDP) is the first-line chemotherapy drug for SCLC, but the choice of second-line chemotherapy drugs is not clear. In this paper, a SCLC cell-based sensor was proposed, and its applications in chemotherapy effects rapid evaluation for anticancer drugs were investigated. SCLC cell lines lung adenocarcinoma cell (LTEP-P) and DDP-resistant lung adenocarcinoma cell (LTEP-P/DDP-1.0) are cultured on carbon screen-printed electrode (CSPE) to fabricate integrated cell-based sensor. Several chemotherapy anticancer drugs, including cisplatin, ifosmamide, gemcitabine, paclitaxel, docetaxel, vinorelbine, etoposide, camptothecin, and topotecan, are selected as experimental chemicals. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) tests are conducted to evaluate chemotherapy drug effects on LTEP-P and LTEP-P/DDP-1.0 cell lines. Electrical cell-substrate impedance sensing (ECIS) responses to anti-tumor chemicals are measured and processed by double-layered cascaded stochastic resonance (DCSR). Cisplatin solutions in different concentrations measurement results demonstrate that LTEP-P cell-based sensor presents quantitative analysis abilities for cisplatin and topotecan. Cisplatin and its mixtures can also be discriminated. Results demonstrate that LTEP-P cell-based sensor sensitively evaluates chemotherapy drugs' apoptosis function to SCLC cells. LTEP-P/DDP-1.0 cell-based sensor responses demonstrate that gemcitabine, vinorelbine, and camptothecin are ideal second-line drugs for clinical post-cisplatin therapy than other drugs according to MTT test results. This work provides a novel way for SCLC second-line clinical chemotherapy drug screening. Copyright © 2017 Elsevier B.V. All rights reserved.
New strategy for drug discovery by large-scale association analysis of molecular networks of different species.

PubMed

Zhang, Bo; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Wu, Ziyin; Zhang, Wenjuan; Yang, Xiaoyan; Gong, Fukai; Li, Yuerong; Chen, Xiaoyu; Gao, Shuo; Chen, Xuetong; Li, Yan; Lu, Aiping; Wang, Yonghua

2016-02-25

The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.
Risk of drug resistance in Plasmodium falciparum malaria therapy-a systematic review and meta-analysis.

PubMed

Zhou, Li-Juan; Xia, Jing; Wei, Hai-Xia; Liu, Xiao-Jun; Peng, Hong-Juan

2017-02-01

Plasmodium falciparum is responsible for the vast majority of the morbidity and mortality associated with malaria infection globally. Although a number of studies have reported the emergence of drug resistance in different therapies for P. falciparum infection, the degree of the drug resistance in different antimalarials is still unclear. This research investigated the risk of drug resistance in the therapies with different medications based on meta-analyses. Relevant original randomized control trials (RCTs) were searched in all available electronic databases. Pooled relative risks (RRs) with 95% confidence intervals (95% CIs) were used to evaluate the risk of drug resistance resulting from different treatments. Seventy-eight studies were included in the meta-analysis to compare drug resistance in the treatment of P. falciparum infections and yielded the following results: chloroquine (CQ) > sulfadoxine-pyrimethamine (SP) (RR = 3.67, p < 0.001 ), mefloquine (MQ) < SP (RR = 0.26, p < 0.001), artesunate + sulfadoxine-pyrimethamine (AS + SP) > artemether + lumefantrine (AL) (RR = 2.94, p < 0.001), dihydroartemisinin + piperaquine (DHA + PQ) < AL (RR = 0.7, p < 0.05), and non-artemisinin-based combination therapies (NACTs) > artemisinin-based combination therapies (ACTs) (RR = 1.93, p < 0.001); no significant difference was found in amodiaquine (AQ) vs. SP, AS + AQ vs. AS + SP, AS + AQ vs. AL, or AS + MQ vs. AL. These results presented a global view for the current status of antimalarial drug resistance and provided a guidance for choice of antimalarials for efficient treatment and prolonging the life span of the current effective antimalarial drugs.
Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance.

PubMed

Emad, Amin; Cairns, Junmei; Kalari, Krishna R; Wang, Liewei; Sinha, Saurabh

2017-08-11

Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance. We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group. Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.
78 FR 48636 - Current Good Manufacturing Practice and Hazard Analysis and Risk-Based Preventive Controls for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-09

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration 21 CFR Parts 1, 16, 106, 110... Manufacturing Practice and Hazard Analysis and Risk- Based Preventive Controls for Human Food; Extension of...-Based Preventive Controls for Human Food,'' that appeared in the Federal Register of January 16, 2013...
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

NASA Astrophysics Data System (ADS)

di Clemente, Riccardo; Pietronero, Luciano

2012-07-01

We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
Computational investigation of drug-resistant mutant of M2 proton channel (S31N) against rimantadine.

PubMed

Karthick, V; Ramanathan, K

2014-11-01

M2 proton channel is the target for treating the patients who ere suffering from influenza A infection, which facilitates the spread of virions. Amantadine and rimantadine are adamantadine-based drugs, which target M2 proton channel and inhibit the viral replication. Preferably, rimantadine drug is used more than amantadine because of its fewer side effects. However, S31N mutation in the M2 proton channel was highly resistant to the rimantadine drug. Therefore, in the present study, we focused to understand the drug-resistance mechanism of S31N mutation with the aid of molecular docking and dynamics approach. The docking analysis undoubtedly indicates that affinity for rimantadine with mutant-type M2 proton channel is significantly lesser than the native-type M2 proton channel. In addition, RMSD, RMSF, and principal component analysis suggested that the mutation shows increased flexibility. Furthermore, the intermolecular hydrogen bonds analysis showed that there is a complete loss of hydrogen bonds in the mutant complex. On the whole, we conclude that the intermolecular contact was maintained by D-44, a key residue for stable binding of rimantadine. These findings are certainly helpful for better understanding of drug-resistance mechanism and also helpful for designing new drugs for treating influenza infection against drug-resistance target.
FLIM FRET Technology for Drug Discovery: Automated Multiwell-Plate High-Content Analysis, Multiplexed Readouts and Application in Situ**

PubMed Central

Kumar, Sunil; Alibhai, Dominic; Margineanu, Anca; Laine, Romain; Kennedy, Gordon; McGinty, James; Warren, Sean; Kelly, Douglas; Alexandrov, Yuriy; Munro, Ian; Talbot, Clifford; Stuckey, Daniel W; Kimberly, Christopher; Viellerobe, Bertrand; Lacombe, Francois; Lam, Eric W-F; Taylor, Harriet; Dallman, Margaret J; Stamp, Gordon; Murray, Edward J; Stuhmeier, Frank; Sardini, Alessandro; Katan, Matilda; Elson, Daniel S; Neil, Mark A A; Dunsby, Chris; French, Paul M W

2011-01-01

A fluorescence lifetime imaging (FLIM) technology platform intended to read out changes in Förster resonance energy transfer (FRET) efficiency is presented for the study of protein interactions across the drug-discovery pipeline. FLIM provides a robust, inherently ratiometric imaging modality for drug discovery that could allow the same sensor constructs to be translated from automated cell-based assays through small transparent organisms such as zebrafish to mammals. To this end, an automated FLIM multiwell-plate reader is described for high content analysis of fixed and live cells, tomographic FLIM in zebrafish and FLIM FRET of live cells via confocal endomicroscopy. For cell-based assays, an exemplar application reading out protein aggregation using FLIM FRET is presented, and the potential for multiple simultaneous FLIM (FRET) readouts in microscopy is illustrated. PMID:21337485
Annotation analysis for testing drug safety signals using unstructured clinical notes

PubMed Central

2012-01-01

Background The electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text of clinical notes and is not gathered into centralized repositories. With the increasing access to large volumes of electronic medical data—in particular the clinical notes—it may be possible to computationally encode and to test drug safety signals in an active manner. Results We describe the application of simple annotation tools on clinical text and the mining of the resulting annotations to compute the risk of getting a myocardial infarction for patients with rheumatoid arthritis that take Vioxx. Our analysis clearly reveals elevated risks for myocardial infarction in rheumatoid arthritis patients taking Vioxx (odds ratio 2.06) before 2005. Conclusions Our results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records. PMID:22541596
Phospholipid-based solid drug formulations for oral bioavailability enhancement: A meta-analysis.

PubMed

Fong, Sophia Yui Kau; Brandl, Martin; Bauer-Brandl, Annette

2015-12-01

Low bioavailability nowadays often represents a challenge in oral dosage form development. Solid formulations composed of drug and phospholipid (PL), which, upon contact with water, eventually form multilamellar liposomes (i.e. 'proliposomes'), are an emerging approach to solve such issue. Regarded as an 'improved' version of liposomes concerning storage stability, the potential and versatility of a range of such formulations for oral drug delivery have been extensively discussed. However, a systematic and quantitative analysis of the studies that applied solid PL for oral bioavailability enhancement is currently lacking. Such analysis is necessary for providing an overview of the research progress and addressing the question on how promising this approach can be on bioavailability enhancement. The current review performed a systematic search of references in three evidence-based English databases, Medline, Embase, and SciFinder, from the year of 1985 up till March 2015. A total of 112 research articles and 82 patents that involved solid PL-based formulations were identified. The majority of such formulations was intended for oral drug delivery (55%) and was developed to address low bioavailability issues (49%). A final of 54 studies that applied such formulations for bioavailability enhancement of 43 different drugs with poor water solubility and/or permeability were identified. These proof-of-concept studies with in vitro (n=31) and/or animal (n=23) evidences have been systematically summarized. Meta-analyses were conducted to measure the overall enhancement power (percent increase compared to control group) of solid PL formulations on drugs' solubility, permeability and oral bioavailability, which were found to be 127.4% (95% CI [86.1, 168.7]), 59.6% (95% CI [30.1, 89.0]), and 18.5% (95% CI [10.1, 26.9]) respectively. Correlations between the enhancement factors and in silico physiochemical properties of drugs were also performed to check if such approach can be used to identify the best candidates for oral solid PL formulation. In addition to scientific literature, 13 solid PL formulation-related patents that addressed the issue of low oral bioavailability have been identified and summarized; whereas no clinical study was identified from the current search. By providing systematic information and meta-analysis on studies that applied the principle of 'proliposomes' for oral bioavailability enhancement, the current review should be insightful for formulation scientists who wish to adopt the PL based approach to overcome the solubility, permeability and bioavailability issues of orally delivered drugs. Copyright © 2015 Elsevier B.V. All rights reserved.
Computer-aided drug design for AMP-activated protein kinase activators.

PubMed

Wang, Zhanli; Huo, Jianxin; Sun, Lidan; Wang, Yongfu; Jin, Hongwei; Yu, Hui; Zhang, Liangren; Zhou, Lishe

2011-09-01

AMP-activated protein kinase (AMPK) is an important therapeutic target for the potential treatment of metabolic disorders, cardiovascular disease and cancer. Recently, various classes of compounds that activate AMPK by direct or indirect interactions have been reported. The importance of computer-aided drug design approaches in the search for potent activators of AMPK is now established, including structure-based design, ligand-based design, fragment-based design, as well as structural analysis. This review article highlights the computer-aided drug design approaches utilized to discover of activators targeting AMPK. The principles, advantages or limitation of the different methods are also being discussed together with examples of applications taken from the literatures.
The sweet tooth of biopharmaceuticals: importance of recombinant protein glycosylation analysis.

PubMed

Lingg, Nico; Zhang, Peiqing; Song, Zhiwei; Bardor, Muriel

2012-12-01

Biopharmaceuticals currently represent the fastest growing sector of the pharmaceutical industry, mainly driven by a rapid expansion in the manufacture of recombinant protein-based drugs. Glycosylation is the most prominent post-translational modification occurring on these protein drugs. It constitutes one of the critical quality attributes that requires thorough analysis for optimal efficacy and safety. This review examines the functional importance of glycosylation of recombinant protein drugs, illustrated using three examples of protein biopharmaceuticals: IgG antibodies, erythropoietin and glucocerebrosidase. Current analytical methods are reviewed as solutions for qualitative and quantitative measurements of glycosylation to monitor quality target product profiles of recombinant glycoprotein drugs. Finally, we propose a framework for designing the quality target product profile of recombinant glycoproteins and planning workflow for glycosylation analysis with the selection of available analytical methods and tools. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Phenytoin-Bovine Serum Albumin interactions - modeling plasma protein - drug binding: A multi-spectroscopy and in silico-based correlation

NASA Astrophysics Data System (ADS)

Suresh, P. K.; Divya, Naik; Nidhi, Shah; Rajasekaran, R.

2018-03-01

The study focused on the analysis of the nature and site of binding of Phenytoin (PHT) -(a model hydrophobic drug) with Bovine Serum Albumin (BSA) (a model protein used as a surrogate for HSA). Interactions with defined amounts of Phenytoin and BSA demonstrated a blue shift (hypsochromic -change in the microenvironment of the tryptophan residue with decrease in the polar environment and more of hydrophobicity) with respect to the albumin protein and a red shift (bathochromic -hydrophobicity and polarity related changes) in the case of the model hydrophobic drug. This shift, albeit lower in magnitude, has been substantiated by a fairly convincing, Phenytoin-mediated quenching of the endogenous fluorophore in BSA. Spectral shifts studied at varying pH, temperatures and incubation periods (at varying concentrations of PHT with a defined/constant BSA concentration) showed no significant differences (data not shown). FTIR analysis provided evidence of the interaction of PHT with BSA with a stretching vibration of 1737.86 cm- 1, apart from the vibrations characteristically associated with the amine and carboxyl groups respectively. Our in vitro findings were extended to molecular docking of BSA with PHT (with the different ionized forms of the drug) and the subsequent LIGPLOT-based analysis. In general, a preponderance of hydrophobic interactions was observed. These hydrophobic interactions corroborate the tryptophan-based spectral shifts and the fluorescence quenching data. These results substantiates our hitherto unreported in vitro/in silico experimental flow and provides a basis for screening other hydrophobic drugs in its class.
Company observational post-marketing studies: drug risk assessment and drug research in special populations--a study-based analysis.

PubMed

Hasford, J; Lamprecht, T

1998-01-01

Company observational post-marketing studies (COPS) claim to provide essential data about drug risks and effectiveness in special populations not admitted to pre-approval clinical trials. Since COPS are often mainly regarded as a marketing activity, this study-based analysis tries to evaluate the scientific contributions of COPS. Thirty-five COPS were identified by hand-searching through medical journals, writing to pharmaceutical manufacturers and using MEDLINE. Fourteen COPS evaluated cardiovascular drugs, 9 evaluated NSAIDs and 12 evaluated various other indications. Thirty-five COPS listed effectiveness, 31 listed safety and 8 listed patient compliance as principal objectives. Not a single COPS included a control group. Seventeen of 21 evaluable COPS mentioned extensive exclusion criteria similar to those in clinical trials. Median observation time was 8 weeks, too short for chronic diseases and for adverse drug reactions with longer latency periods. One new adverse event was regarded. Global assessments of the outcomes by physicians dominated and were not based on objective clinical findings. None of the studies specified any details concerning the standardisation of observations or quality-control procedures. The current COPS scheme does not contribute significantly to our knowledge of drug safety and the effects in special populations. Despite serious criticism over the past 20 years, the poor quality of COPS compared with dramatic improvements of pre-approval trials - implies a need for detailed guidelines for non-experimental phase IV research, similar to the Good Clinical Practice-Guideline of the European Community.
Comparative safety profiles of intravitreal bevacizumab, ranibizumab and pegaptanib: the analysis of the WHO database of adverse drug reactions.

PubMed

Biagi, C; Conti, V; Montanaro, N; Melis, M; Buccellato, E; Donati, M; Covezzoli, A; Amato, R; Pazzi, L; Venegoni, M; Vaccheri, A; Motola, D

2014-12-01

The purpose of this study is to conduct a comparative analysis of the suspected adverse drug reactions (ADRs) associated with intravitreal bevacizumab, ranibizumab and pegaptanib in the WHO database in order to have a real-life information on these drugs, which now is only based on data coming from clinical trials. ADR reports for intravitreal use of bevacizumab, ranibizumab and pegaptanib from January 2002 to December 2012 were selected from the WHO-VigiBase. Reporting odds ratio (ROR) with confidence interval of 95 % and p value was calculated. The analysis was performed for drug-reaction pairs. The Medical Dictionary for Regulatory Activities (MedDRA) terminology for ADRs was used. The analysis was performed on 3180 reports corresponding to 7753 drug-reaction pairs. Significant RORs for endophthalmitis and uveitis (1.90, 95 % confidence interval (CI) 1.48-2.43, and 10.62, 6.62-17.05, respectively) were retrieved for bevacizumab, and cerebrovascular accident and myocardial infarction produced significant ROR (1.54, 1.14-2.10 and 1.73, 1.18-2.53, respectively) for ranibizumab. Pegaptanib was significantly associated with visual impairment (1.98, 1.12-3.5, p = 0.02), nausea (3.29, 1.57-6.86, p < 0.001), vomiting (2.91, 1.2-7.07, p = 0.01) and drug hypersensitivity (8.75, 3.1-24.66, p < 0.001). Our data showed an elevated disproportionality for cardiovascular ADRs in patients treated with ranibizumab and for infective ocular reactions in those treated with bevacizumab. No relevant safety issues were identified for pegaptanib. These findings suggest bevacizumab as a suitable choice for AMD therapy due to its effectiveness similar to that of ranibizumab, its favourable safety profile and for its lower cost.

Assessment of Web-Based Consumer Reviews as a Resource for Drug Performance

PubMed Central

Adusumalli, Swarnaseetha; Lee, HueyTyng; Hoi, Qiangze; Koo, Si-Lin; Tan, Iain Beehuat

2015-01-01

Background Some health websites provide a public forum for consumers to post ratings and reviews on drugs. Drug reviews are easily accessible and comprehensible, unlike clinical trials and published literature. Because the public increasingly uses the Internet as a source of medical information, it is important to know whether such information is reliable. Objective We aim to examine whether Web-based consumer drug ratings and reviews can be used as a resource to compare drug performance. Methods We analyzed 103,411 consumer-generated reviews on 615 drugs used to treat 249 disease conditions from the health website WebMD. Statistical analysis identified 427 drug pairs from 24 conditions for which two drugs treating the same condition had significantly and substantially different satisfaction ratings (with at least a half-point difference between Web-based ratings and P<.01). PubMed and Google Scholar were searched for publications that were assessed for concordance with findings online. Results Scientific literature was found for 77 out of the 427 drug pairs and compared to findings online. Nearly two-thirds (48/77, 62%) of the online drug trends with at least a half-point difference in online ratings were supported by published literature (P=.02). For a 1-point online rating difference, the concordance rate increased to 68% (15/22) (P=.07). The discrepancies between scientific literature and findings online were further examined to obtain more insights into the usability of Web-based consumer-generated reviews. We discovered that (1) drugs with FDA black box warnings or used off-label were rated poorly in Web-based reviews, (2) drugs with addictive properties were rated higher than their counterparts in Web-based reviews, and (3) second-line or alternative drugs were rated higher. In addition, Web-based ratings indicated drug delivery problems. If FDA black box warning labels are used to resolve disagreements between publications and online trends, the concordance rate increases to 71% (55/77) (P<.001) for a half-point rating difference and 82% (18/22) for a 1-point rating difference (P=.002). Our results suggest that Web-based reviews can be used to inform patients’ drug choices, with certain caveats. Conclusions Web-based reviews can be viewed as an orthogonal source of information for consumers, physicians, and drug manufacturers to assess the performance of a drug. However, one should be cautious to rely solely on consumer reviews as ratings can be strongly influenced by the consumer experience. PMID:26319108
Integration of drug dosing data with physiological data streams using a cloud computing paradigm.

PubMed

Bressan, Nadja; James, Andrew; McGregor, Carolyn

2013-01-01

Many drugs are used during the provision of intensive care for the preterm newborn infant. Recommendations for drug dosing in newborns depend upon data from population based pharmacokinetic research. There is a need to be able to modify drug dosing in response to the preterm infant's response to the standard dosing recommendations. The real-time integration of physiological data with drug dosing data would facilitate individualised drug dosing for these immature infants. This paper proposes the use of a novel computational framework that employs real-time, temporal data analysis for this task. Deployment of the framework within the cloud computing paradigm will enable widespread distribution of individualized drug dosing for newborn infants.
EMPLOYMENT-BASED ABSTINENCE REINFORCEMENT PROMOTES OPIATE AND COCAINE ABSTINENCE IN OUT-OF-TREATMENT INJECTION DRUG USERS

PubMed Central

Holtyn, August F.; Koffarnus, Mikhail N.; DeFulio, Anthony; Sigurdsson, Sigurdur O.; Strain, Eric C.; Schwartz, Robert P.; Silverman, Kenneth

2016-01-01

We examined the use of employment-based abstinence reinforcement in out-of-treatment injection drug users, in this secondary analysis of a previously reported trial. Participants (N = 33) could work in the therapeutic workplace, a model employment-based program for drug addiction, for 30 weeks and could earn approximately $10 per hr. During a 4-week induction, participants only had to work to earn pay. After induction, access to the workplace was contingent on enrollment in methadone treatment. After participants met the methadone contingency for 3 weeks, they had to provide opiate-negative urine samples to maintain maximum pay. After participants met those contingencies for 3 weeks, they had to provide opiate- and cocaine-negative urine samples to maintain maximum pay. The percentage of drug-negative urine samples remained stable until the abstinence reinforcement contingency for each drug was applied. The percentage of opiate- and cocaine-negative urine samples increased abruptly and significantly after the opiate- and cocaine-abstinence contingencies, respectively, were applied. These results demonstrate that the sequential administration of employment-based abstinence reinforcement can increase opiate and cocaine abstinence among out-of-treatment injection drug users. PMID:25292399
Discovery of Boolean metabolic networks: integer linear programming based approach.

PubMed

Qiu, Yushan; Jiang, Hao; Ching, Wai-Ki; Cheng, Xiaoqing

2018-04-11

Traditional drug discovery methods focused on the efficacy of drugs rather than their toxicity. However, toxicity and/or lack of efficacy are produced when unintended targets are affected in metabolic networks. Thus, identification of biological targets which can be manipulated to produce the desired effect with minimum side-effects has become an important and challenging topic. Efficient computational methods are required to identify the drug targets while incurring minimal side-effects. In this paper, we propose a graph-based computational damage model that summarizes the impact of enzymes on compounds in metabolic networks. An efficient method based on Integer Linear Programming formalism is then developed to identify the optimal enzyme-combination so as to minimize the side-effects. The identified target enzymes for known successful drugs are then verified by comparing the results with those in the existing literature. Side-effects reduction plays a crucial role in the study of drug development. A graph-based computational damage model is proposed and the theoretical analysis states the captured problem is NP-completeness. The proposed approaches can therefore contribute to the discovery of drug targets. Our developed software is available at " http://hkumath.hku.hk/~wkc/APBC2018-metabolic-network.zip ".
Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

PubMed

He, Yongqun

2016-06-01

Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.
Research and Development of Hepatitis B Drugs: An Analysis Based on Technology Flows Measured by Patent Citations

PubMed Central

Wan, Jian-bo; He, Chengwei; Hu, Yuanjia

2016-01-01

Despite the existence of available therapies, the Hepatitis B virus infection continues to be one of the most serious threats to human health, especially in developing countries such as China and India. To shed light on the improvement of current therapies and development of novel anti-HBV drugs, we thoroughly investigated 212 US patents of anti-HBV drugs and analyzed the technology flow in research and development of anti-HBV drugs based on data from IMS LifeCycle databases. Moreover, utilizing the patent citation method, which is an effective indicator of technology flow, we constructed patent citation network models and performed network analysis in order to reveal the features of different technology clusters. As a result, we identified the stagnant status of anti-HBV drug development and pointed the way for development of domestic pharmaceuticals in developing countries. We also discussed about therapeutic vaccines as the potential next generation therapy for HBV infection. Lastly, we depicted the cooperation between entities and found that novel forms of cooperation added diversity to the conventional form of cooperation within the pharmaceutical industry. In summary, our study provides inspiring insights for investors, policy makers, researchers, and other readers interested in anti-HBV drug development. PMID:27727319
Phenotypic assays for Mycobacterium tuberculosis infection.

PubMed

Song, Ok-Ryul; Deboosere, Nathalie; Delorme, Vincent; Queval, Christophe J; Deloison, Gaspard; Werkmeister, Elisabeth; Lafont, Frank; Baulard, Alain; Iantomasi, Raffaella; Brodin, Priscille

2017-10-01

Tuberculosis (TB) is still a major global threat, killing more than one million persons each year. With the constant increase of Mycobacterium tuberculosis strains resistant to first- and second-line drugs, there is an urgent need for the development of new drugs to control the propagation of TB. Although screenings of small molecules on axenic M. tuberculosis cultures were successful for the identification of novel putative anti-TB drugs, new drugs in the development pipeline remains scarce. Host-directed therapy may represent an alternative for drug development against TB. Indeed, M. tuberculosis has multiple specific interactions within host phagocytes, which may be targeted by small molecules. In order to enable drug discovery strategies against microbes residing within host macrophages, we developed multiple fluorescence-based HT/CS phenotypic assays monitoring the intracellular replication of M. tuberculosis as well as its intracellular trafficking. What we propose here is a population-based, multi-parametric analysis pipeline that can be used to monitor the intracellular fate of M. tuberculosis and the dynamics of cellular events such as phagosomal maturation (acidification and permeabilization), zinc poisoning system or lipid body accumulation. Such analysis allows the quantification of biological events considering the host-pathogen interplay and may thus be derived to other intracellular pathogens. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.
Alcohol and drug involvement in motorcycle driver injuries in the city of Sao Paulo, Brazil: Analysis of crash culpability and other associated factors.

PubMed

de Carvalho, Heraclito Barbosa; Andreuccetti, Gabriel; Rezende, Marcelo Rosa; Bernini, Celso; Silva, Jorge Santos; Leyton, Vilma; D'Andréa Greve, Julia Maria

2016-05-01

Earlier studies have already identified that a greater proportion of injured drivers are under the effects of illicit drugs than alcohol in Brazil, but the crash risk attributable to each substance is still unknown. Injured motorcycle drivers who were involved in traffic accidents in the West Zone of the city of Sao Paulo were recruited for a cross-sectional study based on crash culpability analysis. Alcohol and drug positivity among drivers was evaluated according to their responsibility for the crash. Culpability ratios were generated based on the proportion of drivers who were deemed culpable in relation to those considered not culpable according to the use of drugs and alcohol. Of the 273 drivers recruited, 10.6% tested positive for alcohol. Among those who were also tested for drugs (n=232), 20.3% had consumed either alcohol and/or other drugs, 15.5% of whom were positive only for drugs other than alcohol, specifically cannabis and cocaine. Drivers who tested positive for alcohol were significantly less likely to possess a valid driver's license and to report driving professionally, whereas those who had consumed only drugs were more likely to drive professionally. The culpability ratio estimated for alcohol-positive drivers was three times higher than that for alcohol-free drivers, showing a superior ratio than drivers who had consumed only drugs other than alcohol, who presented a 1.7 times higher culpability ratio than drug-free drivers. Substance use was overrepresented among culpable motorcycle drivers, with alcohol showing a greater contribution to crash culpability than other drugs. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
A bioinformatics approach for precision medicine off-label drug drug selection among triple negative breast cancer patients

PubMed Central

Cheng, Lijun; Schneider, Bryan P

2016-01-01

Background Cancer has been extensively characterized on the basis of genomics. The integration of genetic information about cancers with data on how the cancers respond to target based therapy to help to optimum cancer treatment. Objective The increasing usage of sequencing technology in cancer research and clinical practice has enormously advanced our understanding of cancer mechanisms. The cancer precision medicine is becoming a reality. Although off-label drug usage is a common practice in treating cancer, it suffers from the lack of knowledge base for proper cancer drug selections. This eminent need has become even more apparent considering the upcoming genomics data. Methods In this paper, a personalized medicine knowledge base is constructed by integrating various cancer drugs, drug-target database, and knowledge sources for the proper cancer drugs and their target selections. Based on the knowledge base, a bioinformatics approach for cancer drugs selection in precision medicine is developed. It integrates personal molecular profile data, including copy number variation, mutation, and gene expression. Results By analyzing the 85 triple negative breast cancer (TNBC) patient data in the Cancer Genome Altar, we have shown that 71.7% of the TNBC patients have FDA approved drug targets, and 51.7% of the patients have more than one drug target. Sixty-five drug targets are identified as TNBC treatment targets and 85 candidate drugs are recommended. Many existing TNBC candidate targets, such as Poly (ADP-Ribose) Polymerase 1 (PARP1), Cell division protein kinase 6 (CDK6), epidermal growth factor receptor, etc., were identified. On the other hand, we found some additional targets that are not yet fully investigated in the TNBC, such as Gamma-Glutamyl Hydrolase (GGH), Thymidylate Synthetase (TYMS), Protein Tyrosine Kinase 6 (PTK6), Topoisomerase (DNA) I, Mitochondrial (TOP1MT), Smoothened, Frizzled Class Receptor (SMO), etc. Our additional analysis of target and drug selection strategy is also fully supported by the drug screening data on TNBC cell lines in the Cancer Cell Line Encyclopedia. Conclusions The proposed bioinformatics approach lays a foundation for cancer precision medicine. It supplies much needed knowledge base for the off-label cancer drug usage in clinics. PMID:27107440
Use of multiattribute utility theory for formulary management in a health system.

PubMed

Chung, Seonyoung; Kim, Sooyon; Kim, Jeongmee; Sohn, Kieho

2010-01-15

The application, utility, and flexibility of the multiattribute utility theory (MAUT) when used as a formulary decision methodology in a Korean medical center were evaluated. A drug analysis model using MAUT consisting of 10 steps was designed for two drug classes of dihydropyridine calcium channel blockers (CCBs) and angiotensin II receptor blockers (ARBs). These two drug classes contain the most diverse agents among cardiovascular drugs on Samsung Medical Center's drug formulary. The attributes identified for inclusion in the drug analysis model were effectiveness, safety, patient convenience, and cost, with relative weights of 50%, 30%, 10%, and 10%, respectively. The factors were incorporated into the model to quantify the contribution of each attribute. For each factor, a utility scale of 0-100 was established, and the total utility score for each alternative was calculated. An attempt was made to make the model adaptable to changing health care and regulatory circumstances. The analysis revealed amlodipine besylate to be an alternative agent, with the highest total utility score among the dihydropyridine CCBs, while barnidipine hydrochloride had the lowest score. For ARBs, losartan potassium had the greatest total utility score, while olmesartan medoxomil had the lowest. A drug analysis model based on the MAUT was successfully developed and used in making formulary decisions for dihydropyridine CCBs and ARBs for a Korean health system. The model incorporates sufficient utility and flexibility of a drug's attributes and can be used as an alternative decision-making tool for formulary management in health systems.
A systematic study of chemogenomics of carbohydrates.

PubMed

Gu, Jiangyong; Luo, Fang; Chen, Lirong; Yuan, Gu; Xu, Xiaojie

2014-03-04

Chemogenomics focuses on the interactions between biologically active molecules and protein targets for drug discovery. Carbohydrates are the most abundant compounds in natural products. Compared with other drugs, the carbohydrate drugs show weaker side effects. Searching for multi-target carbohydrate drugs can be regarded as a solution to improve therapeutic efficacy and safety. In this work, we collected 60 344 carbohydrates from the Universal Natural Products Database (UNPD) and explored the chemical space of carbohydrates by principal component analysis. We found that there is a large quantity of potential lead compounds among carbohydrates. Then we explored the potential of carbohydrates in drug discovery by using a network-based multi-target computational approach. All carbohydrates were docked to 2389 target proteins. The most potential carbohydrates for drug discovery and their indications were predicted based on a docking score-weighted prediction model. We also explored the interactions between carbohydrates and target proteins to find the pathological networks, potential drug candidates and new indications.
["When the ad is good, the product is sold." The MonitorACAO Project and drug advertising in Brazil].

PubMed

Soares, Jussara Calmon Reis de Souza

2008-04-01

This paper presents an analysis on drug advertising in Brazil, based on the final report of the MonitorACAO Project, by the group from the Universidade Federal Fluminense, Niterói, Rio de Janeiro. Due to a partnership between the university and the National Agency for Health Surveillance (ANVISA), drug advertisements were monitored and analyzed for one year, according to the methodology defined by the Agency. The samples were collected in medical practices and hospitals, drugstores, pharmacies and in scientific magazines. TV and radio programs were monitored, in the case of OTC drugs. 159 advertisements referring to pharmaceuticals were sent to ANVISA,from a total of 263 irregular ads analyzed between October 2004 and August 2005. The main problems found were the poor quality of drug information to health professionals, as well as misleading drug use to lay population. Based on the results of this project and on other studies, the banning of drug advertising in Brazil is proposed.
Injectable and body temperature sensitive hydrogels based on chitosan and hyaluronic acid for pH sensitive drug release.

PubMed

Zhang, Wei; Jin, Xin; Li, Heng; Zhang, Run-Run; Wu, Cheng-Wei

2018-04-15

Hydrogels based on chitosan/hyaluronic acid/β-sodium glycerophosphate demonstrate injectability, body temperature sensitivity, pH sensitive drug release and adhesion to cancer cell. The drug (doxorubicin) loaded hydrogel precursor solutions are injectable and turn to hydrogels when the temperature is increased to body temperature. The acidic condition (pH 4.00) can trigger the release of drug and the cancer cell (Hela) can adhere to the surface of the hydrogels, which will be beneficial for tumor site-specific administration of drug. The mechanical strength, the gelation temperature, and the drug release behavior can be tuned by varying hyaluronic acid content. The mechanisms were characterized using dynamic mechanical analysis, Fourier transform infrared spectroscopy, scanning electron microscopy and fluorescence microscopy. The carboxyl group in hyaluronic acid can form the hydrogen bondings with the protonated amine in chitosan, which promotes the increase of mechanical strength of the hydrogels and depresses the initial burst release of drug from the hydrogel. Copyright © 2018 Elsevier Ltd. All rights reserved.
Human cytosolic glutathione-S-transferases: quantitative analysis of expression, comparative analysis of structures and inhibition strategies of isozymes involved in drug resistance.

PubMed

Mohana, Krishnamoorthy; Achary, Anant

2017-08-01

Glutathione-S-transferase (GST) inhibition is a strategy to overcome drug resistance. Several isoforms of human GSTs are present and they are expressed in almost all the organs. Specific expression levels of GSTs in various organs are collected from the human transcriptome data and analysis of the organ-specific expression of GST isoforms is carried out. The variations in the level of expressions of GST isoforms are statistically significant. The GST expression differs in diseased conditions as reported by many investigators and some of the isoforms of GSTs are disease markers or drug targets. Structure analysis of various isoforms is carried out and literature mining has been performed to identify the differences in the active sites of the GSTs. The xenobiotic binding H site is classified into H1, H2, and H3 and the differences in the amino acid composition, the hydrophobicity and other structural features of H site of GSTs are discussed. The existing inhibition strategies are compared. The advent of rational drug design, mechanism-based inhibition strategies, availability of high-throughput screening, target specific, and selective inhibition of GST isoforms involved in drug resistance could be achieved for the reversal of drug resistance and aid in the treatment of diseases.
Recent progress and market analysis of anticoagulant drugs

PubMed Central

Fan, Ping; Gao, Yangyang; Zheng, Minglin; Xu, Ting; Schoenhagen, Paul

2018-01-01

This review describes epidemiology of thromboembolic disease in China and abroad, evaluates trends in the development of anticoagulant drugs, and analyzes the market situation based on large amounts of accumulated data. Specifically, we describe advances in clinical application of anticoagulants and analyze the most commonly used anticoagulants in the market systematically.
75 FR 80061 - Abbott Laboratories, Inc.; Withdrawal of Approval of a New Drug Application for MERIDIA

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-21

... withdrawing approval of a new drug application (NDA) for MERIDIA (sibutramine hydrochloride (HCl)) oral... requested that Abbott voluntarily withdraw MERIDIA (sibutramine HCl) oral capsules from the market, based on FDA's recent analysis of clinical trial data from the Sibutramine Cardiovascular Outcomes Trial (SCOUT...
Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

PubMed

Nisius, Britta; Gohlke, Holger

2012-09-24

Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.
Recent Advances in Electrochemical Biosensors Based on Enzyme Inhibition for Clinical and Pharmaceutical Applications.

PubMed

El Harrad, Loubna; Bourais, Ilhame; Mohammadi, Hasna; Amine, Aziz

2018-01-09

A large number of enzyme inhibitors are used as drugs to treat several diseases such as gout, diabetes, AIDS, depression, Parkinson's and Alzheimer's diseases. Electrochemical biosensors based on enzyme inhibition are useful devices for an easy, fast and environment friendly monitoring of inhibitors like drugs. In the last decades, electrochemical biosensors have shown great potentials in the detection of different drugs like neostigmine, ketoconazole, donepezil, allopurinol and many others. They attracted increasing attention due to the advantage of being high sensitive and accurate analytical tools, able to reach low detection limits and the possibility to be performed on real samples. This review will spotlight the research conducted in the past 10 years (2007-2017) on inhibition based enzymatic electrochemical biosensors for the analysis of different drugs. New assays based on novel bio-devices will be debated. Moreover, the exploration of the recent graphical approach in diagnosis of reversible and irreversible inhibition mechanism will be discussed. The accurate and the fast diagnosis of inhibition type will help researchers in further drug design improvements and the identification of new molecules that will serve as new enzyme targets.
Application of ethyl cellulose, microcrystalline cellulose and octadecanol for wax based floating solid dispersion pellets.

PubMed

Yan, Hong-Xiang; Zhang, Shuang-Shuang; He, Jian-Hua; Liu, Jian-Ping

2016-09-05

The present study aimed to develop and optimize the wax based floating sustained-release dispersion pellets for a weakly acidic hydrophilic drug protocatechuic acid to achieve prolonged gastric residence time and improved bioavailability. This low-density drug delivery system consisted of octadecanol/microcrystalline cellulose mixture matrix pellet cores prepared by extrusion-spheronization technique, coated with drug/ethyl cellulose 100cp solid dispersion using single-step fluid-bed coating method. The formulation-optimized pellets could maintain excellent floating state without lag time and sustain the drug release efficiently for 12h based on non-Fickian transport mechanism. Observed by SEM, the optimized pellet was the dispersion-layered spherical structure containing a compact inner core. DSC, XRD and FTIR analysis revealed drug was uniformly dispersed in the amorphous molecule form and had no significant physicochemical interactions with the polymer dispersion carrier. The stability study of the resultant pellets further proved the rationality and integrity of the developed formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Geometry of modified release formulations during dissolution--influence on performance of dosage forms with diclofenac sodium.

PubMed

Dorożyński, Przemysław; Kulinowski, Piotr; Jamróz, Witold; Juszczyk, Ewelina

2014-12-30

The objectives of the work included: presentation of magnetic resonance imaging (MRI) and fractal analysis based approach to comparison of dosage forms of different composition, structure, and assessment of the influence of the compositional factors i.e., matrix type, excipients etc., on properties and performance of the dosage form during drug dissolution. The work presents the first attempt to compare MRI data obtained for tablet formulations of different composition and characterized by distinct differences in hydration and drug dissolution mechanisms. The main difficulty, in such a case stems from differences in hydration behavior and tablet's geometry i.e., swelling, cracking, capping etc. A novel approach to characterization of matrix systems i.e., quantification of changes of geometrical complexity of the matrix shape during drug dissolution has been developed. Using three chosen commercial modified release tablet formulations with diclofenac sodium we present the method of parameterization of their geometrical complexity on the base of fractal analysis. The main result of the study is the correlation between the hydrating tablet behavior and drug dissolution - the increase of geometrical complexity expressed as fractal dimension relates to the increased variability of drug dissolution results. Copyright © 2014 Elsevier B.V. All rights reserved.

Random Forest Segregation of Drug Responses May Define Regions of Biological Significance.

PubMed

Bukhari, Qasim; Borsook, David; Rudin, Markus; Becerra, Lino

2016-01-01

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies.
Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less
National Drug Formulary review of statin therapeutic group using the multiattribute scoring tool

PubMed Central

Ramli, Azuana; Aljunid, Syed Mohamed; Sulong, Saperi; Md Yusof, Faridah Aryani

2013-01-01

Purpose HMG-CoA reductase inhibitors (statins) are extensively used in treating hypercholesterolemia. The statins available in Malaysia include atorvastatin, lovastatin, pravastatin, rosuvastatin, simvastatin, and fluvastatin. Over the years, they have accumulated in the National Drug Formulary; hence, the need for review. Effective selection of the best drugs to remain in the formulary can become complex due to the multiple drug attributes involved, and is made worse by the limited time and resources available. The multiattribute scoring tool (MAST) systematizes the evaluation of the drug attributes to facilitate the drug selection process. In this study, a MAST framework was developed to rank the statins based on their utilities or benefits. Methods Published literature on multicriteria decision analysis (MCDA) were studied and five sessions of expert group discussions were conducted to build the MAST framework and to review the evidence. The attributes identified and selected for analysis were efficacy (clinical efficacy, clinical endpoints), safety (drug interactions, serious side effects and documentation), drug applicability (drug strength/formulation, indications, dose frequency, side effects, food–drug interactions, and dose adjustments), and cost. The average weights assigned by the members for efficacy, safety, drug applicability and cost were 32.6%, 26.2%, 24.1%, and 17.1%, respectively. The utility values of the attributes were scored based on the published evidence or/and agreements during the group discussions. The attribute scores were added up to provide the total utility score. Results Using the MAST, the six statins under review were successfully scored and ranked. Atorvastatin scored the highest total utility score (TUS) of 84.48, followed by simvastatin (83.11). Atorvastatin and simvastatin scored consistently high, even before drug costs were included. The low scores on the side effects for atorvastatin were compensated for by the higher scores on the clinical endpoints resulting in a higher TUS for atorvastatin. Fluvastatin recorded the lowest TUS. Conclusion The multiattribute scoring tool was successfully applied to organize decision variables in reviewing statins for the formulary. Based on the TUS, atorvastatin is recommended to remain in the formulary and be considered as first-line in the treatment of hypercholesterolemia. PMID:24353428
From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine

PubMed Central

Everett, Jeremy R.

2016-01-01

Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments. PMID:27660611
Novel sample preparation method for surfactant containing suppositories: effect of micelle formation on drug recovery.

PubMed

Kalmár, Éva; Ueno, Konomi; Forgó, Péter; Szakonyi, Gerda; Dombi, György

2013-09-01

Rectal drug delivery is currently at the focus of attention. Surfactants promote drug release from the suppository bases and enhance the formulation properties. The aim of our work was to develop a sample preparation method for HPLC analysis for a suppository base containing 95% hard fat, 2.5% Tween 20 and 2.5% Tween 60. A conventional sample preparation method did not provide successful results as the recovery of the drug failed to fulfil the validation criterion 95-105%. This was caused by the non-ionic surfactants in the suppository base incorporating some of the drug, preventing its release. As guidance for the formulation from an analytical aspect, we suggest a well defined surfactant content based on the turbidimetric determination of the CMC (critical micelle formation concentration) in the applied methanol-water solvent. Our CMC data correlate well with the results of previous studies. As regards the sample preparation procedure, a study was performed of the effects of ionic strength and pH on the drug recovery with the avoidance of degradation of the drug during the procedure. Aminophenazone and paracetamol were used as model drugs. The optimum conditions for drug release from the molten suppository base were found to be 100 mM NaCl, 20-40 mM NaOH and a 30 min ultrasonic treatment of the final sample solution. As these conditions could cause the degradation of the drugs in the solution, this was followed by NMR spectroscopy, and the results indicated that degradation did not take place. The determined CMCs were 0.08 mM for Tween 20, 0.06 mM for Tween 60 and 0.04 mM for a combined Tween 20, Tween 60 system. Copyright © 2013 Elsevier B.V. All rights reserved.
Drug overdose surveillance using hospital discharge data.

PubMed

Slavova, Svetla; Bunn, Terry L; Talbert, Jeffery

2014-01-01

We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000-2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison.
Young people's attitudes towards illicit drugs: A population-based study.

PubMed

Friis, Karina; Østergaard, Jeanette; Reese, Sidsel; Lasgaard, Mathias

2017-12-01

Previous studies indicate that young people who have positive attitudes towards illicit drugs are more inclined to experiment with them. The first aim of our study was to identify the sociodemographic and risk behaviour characteristics of young people (16-24 years) with positive attitudes towards illicit drug use. The second aim was to identify the characteristics of young people with positive attitudes towards illicit drugs among those who had never tried drugs, those who had tried cannabis but no other illicit drugs, and those who regularly used cannabis and/or had tried other illicit drugs. The analysis was based on a population-based survey from 2013 ( N = 3812). Multiple logistic regression was used to analyse the association between sociodemographic and risk behaviour characteristics and positive attitudes towards illicit drugs. Young men had twice the odds of having positive attitudes towards illicit drug use compared with young women (AOR = 2.1). Also, young age, being single, being employed, smoking tobacco, practising unprotected sex, and experimental cannabis use were associated with positive attitudes towards illicit drug use. Finally, use of cannabis at least 10 times during the previous year and/or use of other illicit drugs had the strongest association with positive attitudes to illicit drug use (AOR = 6.0). Young people who have positive attitudes towards illicit drug use are characterized by a broad range of risky behaviours. These findings may help to identify young people at risk of initiating illicit drug use and thereby support the development and implementation of prevention programmes.
Optimizing non-invasive radiofrequency hyperthermia treatment for improving drug delivery in 4T1 mouse breast cancer model

PubMed Central

Ware, Matthew J.; Krzykawska-Serda, Martyna; Chak-Shing Ho, Jason; Newton, Jared; Suki, Sarah; Law, Justin; Nguyen, Lam; Keshishian, Vazrik; Serda, Maciej; Taylor, Kimberly; Curley, Steven A.; Corr, Stuart J.

2017-01-01

Interactions of high-frequency radio waves (RF) with biological tissues are currently being investigated as a therapeutic platform for non-invasive cancer hyperthermia therapy. RF delivers thermal energy into tissues, which increases intra-tumoral drug perfusion and blood-flow. Herein, we describe an optical-based method to optimize the short-term treatment schedules of drug and hyperthermia administration in a 4T1 breast cancer model via RF, with the aim of maximizing drug localization and homogenous distribution within the tumor microenvironment. This method, based on the analysis of fluorescent dyes localized into the tumor, is more time, cost and resource efficient, when compared to current analytical methods for tumor-targeting drug analysis such as HPLC and LC-MS. Alexa-Albumin 647 nm fluorphore was chosen as a surrogate for nab-paclitaxel based on its similar molecular weight and albumin driven pharmacokinetics. We found that RF hyperthermia induced a 30–40% increase in Alexa-Albumin into the tumor micro-environment 24 h after treatment when compared to non-heat treated mice. Additionally, we showed that the RF method of delivering hyperthermia to tumors was more localized and uniform across the tumor mass when compared to other methods of heating. Lastly, we provided insight into some of the factors that influence the delivery of RF hyperthermia to tumors. PMID:28287120
Optimizing non-invasive radiofrequency hyperthermia treatment for improving drug delivery in 4T1 mouse breast cancer model.

PubMed

Ware, Matthew J; Krzykawska-Serda, Martyna; Chak-Shing Ho, Jason; Newton, Jared; Suki, Sarah; Law, Justin; Nguyen, Lam; Keshishian, Vazrik; Serda, Maciej; Taylor, Kimberly; Curley, Steven A; Corr, Stuart J

2017-03-13

Interactions of high-frequency radio waves (RF) with biological tissues are currently being investigated as a therapeutic platform for non-invasive cancer hyperthermia therapy. RF delivers thermal energy into tissues, which increases intra-tumoral drug perfusion and blood-flow. Herein, we describe an optical-based method to optimize the short-term treatment schedules of drug and hyperthermia administration in a 4T1 breast cancer model via RF, with the aim of maximizing drug localization and homogenous distribution within the tumor microenvironment. This method, based on the analysis of fluorescent dyes localized into the tumor, is more time, cost and resource efficient, when compared to current analytical methods for tumor-targeting drug analysis such as HPLC and LC-MS. Alexa-Albumin 647 nm fluorphore was chosen as a surrogate for nab-paclitaxel based on its similar molecular weight and albumin driven pharmacokinetics. We found that RF hyperthermia induced a 30-40% increase in Alexa-Albumin into the tumor micro-environment 24 h after treatment when compared to non-heat treated mice. Additionally, we showed that the RF method of delivering hyperthermia to tumors was more localized and uniform across the tumor mass when compared to other methods of heating. Lastly, we provided insight into some of the factors that influence the delivery of RF hyperthermia to tumors.
Optimizing non-invasive radiofrequency hyperthermia treatment for improving drug delivery in 4T1 mouse breast cancer model

NASA Astrophysics Data System (ADS)

Ware, Matthew J.; Krzykawska-Serda, Martyna; Chak-Shing Ho, Jason; Newton, Jared; Suki, Sarah; Law, Justin; Nguyen, Lam; Keshishian, Vazrik; Serda, Maciej; Taylor, Kimberly; Curley, Steven A.; Corr, Stuart J.

2017-03-01

Interactions of high-frequency radio waves (RF) with biological tissues are currently being investigated as a therapeutic platform for non-invasive cancer hyperthermia therapy. RF delivers thermal energy into tissues, which increases intra-tumoral drug perfusion and blood-flow. Herein, we describe an optical-based method to optimize the short-term treatment schedules of drug and hyperthermia administration in a 4T1 breast cancer model via RF, with the aim of maximizing drug localization and homogenous distribution within the tumor microenvironment. This method, based on the analysis of fluorescent dyes localized into the tumor, is more time, cost and resource efficient, when compared to current analytical methods for tumor-targeting drug analysis such as HPLC and LC-MS. Alexa-Albumin 647 nm fluorphore was chosen as a surrogate for nab-paclitaxel based on its similar molecular weight and albumin driven pharmacokinetics. We found that RF hyperthermia induced a 30-40% increase in Alexa-Albumin into the tumor micro-environment 24 h after treatment when compared to non-heat treated mice. Additionally, we showed that the RF method of delivering hyperthermia to tumors was more localized and uniform across the tumor mass when compared to other methods of heating. Lastly, we provided insight into some of the factors that influence the delivery of RF hyperthermia to tumors.
Parental Perceptions of Neighborhood Effects in Latino Comunas

PubMed Central

Horner, Pilar; Sanchez, Ninive; Castillo, Marcela; Delva, Jorge

2011-01-01

Objectives To obtain rich information about how adult Latinos living in high-poverty/high-drug use neighborhoods perceive and negotiate their environment. Methods In 2008, thirteen adult caregivers in Santiago, Chile were interviewed with open-ended questions to ascertain beliefs about neighborhood effects and drug use. Analysis Inductive analysis was used to develop the codebook/identify trends. Discussion Residents externalized their understanding of drug use and misuse by invoking the concept of delinquent youth. A typology of their perceptions is offered. Learning more about residents’ circumstances may help focus on needs-based interventions. More research with Latino neighborhoods is needed for culturally-competent models of interventions. PMID:22497879
Quality assessment of crude and processed Arecae semen based on colorimeter and HPLC combined with chemometrics methods.

PubMed

Sun, Meng; Yan, Donghui; Yang, Xiaolu; Xue, Xingyang; Zhou, Sujuan; Liang, Shengwang; Wang, Shumei; Meng, Jiang

2017-05-01

Raw Arecae Semen, the seed of Areca catechu L., as well as Arecae Semen Tostum and Arecae semen carbonisata are traditionally processed by stir-baking for subsequent use in a variety of clinical applications. These three Arecae semen types, important Chinese herbal drugs, have been used in China and other Asian countries for thousands of years. In this study, the sensory technologies of a colorimeter and sensitive validated high-performance liquid chromatography with diode array detection were employed to discriminate raw Arecae semen and its processed drugs. The color parameters of the samples were determined by a colorimeter instrument CR-410. Moreover, the fingerprints of the four alkaloids of arecaidine, guvacine, arecoline and guvacoline were surveyed by high-performance liquid chromatography. Subsequently, Student's t test, the analysis of variance, fingerprint similarity analysis, hierarchical cluster analysis, principal component analysis, factor analysis and Pearson's correlation test were performed for final data analysis. The results obtained demonstrated a significant color change characteristic for components in raw Arecae semen and its processed drugs. Crude and processed Arecae semen could be determined based on colorimetry and high-performance liquid chromatography with a diode array detector coupled with chemometrics methods for a comprehensive quality evaluation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Perhaps More Consideration of Pavlovian–Operant Interaction May Improve the Clinical Efficacy of Behaviorally Based Drug Treatment Programs

PubMed Central

Troisi, Joseph R.

2014-01-01

Drug abuse remains costly. Drug-related cues can evoke cue-reactivity and craving, contributing to relapse. The Pavlovian extinction-based cue-exposure therapy (CET) has not been very successful in treating drug abuse. A functional operant analysis of complex rituals involved in CET is outlined and reinterpreted as an operant heterogeneous chain maintained by observing responses, conditioned reinforcers, and discriminative stimuli. It is further noted that operant functions are not predicated on Pavlovian processes but can be influenced by them in contributing to relapse; several empirical studies from the animal and human literature highlight this view. Cue-reactivity evoked by Pavlovian processes is conceptualized as an operant establishing/motivating operation. CET may be more effective in incorporating an operant-based approach that takes into account the complexity of Pavlovian–operant interaction. Extinction of the operant chain coupled with the shaping of alternative behaviors is proposed as an integrated therapy. It is proposed that operant-based drug abuse treatments (contingency management, voucher programs, and the therapeutic work environment) might consider incorporating cue-reactivity, as establishing/motivating operations, to increase long-term success—a hybrid approach based on Pavlovian–operant interaction. PMID:25346551
Perhaps More Consideration of Pavlovian-Operant Interaction May Improve the Clinical Efficacy of Behaviorally Based Drug Treatment Programs.

PubMed

Troisi, Joseph R

2013-01-01

Drug abuse remains costly. Drug-related cues can evoke cue-reactivity and craving, contributing to relapse. The Pavlovian extinction-based cue-exposure therapy (CET) has not been very successful in treating drug abuse. A functional operant analysis of complex rituals involved in CET is outlined and reinterpreted as an operant heterogeneous chain maintained by observing responses, conditioned reinforcers, and discriminative stimuli. It is further noted that operant functions are not predicated on Pavlovian processes but can be influenced by them in contributing to relapse; several empirical studies from the animal and human literature highlight this view. Cue-reactivity evoked by Pavlovian processes is conceptualized as an operant establishing/motivating operation. CET may be more effective in incorporating an operant-based approach that takes into account the complexity of Pavlovian-operant interaction. Extinction of the operant chain coupled with the shaping of alternative behaviors is proposed as an integrated therapy. It is proposed that operant-based drug abuse treatments (contingency management, voucher programs, and the therapeutic work environment) might consider incorporating cue-reactivity, as establishing/motivating operations, to increase long-term success-a hybrid approach based on Pavlovian-operant interaction.
Antiviral Information Management System (AIMS): a prototype for operational innovation in drug development.

PubMed

Jadhav, Pravin R; Neal, Lauren; Florian, Jeff; Chen, Ying; Naeger, Lisa; Robertson, Sarah; Soon, Guoxing; Birnkrant, Debra

2010-09-01

This article presents a prototype for an operational innovation in knowledge management (KM). These operational innovations are geared toward managing knowledge efficiently and accessing all available information by embracing advances in bioinformatics and allied fields. The specific components of the proposed KM system are (1) a database to archive hepatitis C virus (HCV) treatment data in a structured format and retrieve information in a query-capable manner and (2) an automated analysis tool to inform trial design elements for HCV drug development. The proposed framework is intended to benefit drug development by increasing efficiency of dose selection and improving the consistency of advice from US Food and Drug Administration (FDA). It is also hoped that the framework will encourage collaboration among FDA, industry, and academic scientists to guide the HCV drug development process using model-based quantitative analysis techniques.
Functional analysis and transcriptional output of the Göttingen minipig genome.

PubMed

Heckel, Tobias; Schmucki, Roland; Berrera, Marco; Ringshandl, Stephan; Badi, Laura; Steiner, Guido; Ravon, Morgane; Küng, Erich; Kuhn, Bernd; Kratochwil, Nicole A; Schmitt, Georg; Kiialainen, Anna; Nowaczyk, Corinne; Daff, Hamina; Khan, Azinwi Phina; Lekolool, Isaac; Pelle, Roger; Okoth, Edward; Bishop, Richard; Daubenberger, Claudia; Ebeling, Martin; Certa, Ulrich

2015-11-14

In the past decade the Göttingen minipig has gained increasing recognition as animal model in pharmaceutical and safety research because it recapitulates many aspects of human physiology and metabolism. Genome-based comparison of drug targets together with quantitative tissue expression analysis allows rational prediction of pharmacology and cross-reactivity of human drugs in animal models thereby improving drug attrition which is an important challenge in the process of drug development. Here we present a new chromosome level based version of the Göttingen minipig genome together with a comparative transcriptional analysis of tissues with pharmaceutical relevance as basis for translational research. We relied on mapping and assembly of WGS (whole-genome-shotgun sequencing) derived reads to the reference genome of the Duroc pig and predict 19,228 human orthologous protein-coding genes. Genome-based prediction of the sequence of human drug targets enables the prediction of drug cross-reactivity based on conservation of binding sites. We further support the finding that the genome of Sus scrofa contains about ten-times less pseudogenized genes compared to other vertebrates. Among the functional human orthologs of these minipig pseudogenes we found HEPN1, a putative tumor suppressor gene. The genomes of Sus scrofa, the Tibetan boar, the African Bushpig, and the Warthog show sequence conservation of all inactivating HEPN1 mutations suggesting disruption before the evolutionary split of these pig species. We identify 133 Sus scrofa specific, conserved long non-coding RNAs (lncRNAs) in the minipig genome and show that these transcripts are highly conserved in the African pigs and the Tibetan boar suggesting functional significance. Using a new minipig specific microarray we show high conservation of gene expression signatures in 13 tissues with biomedical relevance between humans and adult minipigs. We underline this relationship for minipig and human liver where we could demonstrate similar expression levels for most phase I drug-metabolizing enzymes. Higher expression levels and metabolic activities were found for FMO1, AKR/CRs and for phase II drug metabolizing enzymes in minipig as compared to human. The variability of gene expression in equivalent human and minipig tissues is considerably higher in minipig organs, which is important for study design in case a human target belongs to this variable category in the minipig. The first analysis of gene expression in multiple tissues during development from young to adult shows that the majority of transcriptional programs are concluded four weeks after birth. This finding is in line with the advanced state of human postnatal organ development at comparative age categories and further supports the minipig as model for pediatric drug safety studies. Genome based assessment of sequence conservation combined with gene expression data in several tissues improves the translational value of the minipig for human drug development. The genome and gene expression data presented here are important resources for researchers using the minipig as model for biomedical research or commercial breeding. Potential impact of our data for comparative genomics, translational research, and experimental medicine are discussed.
A structure- and chemical genomics-based approach for repositioning of drugs against VCP/p97 ATPase.

PubMed

Segura-Cabrera, Aldo; Tripathi, Reshmi; Zhang, Xiaoyi; Gui, Lin; Chou, Tsui-Fen; Komurov, Kakajan

2017-03-21

Valosin-containing protein (VCP/p97) ATPase (a.k.a. Cdc48) is a key member of the ER-associated protein degradation (ERAD) pathway. ERAD and VCP/p97 have been implicated in a multitude of human diseases, such as neurodegenerative diseases and cancer. Inhibition of VCP/p97 induces proteotoxic ER stress and cell death in cancer cells, making it an attractive target for cancer treatment. However, no drugs exist against this protein in the market. Repositioning of drugs towards new indications is an attractive alternative to the de novo drug development due to the potential for significantly shorter time to clinical translation. Here, we employed an integrative strategy for the repositioning of drugs as novel inhibitors of the VCP/p97 ATPase. We integrated structure-based virtual screening with the chemical genomics analysis of drug molecular signatures, and identified several candidate inhibitors of VCP/p97 ATPase. Importantly, experimental validation with cell-based and in vitro ATPase assays confirmed three (ebastine, astemizole and clotrimazole) out of seven tested candidates (~40% true hit rate) as direct inhibitors of VCP/p97 and ERAD. This study introduces an effective integrative strategy for drug repositioning, and identified new drugs against the VCP/p97/ERAD pathway in human diseases.
Synthesis, characterization and in vitro cytotoxicity analysis of a novel cellulose based drug carrier for the controlled delivery of 5-fluorouracil, an anticancer drug

NASA Astrophysics Data System (ADS)

Anirudhan, Thayyath S.; Nima, Jayachandran; Divya, Peethambaran L.

2015-11-01

The present investigation concerns the development and evaluation of a novel drug delivery system, aminated-glycidylmethacrylate grafted cellulose-grafted polymethacrylic acid-succinyl cyclodextrin (Cell-g-(GMA/en)-PMA-SCD) for the controlled release of 5-Fluorouracil, an anticancer drug. The prepared drug carrier was characterized by FT-IR, XRD and SEM techniques. Binding kinetics and isotherm studies of 5-FU onto Cell-g-(GMA/en)-PMA-SCD were found to follow pseudo-second-order and Langmuir model respectively. Maximum binding capacity of drug carrier was found to be 149.09 mg g-1 at 37 °C. Swelling studies, in vitro release kinetics, drug loading efficiency and encapsulation efficiency of Cell-g-(GMA/en)-PMA-SCD were studied. The release kinetics was analyzed using Ritger-Peppas equation at pH 7.4. Cytotoxicity analysis on MCF-7 (human breast carcinoma) cells indicated that the drug carrier shows sustained and controlled release of drug to the target site. Hence, it is evident from this investigation that Cell-g-(GMA/en)-PMA-SCD could be a promising carrier for 5-FU.
CImbinator: a web-based tool for drug synergy analysis in small- and large-scale datasets.

PubMed

Flobak, Åsmund; Vazquez, Miguel; Lægreid, Astrid; Valencia, Alfonso

2017-08-01

Drug synergies are sought to identify combinations of drugs particularly beneficial. User-friendly software solutions that can assist analysis of large-scale datasets are required. CImbinator is a web-service that can aid in batch-wise and in-depth analyzes of data from small-scale and large-scale drug combination screens. CImbinator offers to quantify drug combination effects, using both the commonly employed median effect equation, as well as advanced experimental mathematical models describing dose response relationships. CImbinator is written in Ruby and R. It uses the R package drc for advanced drug response modeling. CImbinator is available at http://cimbinator.bioinfo.cnio.es , the source-code is open and available at https://github.com/Rbbt-Workflows/combination_index . A Docker image is also available at https://hub.docker.com/r/mikisvaz/rbbt-ci_mbinator/ . asmund.flobak@ntnu.no or miguel.vazquez@cnio.es. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Pharmacometrics in pregnancy: An unmet need.

PubMed

Ke, Alice Ban; Rostami-Hodjegan, Amin; Zhao, Ping; Unadkat, Jashvant D

2014-01-01

Pregnant women and their fetuses are orphan populations with respect to the safety and efficacy of drugs. Physiological and absorption, distribution, metabolism, and excretion (ADME) changes during pregnancy can significantly affect drug pharmacokinetics (PK) and may necessitate dose adjustment. Here, the specific aspects related to the design, execution, and analysis of clinical studies in pregnant women are discussed, underlining the unmet need for top-down pharmacometrics analyses and bottom-up modeling approaches. The modeling tools that support data analysis for the pregnancy population are reviewed, with a focus on physiologically based pharmacokinetics (PBPK) and population pharmacokinetics (POP-PK). By integrating physiological data, preclinical data, and clinical data (e.g., via POP-PK) to quantify anticipated changes in the PK of drugs during pregnancy, the PBPK approach allows extrapolation beyond the previously studied model drugs to other drugs with well-characterized ADME characteristics. Such a systems pharmacology approach can identify drugs whose PK may be altered during pregnancy, guide rational PK study design, and support dose adjustment for pregnant women.

Trends in Nanopharmaceutical Patents

PubMed Central

Antunes, Adelaide; Fierro, Iolanda; Guerrante, Rafaela; Mendes, Flavia; Alencar, Maria Simone de M.

2013-01-01

Investment in nanotechnology is now a given constant by governments, research centers and companies in both more developed countries and emerging markets. Due to their characteristics, such as high stability, ability to enable antigen identification on specific cells in the human body and controlling the release of drugs and, therefore, improving therapies, nanoparticles have been the subject of research and patent applications in the pharmaceutical field. According to the Organization for Economic Co-operation and Development (OCDE), patent data can be used as a source of information in order to measure science and technology activities. Thereby, this paper presents an analysis based on patent documents related to nanotechnology in the pharmaceutical sector. As a result, the analysis of patents demonstrate primarily that nanobiotechnology attracts high levels of R&D investments, including nanoparticle-based chemotherapeutic agents/drugs, monoclonal antibody nanoparticle complexes and their role in drug delivery or contrast agents with non-toxic effects. PMID:23535336
An airport cargo inspection system based on X-ray and thermal neutron analysis (TNA).

PubMed

Ipe, Nisy E; Akery, A; Ryge, P; Brown, D; Liu, F; Thieu, J; James, B

2005-01-01

A cargo inspection system incorporating a high-resolution X-ray imaging system with a material-specific detection system based on Ancore Corporation's patented thermal neutron analysis (TNA) technology can detect bulk quantities of explosives and drugs concealed in trucks or cargo containers. The TNA process utilises a 252Cf neutron source surrounded by a moderator. The neutron interactions with the inspected object result in strong and unique gamma-ray signals from nitrogen, which is a key ingredient in modern high explosives, and from chlorinated drugs. The TNA computer analyses the gamma-ray signals and automatically determines the presence of explosives or drugs. The radiation source terms and shielding design of the facility are described. For the X-ray generator, the primary beam, leakage radiation, and scattered primary and leakage radiation were considered. For the TNA, the primary neutrons and tunnel scattered neutrons as well as the neutron-capture gamma rays were considered.
Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes

NASA Astrophysics Data System (ADS)

Cleves, Ann E.; Jain, Ajay N.

2015-02-01

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.
Advances in the analysis of steroid hormone drugs in pharmaceuticals and environmental samples (2004-2010).

PubMed

Görög, Sándor

2011-06-25

A critical review of the literature of the analysis of steroid hormone drugs is presented based on 213 publications published between 2004 and 2010. The state of the art of the assay and purity check of bulk drug materials is characterized on the basis of the principal pharmacopoeias supplemented by the literature dealing with their impurity profiling and solid state characterization. The determination of the active ingredients and impurities/degradants in pharmaceutical formulation by HPLC, other chromatographic, electrodriven, spectrophotometric and other methods is also summarized. A short section deals with the application of analytical methods in drug research. The literature of the determination of steroid hormones in environmental samples is summarized in tabulated form. Copyright © 2010 Elsevier B.V. All rights reserved.
Treatment of challenging behavior exhibited by children with prenatal drug exposure.

PubMed

Kurtz, Patricia F; Chin, Michelle D; Rush, Karena S; Dixon, Dennis R

2008-01-01

A large body of literature exists describing the harmful effects of prenatal drug exposure on infant and child development. However, there is a paucity of research examining strategies to ameliorate sequelae such as externalizing behavior problems. In the present study, functional analysis procedures were used to assess challenging behavior exhibited by two children who were prenatally exposed to drugs of abuse. Results for both children indicated that challenging behavior was maintained by access to positive reinforcement (adult attention and tangible items). For one child, challenging behavior was also maintained by negative reinforcement (escape from activities of daily living). Function-based interventions were effective in reducing challenging behavior for both children. Implications for utilizing methods of applied behavior analysis in research with children with prenatal drug exposure are discussed.
A literature review and meta-analysis of drug company-funded mental health websites.

PubMed

Read, J; Cain, A

2013-12-01

The pharmaceutical industry exercises pervasive influence in the mental health field. The internet has become a primary source of mental health information for the public and practitioners. This study therefore compared mental health websites funded and not funded by drug companies. A systematic literature review of studies examining the role of drug companies in the funding of mental health websites was conducted, followed by a meta-analysis of studies comparing drug company-funded (DCF) sites with sites not funded by the industry. Mental health websites, in general, overemphasize biogenetic causal explanations and medication. Many mental health websites (42%) are either drug company owned (6%) or receive funding from drug companies (36%). A meta-analysis found that DCF sites are significantly more biased toward biogenetic causes (P < 0.01) and toward medication (P < 0.0001) than sites that are financially independent of the industry. Practitioners are encouraged to inform patients about the bias inherent in industry-sponsored websites and to recommend, instead, more balanced websites that present a range of evidence-based information about causes and treatments. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
National reimbursement listing determinants of new cancer drugs: a retrospective analysis of 58 cancer treatment appraisals in 2007-2016 in South Korea.

PubMed

Kim, Eun-Sook; Kim, Jung-Ae; Lee, Eui-Kyung

2017-08-01

Since the positive-list system was introduced, concerns have been raised over restricting access to new cancer drugs in Korea. Policy changes in the decision-making process, such as risk-sharing agreement and the waiver of pharmacoeconomic data submission, were implemented to improve access to oncology medicines, and other factors are also involved in the reimbursement for cancer drugs. The aim of this study is to investigate the reimbursement listing determinants of new cancer drugs in Korea. All cancer treatment appraisals of Health Insurance Review and Assessment during 2007-2016 were analyzed based on 13 independent variables (comparative effectiveness, cost-effectiveness, drug-price comparison, oncology-specific policy, and innovation such as new mode of action). Univariate and multivariate logistic analyses were conducted. Of 58 analyzed submissions, 40% were listed in the national reimbursement formulary. In univariate analysis, four variables were related to listing: comparative effectiveness, drug-price comparison, new mode of action, and risk-sharing agreement. In multivariate logistic analysis, three variables significantly increased the likelihood of listing: clinical improvement, below alternative's price, and risk-sharing arrangement. Cancer drug's listing increased from 17% to 47% after risk-sharing agreement implementation. Clinical improvement, cost-effectiveness, and RSA application are critical to successful national reimbursement listing.
Micellar electrokinetic capillary chromatographic method for the quantitative analysis of uricosuric and antigout drugs in pharmaceutical preparations.

PubMed

Kou, Hwang-Shang; Lin, Tsai-Pei; Chung, Tang-Chia; Wu, Hsin-Lung

2006-06-01

A simple MEKC method is described for the separation and quantification of seven widely used uricosuric and antigout drugs, including allopurinol (AP), benzbromarone (BZB), colchicine (COL), orotic acid (OA), oxypurinol (OP), probenecid (PB), and sulfinpyrazone (SPZ). The drugs were separated in a BGE of borate buffer (45 mM; pH 9.00) with SDS (20 mM) as the micellar source and the separated drugs were directly monitored with a UV detector (214 nm). Several parameters affecting the separation and analysis of the drugs were studied. Based on the normalized peak-area ratios of the drugs to an internal standard versus the concentration of the drugs, the method is applicable to quantify BZB, COL, and SPZ (each 5-200 microM), AP, OA, OP, and PB (each 10-200 microM) with detection limits (S/N = 3, 0.5 psi, 5 s injection) in the range of 0.6-4.0 microM. The precision (RSD; n = 5) and accuracy (relative error; n = 5) of the method for intraday and interday analyses of the analytes at three levels (30, 120, and 180 microM) are below 4% (n = 3). The method was demonstrated to be suitable for the analysis of AP and COL in commercial tablets with speed and simplicity.
Acute Pancreatitis and Use of Pancreatitis-Associated Drugs: A 10-Year Population-Based Cohort Study.

PubMed

Bertilsson, Sara; Kalaitzakis, Evangelos

2015-10-01

To assess the use of acute pancreatitis (AP)-associated drugs in patients with AP, the relation between sales of these drugs and the incidence of AP, and the potential impact on AP severity and recurrence. All patients with incident AP between 2003 and 2012, in a well-defined area, were retrospectively identified. Data regarding AP etiology, severity, and recurrence and use of AP-associated drugs were extracted from medical records. Drugs were classified according to an evidence-based classification system. Annual drug sales data were obtained from the Swedish drug administration service. Overall, 1457 cases of incident AP were identified. Acute pancreatitis-associated drug users increased from 32% in 2003 to 51% in 2012, reflecting increasing user rates in the general population. The incidence of AP increased during the study period but was not related to AP-associated drug user rates (P > 0.05). Recurrent AP occurred in 23% but was unrelated to AP-associated drug use (P > 0.05). In logistic regression analysis, after adjustment for comorbidity, AP-associated drug use was not related to AP severity (P > 0.05). Use of AP-associated drugs is increasingly frequent in patients with AP. However, it does not have any major impact on the observed epidemiological changes in occurrence, severity, or recurrence of AP.
Need for multicriteria evaluation of generic drug policies.

PubMed

Kaló, Zoltán; Holtorf, Anke-Peggy; Alfonso-Cristancho, Rafael; Shen, Jie; Ágh, Tamás; Inotai, András; Brixner, Diana

2015-03-01

Policymakers tend to focus on improving patented drug policies because they are under pressure from patients, physicians, and manufacturers to increase access to novel therapies. The success of pharmaceutical innovation over the last few decades has led to the availability of many off-patent drugs to treat disease areas with the greatest public health need. Therefore, the success of public health programs in improving the health status of the total population is highly dependent on the efficiency of generic drug policies. The objective of this article was to explore factors influencing the true efficiency of generic prescription drug policies in supporting public health initiatives in the developed world. Health care decision makers often assess the efficiency of generic drug policies by the level of price erosion and market share of generics. Drug quality, bioequivalence, in some cases drug formulations, supply reliability, medical adherence and persistence, health outcomes, and nondrug costs, however, are also attributes of success for generic drug policies. Further methodological research is needed to measure and improve the efficiency of generic drug policies. This also requires extension of the evidence base of the impact of generic drugs, partly based on real-world evidence. Multicriteria decision analysis may assist policymakers and researchers to evaluate the true value of generic drugs. Copyright © 2015. Published by Elsevier Inc.
Development of a Soluplus budesonide freeze-dried powder for nasal drug delivery.

PubMed

Pozzoli, Michele; Traini, Daniela; Young, Paul M; Sukkar, Maria B; Sonvico, Fabio

2017-09-01

The aim of this work was to develop an amorphous solid dispersions/solutions (ASD) of a poorly soluble drug, budesonide (BUD) with a novel polymer Soluplus ® (BASF, Germany) using a freeze-drying technique, in order to improve dissolution and absorption through the nasal route. The small volume of fluid present in the nasal cavity limits the absorption of a poorly soluble drug. Budesonide is a corticosteroid, practically insoluble and normally administered as a suspension-based nasal spray. The formulation was prepared through freeze-drying of polymer-drug solution. The formulation was assessed for its physicochemical (specific surface area, calorimetric analysis and X-ray powder diffraction), release properties and aerodynamic properties as well as transport in vitro using RPMI 2650 nasal cells, in order to elucidate the efficacy of the Soluplus-BUD formulation. The freeze-dried Soluplus-BUD formulation (LYO) showed a porous structure with a specific surface area of 1.4334 ± 0.0178 m 2 /g. The calorimetric analysis confirmed an interaction between BUD and Soluplus and X-ray powder diffraction the amorphous status of the drug. The freeze-dried formulation (LYO) showed faster release compared to both water-based suspension and dry powder commercial products. Furthermore, a LYO formulation, bulked with calcium carbonate (LYO-Ca), showed suitable aerodynamic characteristics for nasal drug delivery. The permeation across RPMI 2650 nasal cell model was higher compared to a commercial water-based BUD suspension. Soluplus has been shown to be a promising polymer for the formulation of BUD amorphous solid suspension/solution. This opens up opportunities to develop new formulations of poorly soluble drug for nasal delivery.
Paclitaxel Drug-Eluting Stents in Peripheral Arterial Disease: A Health Technology Assessment

PubMed Central

2015-01-01

Background Peripheral arterial disease is a condition in which atherosclerotic plaques partially or completely block blood flow to the legs. Although percutaneous transluminal angioplasty and metallic stenting have high immediate success rates in treating peripheral arterial disease, long-term patency and restenosis rates in long and complex lesions remain unsatisfactory. Objective The objective of this analysis was to evaluate the clinical effectiveness, safety, cost-effectiveness and budget impact of Zilver paclitaxel self-expanding drug-eluting stents for the treatment of de novo or restenotic lesions in above-the-knee peripheral arterial disease. Data Sources Literature searches were performed using Ovid MEDLINE, Ovid MEDLINE In-Process and Other Non-Indexed Citations, Ovid Embase, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), and EBM Reviews. For the economic review, a search filter was applied to limit search results to economics-related literature. Data sources for the budget impact analysis included expert opinion, published literature, and Ontario administrative data. Review Methods Systematic reviews, meta-analyses, randomized controlled trials, and observational studies were included in the clinical effectiveness review, and full economic evaluations were included in the economic literature review. Studies were included if they examined the effect of Zilver paclitaxel drug-eluting stents in de novo or restenotic lesions in above-the-knee arteries. For the budget impact analysis, 3 scenarios were constructed based on different assumptions. Results One randomized controlled trial reported a significantly higher patency rate with Zilver paclitaxel drug-eluting stents for lesions ≤ 14 cm than with angioplasty or bare metal stents. One observational study showed no difference in patency rates between Zilver paclitaxel drug-eluting stents and paclitaxel drug-coated balloons. Zilver paclitaxel drug-eluting stents were associated with a significantly higher event-free survival rate than angioplasty, but the event-free survival rate was similar for Zilver paclitaxel drug-eluting stents and paclitaxel drug-coated balloons. No economic evaluations compared Zilver paclitaxel drug-eluting stents with bare metal stents or angioplasty for peripheral arterial disease. A budget impact analysis showed that the cost savings associated with funding of Zilver paclitaxel drug-eluting stents would be $470,000 to $640,000 per year, assuming that the use of the Zilver paclitaxel drug-eluting stent was associated with a lower risk of subsequent revascularization. Conclusions Based on evidence of low to moderate quality, Zilver paclitaxel drug-eluting stents were associated with a higher patency rate than angioplasty or bare metal stents, and with fewer adverse events than angioplasty. The effectiveness and safety of Zilver paclitaxel drug-eluting stents and paclitaxel drug-coated balloons were similar. PMID:26719778
Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets.

PubMed

Maciejewski, Mateusz; Lounkine, Eugen; Whitebread, Steven; Farmer, Pierre; DuMouchel, William; Shoichet, Brian K; Urban, Laszlo

2017-08-08

The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events. Our analysis exposed key idiosyncrasies in FAERS, for example reports of thalidomide causing a deadly ADR when used against myeloma, a likely result of the disease itself; multiplications of the same report, unjustifiably increasing its importance; correlation of reported ADRs with public events, regulatory announcements, and with publications. Comparing the pharmacological, pharmacokinetic, and clinical ADR profiles of methylphenidate, aripiprazole, and risperidone, and of kinase drugs targeting the VEGF receptor, demonstrates how underlying molecular mechanisms can emerge from ADR co-analysis. The precautions and methods we describe may enable investigators to avoid confounding chemistry-based associations and reporting biases in FAERS, and illustrate how comparative analysis of ADRs can reveal underlying mechanisms.
Discovery and characterization of antibody variants using mass spectrometry-based comparative analysis for biosimilar candidates of monoclonal antibody drugs.

PubMed

Li, Wenhua; Yang, Bin; Zhou, Dongmei; Xu, Jun; Ke, Zhi; Suen, Wen-Chen

2016-07-01

Liquid chromatography mass spectrometry (LC-MS) is the most commonly used technique for the characterization of antibody variants. MAb-X and mAb-Y are two approved IgG1 subtype monoclonal antibody drugs recombinantly produced in Chinese hamster ovary (CHO) cells. We report here that two unexpected and rare antibody variants have been discovered during cell culture process development of biosimilars for these two approved drugs through intact mass analysis. We then used comprehensive mass spectrometry-based comparative analysis including reduced light, heavy chains, and domain-specific mass as well as peptide mapping analysis to fully characterize the observed antibody variants. The "middle-up" mass comparative analysis demonstrated that the antibody variant from mAb-X biosimilar candidate was caused by mass variation of antibody crystalline fragment (Fc), whereas a different variant with mass variation in antibody antigen-binding fragment (Fab) from mAb-Y biosimilar candidate was identified. Endoproteinase Lys-C digested peptide mapping and tandem mass spectrometry analysis further revealed that a leucine to glutamine change in N-terminal 402 site of heavy chain was responsible for the generation of mAb-X antibody variant. Lys-C and trypsin coupled non-reduced and reduced peptide mapping comparative analysis showed that the formation of the light-heavy interchain trisulfide bond resulted in the mAb-Y antibody variant. These two cases confirmed that mass spectrometry-based comparative analysis plays a critical role for the characterization of monoclonal antibody variants, and biosimilar developers should start with a comprehensive structural assessment and comparative analysis to decrease the risk of the process development for biosimilars. Copyright © 2016 Elsevier B.V. All rights reserved.
Organizational adoption of preemployment drug testing.

PubMed

Spell, C S; Blum, T C

2001-04-01

This study explored the adoption of preemployment drug testing by 360 organizations. Survival models were developed that included internal organizational and labor market factors hypothesized to affect the likelihood of adoption of drug testing. Also considered was another set of variables that included social and political variables based on institutional theory. An event history analysis using Cox regressions indicated that both internal organizational and environmental variables predicted adoption of drug testing. Results indicate that the higher the proportion of drug testers in the worksite's industry, the more likely it would be to adopt drug testing. Also, the extent to which an organization uses an internal labor market, voluntary turnover rate, and the extent to which management perceives drugs to be a problem were related to likelihood of adoption of drug testing.
PREDOSE: A Semantic Web Platform for Drug Abuse Epidemiology using Social Media

PubMed Central

Cameron, Delroy; Smith, Gary A.; Daniulaityte, Raminta; Sheth, Amit P.; Dave, Drashti; Chen, Lu; Anand, Gaurish; Carlson, Robert; Watkins, Kera Z.; Falck, Russel

2013-01-01

Objectives The role of social media in biomedical knowledge mining, including clinical, medical and healthcare informatics, prescription drug abuse epidemiology and drug pharmacology, has become increasingly significant in recent years. Social media offers opportunities for people to share opinions and experiences freely in online communities, which may contribute information beyond the knowledge of domain professionals. This paper describes the development of a novel Semantic Web platform called PREDOSE (PREscription Drug abuse Online Surveillance and Epidemiology), which is designed to facilitate the epidemiologic study of prescription (and related) drug abuse practices using social media. PREDOSE uses web forum posts and domain knowledge, modeled in a manually created Drug Abuse Ontology (DAO) (pronounced dow), to facilitate the extraction of semantic information from User Generated Content (UGC). A combination of lexical, pattern-based and semantics-based techniques is used together with the domain knowledge to extract fine-grained semantic information from UGC. In a previous study, PREDOSE was used to obtain the datasets from which new knowledge in drug abuse research was derived. Here, we report on various platform enhancements, including an updated DAO, new components for relationship and triple extraction, and tools for content analysis, trend detection and emerging patterns exploration, which enhance the capabilities of the PREDOSE platform. Given these enhancements, PREDOSE is now more equipped to impact drug abuse research by alleviating traditional labor-intensive content analysis tasks. Methods Using custom web crawlers that scrape UGC from publicly available web forums, PREDOSE first automates the collection of web-based social media content for subsequent semantic annotation. The annotation scheme is modeled in the DAO, and includes domain specific knowledge such as prescription (and related) drugs, methods of preparation, side effects, routes of administration, etc. The DAO is also used to help recognize three types of data, namely: 1) entities, 2) relationships and 3) triples. PREDOSE then uses a combination of lexical and semantic-based techniques to extract entities and relationships from the scraped content, and a top-down approach for triple extraction that uses patterns expressed in the DAO. In addition, PREDOSE uses publicly available lexicons to identify initial sentiment expressions in text, and then a probabilistic optimization algorithm (from related research) to extract the final sentiment expressions. Together, these techniques enable the capture of fine-grained semantic information from UGC, and querying, search, trend analysis and overall content analysis of social media related to prescription drug abuse. Moreover, extracted data are also made available to domain experts for the creation of training and test sets for use in evaluation and refinements in information extraction techniques. Results A recent evaluation of the information extraction techniques applied in the PREDOSE platform indicates 85% precision and 72% recall in entity identification, on a manually created gold standard dataset. In another study, PREDOSE achieved 36% precision in relationship identification and 33% precision in triple extraction, through manual evaluation by domain experts. Given the complexity of the relationship and triple extraction tasks and the abstruse nature of social media texts, we interpret these as favorable initial results. Extracted semantic information is currently in use in an online discovery support system, by prescription drug abuse researchers at the Center for Interventions, Treatment and Addictions Research (CITAR) at Wright State University. Conclusion A comprehensive platform for entity, relationship, triple and sentiment extraction from such abstruse texts has never been developed for drug abuse research. PREDOSE has already demonstrated the importance of mining social media by providing data from which new findings in drug abuse research were uncovered. Given the recent platform enhancements, including the refined DAO, components for relationship and triple extraction, and tools for content, trend and emerging pattern analysis, it is expected that PREDOSE will play a significant role in advancing drug abuse epidemiology in future. PMID:23892295
PREDOSE: a semantic web platform for drug abuse epidemiology using social media.

PubMed

Cameron, Delroy; Smith, Gary A; Daniulaityte, Raminta; Sheth, Amit P; Dave, Drashti; Chen, Lu; Anand, Gaurish; Carlson, Robert; Watkins, Kera Z; Falck, Russel

2013-12-01

The role of social media in biomedical knowledge mining, including clinical, medical and healthcare informatics, prescription drug abuse epidemiology and drug pharmacology, has become increasingly significant in recent years. Social media offers opportunities for people to share opinions and experiences freely in online communities, which may contribute information beyond the knowledge of domain professionals. This paper describes the development of a novel semantic web platform called PREDOSE (PREscription Drug abuse Online Surveillance and Epidemiology), which is designed to facilitate the epidemiologic study of prescription (and related) drug abuse practices using social media. PREDOSE uses web forum posts and domain knowledge, modeled in a manually created Drug Abuse Ontology (DAO--pronounced dow), to facilitate the extraction of semantic information from User Generated Content (UGC), through combination of lexical, pattern-based and semantics-based techniques. In a previous study, PREDOSE was used to obtain the datasets from which new knowledge in drug abuse research was derived. Here, we report on various platform enhancements, including an updated DAO, new components for relationship and triple extraction, and tools for content analysis, trend detection and emerging patterns exploration, which enhance the capabilities of the PREDOSE platform. Given these enhancements, PREDOSE is now more equipped to impact drug abuse research by alleviating traditional labor-intensive content analysis tasks. Using custom web crawlers that scrape UGC from publicly available web forums, PREDOSE first automates the collection of web-based social media content for subsequent semantic annotation. The annotation scheme is modeled in the DAO, and includes domain specific knowledge such as prescription (and related) drugs, methods of preparation, side effects, and routes of administration. The DAO is also used to help recognize three types of data, namely: (1) entities, (2) relationships and (3) triples. PREDOSE then uses a combination of lexical and semantic-based techniques to extract entities and relationships from the scraped content, and a top-down approach for triple extraction that uses patterns expressed in the DAO. In addition, PREDOSE uses publicly available lexicons to identify initial sentiment expressions in text, and then a probabilistic optimization algorithm (from related research) to extract the final sentiment expressions. Together, these techniques enable the capture of fine-grained semantic information, which facilitate search, trend analysis and overall content analysis using social media on prescription drug abuse. Moreover, extracted data are also made available to domain experts for the creation of training and test sets for use in evaluation and refinements in information extraction techniques. A recent evaluation of the information extraction techniques applied in the PREDOSE platform indicates 85% precision and 72% recall in entity identification, on a manually created gold standard dataset. In another study, PREDOSE achieved 36% precision in relationship identification and 33% precision in triple extraction, through manual evaluation by domain experts. Given the complexity of the relationship and triple extraction tasks and the abstruse nature of social media texts, we interpret these as favorable initial results. Extracted semantic information is currently in use in an online discovery support system, by prescription drug abuse researchers at the Center for Interventions, Treatment and Addictions Research (CITAR) at Wright State University. A comprehensive platform for entity, relationship, triple and sentiment extraction from such abstruse texts has never been developed for drug abuse research. PREDOSE has already demonstrated the importance of mining social media by providing data from which new findings in drug abuse research were uncovered. Given the recent platform enhancements, including the refined DAO, components for relationship and triple extraction, and tools for content, trend and emerging pattern analysis, it is expected that PREDOSE will play a significant role in advancing drug abuse epidemiology in future. Copyright © 2013 Elsevier Inc. All rights reserved.
Novel nanocarriers for topical drug delivery: investigating delivery efficiency and distribution in skin using two-photon microscopy

NASA Astrophysics Data System (ADS)

Kirejev, Vladimir; Guldbrand, Stina; Bauer, Brigitte; Smedh, Maria; Ericson, Marica B.

2011-03-01

The complex structure of skin represents an effective barrier against external environmental factors, as for example, different chemical and biochemical compounds, yeast, bacterial and viral infections. However, this impermeability prevents efficient transdermal drug delivery which limits the number of drugs that are able to penetrate the skin efficiently. Current trends in drug application through skin focus on the design and use of nanocarriers for transport of active compounds. The transport systems applied so far have several drawbacks, as they often have low payload, high toxicity, a limited variability of inclusion molecules, or long degradation times. The aim of these current studies is to investigate novel topical drug delivery systems, e.g. nanocarriers based on cyclic oligosaccharides - cyclodextrins (CD) or iron (III)-based metal-organic frameworks (MOF). Earlier studies on cell cultures imply that these drug nanocarriers show promising characteristics compared to other drug delivery systems. In our studies, we use two-photon microscopy to investigate the ability of the nanocarriers to deliver compounds through ex-vivo skin samples. Using near infrared light for excitation in the so called optical window of skin allows deep-tissue visualization of drug distribution and localization. In addition, it is possible to employ two-photon based fluorescence correlation spectroscopy for quantitative analysis of drug distribution and concentrations in different cell layers.
The Public Sector: A National Resource for Alcohol and Drug Treatment.

ERIC Educational Resources Information Center

de Miranda, John

Economic analysis of alcohol and drug treatment services usually focuses on understanding the private, profit-oriented, hospital-based setting. Professional publications of the alcoholism treatment field, as well as popular press and electronic media exposure, also focus heavily on the private system. Low cost, quality treatment services, however,…
Alcohol and drug use in early adolescence.

PubMed

Hotton, Tina; Haans, Dave

2004-05-01

This analysis presents the prevalence of substance use among young adolescents. The extent to which factors such as peer behaviour, parenting practices and school commitment and achievement are associated with drinking to intoxication and other drug use is investigated. The data are from the 1998/99 National Longitudinal Survey of Children and Youth. Analysis is based on a cross-sectional file from 4,296 respondents aged 12 to 15. Prevalence estimates for alcohol and drug use were calculated by sex. Logistic regression models were fitted to estimate the odds of drinking to intoxication and drug use, adjusted for socio-demographic factors, peer and parent substance use, parenting practices, school commitment/attachment, emotional health and religious attendance. In general, drinking to intoxication and drug use were more common among 14- and 15-year-olds than among 12- and 13-year-olds. The odds of drinking to intoxication and drug use were highest among adolescents whose friends used alcohol or drugs or were often in trouble, who reported low commitment to school, or whose parents had a hostile and ineffective parenting style.

Scientific white paper on concentration-QTc modeling.

PubMed

Garnett, Christine; Bonate, Peter L; Dang, Qianyu; Ferber, Georg; Huang, Dalong; Liu, Jiang; Mehrotra, Devan; Riley, Steve; Sager, Philip; Tornoe, Christoffer; Wang, Yaning

2018-06-01

The International Council for Harmonisation revised the E14 guideline through the questions and answers process to allow concentration-QTc (C-QTc) modeling to be used as the primary analysis for assessing the QTc interval prolongation risk of new drugs. A well-designed and conducted QTc assessment based on C-QTc modeling in early phase 1 studies can be an alternative approach to a thorough QT study for some drugs to reliably exclude clinically relevant QTc effects. This white paper provides recommendations on how to plan and conduct a definitive QTc assessment of a drug using C-QTc modeling in early phase clinical pharmacology and thorough QT studies. Topics included are: important study design features in a phase 1 study; modeling objectives and approach; exploratory plots; the pre-specified linear mixed effects model; general principles for model development and evaluation; and expectations for modeling analysis plans and reports. The recommendations are based on current best modeling practices, scientific literature and personal experiences of the authors. These recommendations are expected to evolve as their implementation during drug development provides additional data and with advances in analytical methodology.
Acute radiation sickness amelioration analysis. Technical report, 20 July 1990-19 July 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, S.I.; Feister, A.J.; Bareis, D.L.

1994-05-01

Three tasks were conducted under the Acute Radiation Sickness Amelioration Analysis in support of the Defense Nuclear Agency (DNA) and NATO Army Armaments Group (NAAG) Project Group 29 (PG-29) on drugs for the prevention of radiation-induced nausea and vomiting: (1) documents were collected and entered into a data base, (2) data reviews and analyses were performed, and (3) PG-29 and Triservice meetings involving anti-emetic drug development were supported and documented. Approximately 2000 documents were collected, with 1424 complete bibliographic citations entered into a WordPerfect 5.1 data base. Eight reviews and analyses addressing different aspects of the safety and efficacy ofmore » the candidate anti-emetic drugs ondansetron and granistron were prepared. Support was provided for seven international PG-29 meetings and two U.S. Triservice meetings in which the efforts of PG-29 were discussed. These tasks have enabled the DNA and PG-29 to make good progress toward the goal of recommending a serotonin type-3 (5-HT3) receptor antagonist anti-emetic drug for use in military personnel.« less
[Analysis of clinical use of Danhong injection based on hospital information system].

PubMed

Chen, Qian; Yi, Danhui; Xie, Yanming; Yang, Wei; Yang, Wei; Zhuang, Yan; Du, Jing

2011-10-01

To know how Danhong injection is used in clinical practice and to provide a reference for guiding clinical use of Danhong Injection. Extract Danhong injection's post-marketing re-evaluation data from the Hospital Information System of ten three grade III-A General Hospitals in Beijing, use basic statistical analysis methods to analyze Danhong injection's indications, usage and dosage, days of treatment etc. in clinical practice. In patients using Danhong injection, there were more than 60 percent patients were prescribed based on main-diagnosis, first-visit and other diagnosis, which were also coincided with Danhong injection's instruction. In clinical practice, 95.5 percent of Danhong injection's administration routes conformed to the instruction and more than 90 percent of Danhong injection's dosage were within the limits prescribed by the instruction. Danhong injection was used less than 20 days successively. Danhong injection was used in combination with drugs with the action of removing blood stasis, antianginal drug, antiplatelet drug, drugs for cerebrovascular disease and so on. Danhong injection has been used according to instruction in practice almostly.
Drug supply indicators: Pitfalls and possibilities for improvements to assist comparative analysis.

PubMed

Singleton, Nicola; Cunningham, Andrew; Groshkova, Teodora; Royuela, Luis; Sedefov, Roumen

2018-06-01

Interventions to tackle the supply of drugs are seen as standard components of illicit drug policies. Therefore drug market-related administrative data, such as seizures, price, purity and drug-related offending, are used in most countries for policy monitoring and assessment of the drug situation. International agencies, such as the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) and the UN Office of Drugs and Crime, also monitor and report on the drug situation cross-nationally and therefore seek to collect and make available key data in a uniform manner from the countries they cover. However, these data are not primarily collected for this purpose, which makes interpretation and comparative analysis difficult. Examples of limitations of these data sources include: the extent to which they reflect operational priorities rather than market changes; question marks over the robustness of and consistency in data collection methods, and issues around the timeliness of data availability. Such problems are compounded by cultural, social and contextual differences between countries. Making sense of such data is therefore challenging and extreme care needs to be taken using it. Nevertheless, these data provide an important window on a hidden area, so improving the quality of the data collected and expanding its scope should be a priority for those seeking to understand or monitor drug markets and supply reduction. In addition to highlighting some of the potential pitfalls in using supply indicators for comparative analysis, this paper presents a selection of options for improvements based on the current EMCDDA programme of work to improve their supply-related monitoring and analysis. The conceptual framework developed to steer this work may have wider application. Adopting this approach has the potential to provide a richer picture of drug markets, at both national and international levels, and make it easier to compare data between countries. Copyright © 2018 Elsevier B.V. All rights reserved.
Entrapment of alpha1-acid glycoprotein in high-performance affinity columns for drug-protein binding studies.

PubMed

Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S

2016-05-15

A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (±0.5)×10(5)M(-1), which agreed with a previously reported value of 1.0 (±0.1)×10(5)M(-1). Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. Copyright © 2015 Elsevier B.V. All rights reserved.
Entrapment of Alpha1-Acid Glycoprotein in High-Performance Affinity Columns for Drug-Protein Binding Studies

PubMed Central

Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S.

2015-01-01

A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (± 0.5) × 105 M−1, which agreed with a previously reported value of 1.0 (± 0.1) × 105 M−1. Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. PMID:26627938
Delivery of drugs to intracellular organelles using drug delivery systems: Analysis of research trends and targeting efficiencies.

PubMed

Maity, Amit Ranjan; Stepensky, David

2015-12-30

Targeting of drug delivery systems (DDSs) to specific intracellular organelles (i.e., subcellular targeting) has been investigated in numerous publications, but targeting efficiency of these systems is seldom reported. We searched scientific publications in the subcellular DDS targeting field and analyzed targeting efficiency and major formulation parameters that affect it. We identified 77 scientific publications that matched the search criteria. In the majority of these studies nanoparticle-based DDSs were applied, while liposomes, quantum dots and conjugates were used less frequently. The nucleus was the most common intracellular target, followed by mitochondrion, endoplasmic reticulum and Golgi apparatus. In 65% of the publications, DDSs surface was decorated with specific targeting residues, but the efficiency of this surface decoration was not analyzed in predominant majority of the studies. Moreover, only 23% of the analyzed publications contained quantitative data on DDSs subcellular targeting efficiency, while the majority of publications reported qualitative results only. From the analysis of publications in the subcellular targeting field, it appears that insufficient efforts are devoted to quantitative analysis of the major formulation parameters and of the DDSs' intracellular fate. Based on these findings, we provide recommendations for future studies in the field of organelle-specific drug delivery and targeting. Copyright © 2015 Elsevier B.V. All rights reserved.
Identification of new benzamide inhibitor against α-subunit of tryptophan synthase from Mycobacterium tuberculosis through structure-based virtual screening, anti-tuberculosis activity and molecular dynamics simulations.

PubMed

Naz, Sadia; Farooq, Umar; Ali, Sajid; Sarwar, Rizwana; Khan, Sara; Abagyan, Ruben

2018-03-13

Multi-drug-resistant tuberculosis and extensively drug-resistant tuberculosis has emerged as global health threat, causing millions of deaths worldwide. Identification of new drug candidates for tuberculosis (TB) by targeting novel and less explored protein targets will be invaluable for antituberculosis drug discovery. We performed structure-based virtual screening of eMolecules database against a homology model of relatively unexplored protein target: the α-subunit of tryptophan synthase (α-TRPS) from Mycobacterium tuberculosis essential for bacterial survival. Based on physiochemical properties analysis and molecular docking, the seven candidate compounds were selected and evaluated through whole cell-based activity against the H37Rv strain of M. tuberculosis. A new Benzamide inhibitor against α-subunit of tryptophan synthase (α-TRPS) from M. tuberculosis has been identified causing 100% growth inhibition at 25 μg/ml and visible bactericidal activity at 6 μg/ml. This benzamide inhibitor displayed a good predicted binding score (-48.24 kcal/mol) with the α-TRPS binding pocket and has logP value (2.95) comparable to Rifampicin. Further refinement of docking results and evaluation of inhibitor-protein complex stability were investigated through Molecular dynamic (MD) simulations studies. Following MD simulations, Root mean square deviation, Root mean square fluctuation and secondary structure analysis confirmed that protein did not unfold and ligand stayed inside the active pocket of protein during the explored time scale. This identified benzamide inhibitor against the α-subunit of TRPS from M. tuberculosis could be considered as candidate for drug discovery against TB and will be further evaluated for enzyme-based inhibition in future studies.
Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

PubMed

Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki

2017-01-01

The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.
ADME-Space: a new tool for medicinal chemists to explore ADME properties.

PubMed

Bocci, Giovanni; Carosati, Emanuele; Vayer, Philippe; Arrault, Alban; Lozano, Sylvain; Cruciani, Gabriele

2017-07-25

We introduce a new chemical space for drugs and drug-like molecules, exclusively based on their in silico ADME behaviour. This ADME-Space is based on self-organizing map (SOM) applied to 26,000 molecules. Twenty accurate QSPR models, describing important ADME properties, were developed and, successively, used as new molecular descriptors not related to molecular structure. Applications include permeability, active transport, metabolism and bioavailability studies, but the method can be even used to discuss drug-drug interactions (DDIs) or it can be extended to additional ADME properties. Thus, the ADME-Space opens a new framework for the multi-parametric data analysis in drug discovery where all ADME behaviours of molecules are condensed in one map: it allows medicinal chemists to simultaneously monitor several ADME properties, to rapidly select optimal ADME profiles, retrieve warning on potential ADME problems and DDIs or select proper in vitro experiments.
Probabilistic modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less
HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening.

PubMed

Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying

2013-01-01

High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable MatLab project at http://iclab.life.nctu.edu.tw/HCS-Neurons. Few automatic methods focus on analyzing multi-neuron images collected from HCS used in drug discovery. We provided an automatic HCS-based method for generating accurate classifiers to classify neurons based on their phenotypic changes upon drug treatments. The proposed HCS-neurons method is helpful in identifying and classifying chemical or biological molecules that alter the morphology of a group of neurons in HCS.
Using phase II data for the analysis of phase III studies: An application in rare diseases.

PubMed

Wandel, Simon; Neuenschwander, Beat; Röver, Christian; Friede, Tim

2017-06-01

Clinical research and drug development in orphan diseases are challenging, since large-scale randomized studies are difficult to conduct. Formally synthesizing the evidence is therefore of great value, yet this is rarely done in the drug-approval process. Phase III designs that make better use of phase II data can facilitate drug development in orphan diseases. A Bayesian meta-analytic approach is used to inform the phase III study with phase II data. It is particularly attractive, since uncertainty of between-trial heterogeneity can be dealt with probabilistically, which is critical if the number of studies is small. Furthermore, it allows quantifying and discounting the phase II data through the predictive distribution relevant for phase III. A phase III design is proposed which uses the phase II data and considers approval based on a phase III interim analysis. The design is illustrated with a non-inferiority case study from a Food and Drug Administration approval in herpetic keratitis (an orphan disease). Design operating characteristics are compared to those of a traditional design, which ignores the phase II data. An analysis of the phase II data reveals good but insufficient evidence for non-inferiority, highlighting the need for a phase III study. For the phase III study supported by phase II data, the interim analysis is based on half of the patients. For this design, the meta-analytic interim results are conclusive and would justify approval. In contrast, based on the phase III data only, interim results are inconclusive and require further evidence. To accelerate drug development for orphan diseases, innovative study designs and appropriate methodology are needed. Taking advantage of randomized phase II data when analyzing phase III studies looks promising because the evidence from phase II supports informed decision-making. The implementation of the Bayesian design is straightforward with public software such as R.
Determinants of orphan drugs prices in France: a regression analysis.

PubMed

Korchagina, Daria; Millier, Aurelie; Vataire, Anne-Lise; Aballea, Samuel; Falissard, Bruno; Toumi, Mondher

2017-04-21

The introduction of the orphan drug legislation led to the increase in the number of available orphan drugs, but the access to them is often limited due to the high price. Social preferences regarding funding orphan drugs as well as the criteria taken into consideration while setting the price remain unclear. The study aimed at identifying the determinant of orphan drug prices in France using a regression analysis. All drugs with a valid orphan designation at the moment of launch for which the price was available in France were included in the analysis. The selection of covariates was based on a literature review and included drug characteristics (Anatomical Therapeutic Chemical (ATC) class, treatment line, age of target population), diseases characteristics (severity, prevalence, availability of alternative therapeutic options), health technology assessment (HTA) details (actual benefit (AB) and improvement in actual benefit (IAB) scores, delay between the HTA and commercialisation), and study characteristics (type of study, comparator, type of endpoint). The main data sources were European public assessment reports, HTA reports, summaries of opinion on orphan designation of the European Medicines Agency, and the French insurance database of drugs and tariffs. A generalized regression model was developed to test the association between the annual treatment cost and selected covariates. A total of 68 drugs were included. The mean annual treatment cost was €96,518. In the univariate analysis, the ATC class (p = 0.01), availability of alternative treatment options (p = 0.02) and the prevalence (p = 0.02) showed a significant correlation with the annual cost. The multivariate analysis demonstrated significant association between the annual cost and availability of alternative treatment options, ATC class, IAB score, type of comparator in the pivotal clinical trial, as well as commercialisation date and delay between the HTA and commercialisation. The orphan drug pricing is a multivariate phenomenon. The complex association between drug prices and the studied attributes and shows that payers integrate multiple variables in decision making when setting orphan drug prices. The interpretation of the study results is limited by the small sample size and the complex data structure.
An application of a Hill-based response surface model for a drug combination experiment on lung cancer.

PubMed

Ning, Shaoyang; Xu, Hongquan; Al-Shyoukh, Ibrahim; Feng, Jiaying; Sun, Ren

2014-10-30

Combination chemotherapy with multiple drugs has been widely applied to cancer treatment owing to enhanced efficacy and reduced drug resistance. For drug combination experiment analysis, response surface modeling has been commonly adopted. In this paper, we introduce a Hill-based global response surface model and provide an application of the model to a 512-run drug combination experiment with three chemicals, namely AG490, U0126, and indirubin-3 ' -monoxime (I-3-M), on lung cancer cells. The results demonstrate generally improved goodness of fit of our model from the traditional polynomial model, as well as the original Hill model on the basis of fixed-ratio drug combinations. We identify different dose-effect patterns between normal and cancer cells on the basis of our model, which indicates the potential effectiveness of the drug combination in cancer treatment. Meanwhile, drug interactions are analyzed both qualitatively and quantitatively. The distinct interaction patterns between U0126 and I-3-M on two types of cells uncovered by the model could be a further indicator of the efficacy of the drug combination. Copyright © 2014 John Wiley & Sons, Ltd.
Teens, Drugs, & Vegas: Toxicological surveillance of illicit prescription and illegal drug abuse in adolescents (12-17 years) using post-mortem data in Clark County, Nevada from 2005 to 2015.

PubMed

Paul, Anthea B Mahesan; Simms, Lary; Mahesan, Andrew A; Belanger, Eric Charles

2018-04-14

Illegal drug abuse, particularly prescription drug abuse is a growing problem in the United States. Research on adolescent drug abuse is based on national self-reported data. Using local coroner data, quantitative prevalence of illegal substance toxicology and trends can be assessed to aid directed outreach and community-based prevention initiatives. Retrospective analysis was conducted on all cases aged 12-17 years referred to the Office of the Medical Examiner, Clark County from 2005 to 2015 (n = 526). The prevalence of illegal opioid use in this population was 13.3%. The most commonly used drug was tetrahydrocannabinol (THC) in 29.7%. Illegal-prescription opioids and benzodiazepines were used approximately 1.7 times as much as all other illegal-drugs, excluding THC combined. The largest proportion of illicit prescription drug users were accidental death victims (p = 0.02, OR = 2.02). Drug trends by youth are ever evolving and current specific data is necessary to target prevention initiatives in local communities. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

PubMed

Yadav, Manoj Kumar; Singh, Amisha; Swati, D

2014-08-01

Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.
Translational value of liquid chromatography coupled with tandem mass spectrometry-based quantitative proteomics for in vitro-in vivo extrapolation of drug metabolism and transport and considerations in selecting appropriate techniques.

PubMed

Al Feteisi, Hajar; Achour, Brahim; Rostami-Hodjegan, Amin; Barber, Jill

2015-01-01

Drug-metabolizing enzymes and transporters play an important role in drug absorption, distribution, metabolism and excretion and, consequently, they influence drug efficacy and toxicity. Quantification of drug-metabolizing enzymes and transporters in various tissues is therefore essential for comprehensive elucidation of drug absorption, distribution, metabolism and excretion. Recent advances in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) have improved the quantification of pharmacologically relevant proteins. This report presents an overview of mass spectrometry-based methods currently used for the quantification of drug-metabolizing enzymes and drug transporters, mainly focusing on applications and cost associated with various quantitative strategies based on stable isotope-labeled standards (absolute quantification peptide standards, quantification concatemers, protein standards for absolute quantification) and label-free analysis. In mass spectrometry, there is no simple relationship between signal intensity and analyte concentration. Proteomic strategies are therefore complex and several factors need to be considered when selecting the most appropriate method for an intended application, including the number of proteins and samples. Quantitative strategies require appropriate mass spectrometry platforms, yet choice is often limited by the availability of appropriate instrumentation. Quantitative proteomics research requires specialist practical skills and there is a pressing need to dedicate more effort and investment to training personnel in this area. Large-scale multicenter collaborations are also needed to standardize quantitative strategies in order to improve physiologically based pharmacokinetic models.
Recommendations for toxicological investigation of drug-impaired driving and motor vehicle fatalities.

PubMed

Logan, Barry K; Lowrie, Kayla J; Turri, Jennifer L; Yeakel, Jillian K; Limoges, Jennifer F; Miles, Amy K; Scarneo, Colleen E; Kerrigan, Sarah; Farrell, Laurel J

2013-10-01

This report describes the review and update of a set of minimum recommendations for the toxicological investigation of suspected alcohol and drug-impaired driving cases and motor vehicle fatalities involving drugs or alcohol. The recommendations have the goal of ensuring that a consistent set of data regarding the most frequently encountered drugs linked to driving impairment is collected for practical application in the investigation of these cases and to allow epidemiological monitoring and the development of evidence-based public policy on this important public safety issue. The recommendations are based on a survey of practices in US laboratories performing this kind of analysis, consideration of existing epidemiological crash and arrest data and practical considerations of widely available technology platforms in laboratories performing this work. The final recommendations were derived from a consensus meeting of experts recruited from survey respondents and the membership of the National Safety Council's Alcohol, Drug and Impairment Division (formerly known as the Committee on Alcohol and Other Drugs, CAOD).
The social epidemiology of international drug trafficking: comparison of source of supply and distribution networks.

PubMed

Montagne, M

1990-05-01

A variety of strategies have been implemented in an attempt to limit or prevent drug trafficking. Efforts have focused on reducing the supply of drugs, but they have not been very effective. There has been a shift recently to demand-reduction activities, but it is uncertain whether this approach will prove to be valuable. Most of the strategies that are employed are based upon the law enforcement approach. Alternative perspectives, based on principles of epidemiology and social network analysis, are presented and discussed in the context of studying drug trafficking on a global scale. More research and better sources of data and information are needed to delineate the relationship between availability and use, so that we might more effectively focus prevention activities.

Chemometric Methods to Quantify 1D and 2D NMR Spectral Differences Among Similar Protein Therapeutics.

PubMed

Chen, Kang; Park, Junyong; Li, Feng; Patil, Sharadrao M; Keire, David A

2018-04-01

NMR spectroscopy is an emerging analytical tool for measuring complex drug product qualities, e.g., protein higher order structure (HOS) or heparin chemical composition. Most drug NMR spectra have been visually analyzed; however, NMR spectra are inherently quantitative and multivariate and thus suitable for chemometric analysis. Therefore, quantitative measurements derived from chemometric comparisons between spectra could be a key step in establishing acceptance criteria for a new generic drug or a new batch after manufacture change. To measure the capability of chemometric methods to differentiate comparator NMR spectra, we calculated inter-spectra difference metrics on 1D/2D spectra of two insulin drugs, Humulin R® and Novolin R®, from different manufacturers. Both insulin drugs have an identical drug substance but differ in formulation. Chemometric methods (i.e., principal component analysis (PCA), 3-way Tucker3 or graph invariant (GI)) were performed to calculate Mahalanobis distance (D M ) between the two brands (inter-brand) and distance ratio (D R ) among the different lots (intra-brand). The PCA on 1D inter-brand spectral comparison yielded a D M value of 213. In comparing 2D spectra, the Tucker3 analysis yielded the highest differentiability value (D M = 305) in the comparisons made followed by PCA (D M = 255) then the GI method (D M = 40). In conclusion, drug quality comparisons among different lots might benefit from PCA on 1D spectra for rapidly comparing many samples, while higher resolution but more time-consuming 2D-NMR-data-based comparisons using Tucker3 analysis or PCA provide a greater level of assurance for drug structural similarity evaluation between drug brands.
A systematic review of combined student- and parent-based programs to prevent alcohol and other drug use among adolescents.

PubMed

Newton, Nicola C; Champion, Katrina E; Slade, Tim; Chapman, Cath; Stapinski, Lexine; Koning, Ina; Tonks, Zoe; Teesson, Maree

2017-05-01

Alcohol and other drug use among adolescents is a serious concern, and effective prevention is critical. Research indicates that expanding school-based prevention programs to include parenting components could increase prevention outcomes. This paper aims to identify and describe existing combined student- and parent-based programs for the prevention of alcohol and other drug use to evaluate the efficacy of existing programs. The PsycINFO, Medline, Central Register of Controlled trials and Cochrane databases were searched in April 2015 and additional articles were obtained from reference lists. Studies were included if they evaluated a combined universal intervention for students (aged 11-18 years old) and their parents designed to prevent alcohol and/or other drug use, and were delivered in a school-based setting. Risk of bias was assessed by two independent reviewers. Because of the heterogeneity of the included studies, it was not possible to conduct a meta-analysis and a qualitative description of the studies was provided. From a total of 1654 screened papers, 22 research papers met inclusion criteria, which included 13 trials of 10 programs. Of these, nine programs demonstrated significant intervention effects in terms of delaying or reducing adolescent alcohol and/or other drug use in at least one trial. This is the first review of combined student- and parent-based interventions to prevent and reduce alcohol and other drug use. Whilst existing combined student- and parent-based programs have shown promising results, key gaps in the literature have been identified and are discussed in the context of the development of future prevention programs. [Newton NC, Champion KE, Slade T, Chapman C, Stapinski L, Koning I, Tonks Z, Teesson M. A systematic review of combined student- and parent-based programs to prevent alcohol and other drug use among adolescents. Drug Alcohol Rev 2017;36:337-351]. © 2017 Australasian Professional Society on Alcohol and other Drugs.
Broad-spectrum drug screening of meconium by liquid chromatography with tandem mass spectrometry and time-of-flight mass spectrometry.

PubMed

Ristimaa, Johanna; Gergov, Merja; Pelander, Anna; Halmesmäki, Erja; Ojanperä, Ilkka

2010-09-01

Analysis of the major drugs of abuse in meconium has been established in clinical practice for detecting fetal exposure to illicit drugs, particularly for the ready availability of the sample and ease of collection from diapers, compared with neonatal hair and urine. Very little is known about the occurrence and detection possibilities of therapeutic and licit drugs in meconium. Meconium specimens (n = 209) were collected in delivery hospitals, from infants of mothers who were suspected to be drug abusers. A targeted analysis method by liquid chromatography-triple quadrupole mass spectrometry (LC-MS/MS) was developed for abused drugs: amphetamine, methamphetamine, 3,4-methylenedioxyamphetamine, 3,4-methylenedioxymethamphetamine, morphine, codeine, 6-monoacetylmorphine, oxycodone, methadone, tramadol, buprenorphine, and norbuprenorphine. A separate LC-MS/MS method was developed for 11-nor-∆(9)-tetrahydrocannabinol-9-carboxylic acid. A screening method based on LC coupled to time-of-flight MS was applied to a broad spectrum of drugs. As a result, a total of 77 different compounds were found. The main drug findings in meconium were as follows: local anesthetics 82.5% (n = 172), nicotine or its metabolites 61.5% (n = 129), opioids 48.5% (n = 101), stimulants 21.0% (n = 44), hypnotics and sedatives 19.0% (n = 40), antidepressants 18.0% (n = 38), antipsychotics 5.5% (n = 11), and cannabis 3.0% (n = 5). By revealing drugs and metabolites beyond the ordinary scope, the present procedure helps the pediatrician in cases where maternal denial is strong but the infant seems to suffer from typical drug-withdrawal symptoms. Intrapartum drug administration cannot be differentiated from gestational drug use by meconium analysis, which affects the interpretation of oxycodone, tramadol, fentanyl, pethidine, and ephedrine findings.
Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

PubMed

Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

2017-05-01

To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.
Drug Overdose Surveillance Using Hospital Discharge Data

PubMed Central

Bunn, Terry L.; Talbert, Jeffery

2014-01-01

Objectives We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. Methods We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000–2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Results Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. Conclusion The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison. PMID:25177055
Effect of gellan gum on the thermogelation property and drug release profile of Poloxamer 407 based ophthalmic formulation.

PubMed

Dewan, Mitali; Sarkar, Gunjan; Bhowmik, Manas; Das, Beauty; Chattoapadhyay, Atis Kumar; Rana, Dipak; Chattopadhyay, Dipankar

2017-09-01

The effect of gellan gum on the gelation behavior and in-vitro release of a specific drug named pilocarpine hydrochloride from different ophthalmic formulations based on poloxamer 407 is examined. The mixture of 0.3wt% gellan gum and 18wt% poloxamer (PM) solutions show a considerable increase in gel strength in physiological condition. Gel dissolution rate from PM based formulation is significantly decreased due to the addition of gellan gum. FTIR spectra analysis witnesses an interaction in between OH groups of two polymers which accounts for lowering in gelation temperature of PM-gellan gum based formulations. It is also observed from the cryo-SEM study that the pore size of PM gel decreases with an addition of gellan gum and in-vitro release studies indicate that PM-gellan gum based formulation retain drug better than the PM solution alone. Therefore, the developed formulation has the potential to be utilized as an in-situ ophthalmic drug carrier. Copyright © 2017 Elsevier B.V. All rights reserved.
Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies.

PubMed

Chou, Ting-Chao

2006-09-01

The median-effect equation derived from the mass-action law principle at equilibrium-steady state via mathematical induction and deduction for different reaction sequences and mechanisms and different types of inhibition has been shown to be the unified theory for the Michaelis-Menten equation, Hill equation, Henderson-Hasselbalch equation, and Scatchard equation. It is shown that dose and effect are interchangeable via defined parameters. This general equation for the single drug effect has been extended to the multiple drug effect equation for n drugs. These equations provide the theoretical basis for the combination index (CI)-isobologram equation that allows quantitative determination of drug interactions, where CI < 1, = 1, and > 1 indicate synergism, additive effect, and antagonism, respectively. Based on these algorithms, computer software has been developed to allow automated simulation of synergism and antagonism at all dose or effect levels. It displays the dose-effect curve, median-effect plot, combination index plot, isobologram, dose-reduction index plot, and polygonogram for in vitro or in vivo studies. This theoretical development, experimental design, and computerized data analysis have facilitated dose-effect analysis for single drug evaluation or carcinogen and radiation risk assessment, as well as for drug or other entity combinations in a vast field of disciplines of biomedical sciences. In this review, selected examples of applications are given, and step-by-step examples of experimental designs and real data analysis are also illustrated. The merging of the mass-action law principle with mathematical induction-deduction has been proven to be a unique and effective scientific method for general theory development. The median-effect principle and its mass-action law based computer software are gaining increased applications in biomedical sciences, from how to effectively evaluate a single compound or entity to how to beneficially use multiple drugs or modalities in combination therapies.
Community-based management versus traditional hospitalization in treatment of drug-resistant tuberculosis: a systematic review and meta-analysis.

PubMed

Williams, Abimbola Onigbanjo; Makinde, Olusesan Ayodeji; Ojo, Mojisola

2016-01-01

Multidrug drug resistant Tuberculosis (MDR-TB) and extensively drug resistant Tuberculosis (XDR-TB) have emerged as significant public health threats worldwide. This systematic review and meta-analysis aimed to investigate the effects of community-based treatment to traditional hospitalization in improving treatment success rates among MDR-TB and XDR-TB patients in the 27 MDR-TB High burden countries (HBC). We searched PubMed, Cochrane, Lancet, Web of Science, International Journal of Tuberculosis and Lung Disease, and Centre for Reviews and Dissemination (CRD) for studies on community-based treatment and traditional hospitalization and MDR-TB and XDR-TB from the 27 MDR-TB HBC. Data on treatment success and failure rates were extracted from retrospective and prospective cohort studies, and a case control study. Sensitivity analysis, subgroup analyses, and meta-regression analysis were used to explore bias and potential sources of heterogeneity. The final sample included 16 studies involving 3344 patients from nine countries; Bangladesh, China, Ethiopia, Kenya, India, South Africa, Philippines, Russia, and Uzbekistan. Based on a random-effects model, we observed a higher treatment success rate in community-based treatment (Point estimate = 0.68, 95 % CI: 0.59 to 0.76, p < 0.01) compared to traditional hospitalization (Point estimate = 0.57, 95 % CI: 0.44 to 0.69, p < 0.01). A lower treatment failure rate was observed in community-based treatment 7 % (Point estimate = 0.07, 95 % CI: 0.03 to 0.10; p < 0.01) compared to traditional hospitalization (Point estimate = 0.188, 95 % CI: 0.10 to 0.28; p < 0.01). In the subgroup analysis, studies without HIV co-infected patients, directly observed therapy short course-plus (DOTS-Plus) implemented throughout therapy, treatment duration > 18 months, and regimen with drugs >5 reported higher treatment success rate. In the meta-regression model, age of patients, adverse events, treatment duration, and lost to follow up explains some of the heterogeneity of treatment effects between studies. Community-based management improved treatment outcomes. A mix of interventions with DOTS-Plus throughout therapy and treatment duration > 18 months as well as strategies in place for lost to follow up and adverse events should be considered in MDR-TB and XDR-TB interventions, as they influenced positively, treatment success.
AtomicChargeCalculator: interactive web-based calculation of atomic charges in large biomolecular complexes and drug-like molecules.

PubMed

Ionescu, Crina-Maria; Sehnal, David; Falginella, Francesco L; Pant, Purbaj; Pravda, Lukáš; Bouchal, Tomáš; Svobodová Vařeková, Radka; Geidl, Stanislav; Koča, Jaroslav

2015-01-01

Partial atomic charges are a well-established concept, useful in understanding and modeling the chemical behavior of molecules, from simple compounds, to large biomolecular complexes with many reactive sites. This paper introduces AtomicChargeCalculator (ACC), a web-based application for the calculation and analysis of atomic charges which respond to changes in molecular conformation and chemical environment. ACC relies on an empirical method to rapidly compute atomic charges with accuracy comparable to quantum mechanical approaches. Due to its efficient implementation, ACC can handle any type of molecular system, regardless of size and chemical complexity, from drug-like molecules to biomacromolecular complexes with hundreds of thousands of atoms. ACC writes out atomic charges into common molecular structure files, and offers interactive facilities for statistical analysis and comparison of the results, in both tabular and graphical form. Due to high customizability and speed, easy streamlining and the unified platform for calculation and analysis, ACC caters to all fields of life sciences, from drug design to nanocarriers. ACC is freely available via the Internet at http://ncbr.muni.cz/ACC.
Glutathione S-transferase P1 (GSTP1) directly influences platinum drug chemosensitivity in ovarian tumour cell lines.

PubMed

Sawers, L; Ferguson, M J; Ihrig, B R; Young, H C; Chakravarty, P; Wolf, C R; Smith, G

2014-09-09

Chemotherapy response in ovarian cancer patients is frequently compromised by drug resistance, possibly due to altered drug metabolism. Platinum drugs are metabolised by glutathione S-transferase P1 (GSTP1), which is abundantly, but variably expressed in ovarian tumours. We have created novel ovarian tumour cell line models to investigate the extent to which differential GSTP1 expression influences chemosensitivity. Glutathione S-transferase P1 was stably deleted in A2780 and expression significantly reduced in cisplatin-resistant A2780DPP cells using Mission shRNA constructs, and MTT assays used to compare chemosensitivity to chemotherapy drugs used to treat ovarian cancer. Differentially expressed genes in GSTP1 knockdown cells were identified by Illumina HT-12 expression arrays and qRT-PCR analysis, and altered pathways predicted by MetaCore (GeneGo) analysis. Cell cycle changes were assessed by FACS analysis of PI-labelled cells and invasion and migration compared in quantitative Boyden chamber-based assays. Glutathione S-transferase P1 knockdown selectively influenced cisplatin and carboplatin chemosensitivity (2.3- and 4.83-fold change in IC50, respectively). Cell cycle progression was unaffected, but cell invasion and migration was significantly reduced. We identified several novel GSTP1 target genes and candidate platinum chemotherapy response biomarkers. Glutathione S-transferase P1 has an important role in cisplatin and carboplatin metabolism in ovarian cancer cells. Inter-tumour differences in GSTP1 expression may therefore influence response to platinum-based chemotherapy in ovarian cancer patients.
Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.
A bioinformatics approach for precision medicine off-label drug drug selection among triple negative breast cancer patients.

PubMed

Cheng, Lijun; Schneider, Bryan P; Li, Lang

2016-07-01

Cancer has been extensively characterized on the basis of genomics. The integration of genetic information about cancers with data on how the cancers respond to target based therapy to help to optimum cancer treatment. The increasing usage of sequencing technology in cancer research and clinical practice has enormously advanced our understanding of cancer mechanisms. The cancer precision medicine is becoming a reality. Although off-label drug usage is a common practice in treating cancer, it suffers from the lack of knowledge base for proper cancer drug selections. This eminent need has become even more apparent considering the upcoming genomics data. In this paper, a personalized medicine knowledge base is constructed by integrating various cancer drugs, drug-target database, and knowledge sources for the proper cancer drugs and their target selections. Based on the knowledge base, a bioinformatics approach for cancer drugs selection in precision medicine is developed. It integrates personal molecular profile data, including copy number variation, mutation, and gene expression. By analyzing the 85 triple negative breast cancer (TNBC) patient data in the Cancer Genome Altar, we have shown that 71.7% of the TNBC patients have FDA approved drug targets, and 51.7% of the patients have more than one drug target. Sixty-five drug targets are identified as TNBC treatment targets and 85 candidate drugs are recommended. Many existing TNBC candidate targets, such as Poly (ADP-Ribose) Polymerase 1 (PARP1), Cell division protein kinase 6 (CDK6), epidermal growth factor receptor, etc., were identified. On the other hand, we found some additional targets that are not yet fully investigated in the TNBC, such as Gamma-Glutamyl Hydrolase (GGH), Thymidylate Synthetase (TYMS), Protein Tyrosine Kinase 6 (PTK6), Topoisomerase (DNA) I, Mitochondrial (TOP1MT), Smoothened, Frizzled Class Receptor (SMO), etc. Our additional analysis of target and drug selection strategy is also fully supported by the drug screening data on TNBC cell lines in the Cancer Cell Line Encyclopedia. The proposed bioinformatics approach lays a foundation for cancer precision medicine. It supplies much needed knowledge base for the off-label cancer drug usage in clinics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Pharmaceutical Price Controls and Minimum Efficacy Regulation: Evidence from the United States and Italy

PubMed Central

Atella, Vincenzo; Bhattacharya, Jay; Carbonari, Lorenzo

2012-01-01

Objective This article examines the relationship between drug price and drug quality and how it varies across two of the most common regulatory regimes in the pharmaceutical market: minimum efficacy standards (MES) and a mix of MES and price control mechanisms (MES + PC). Data Sources Our primary data source is the Tufts-New England Medical Center-Cost Effectiveness Analysis Registry which have been merged with price data taken from MEPS (for the United States) and AIFA (for Italy). Study Design Through a simple model of adverse selection we model the interaction between firms, heterogeneous buyers, and the regulator. Principal Findings The theoretical analysis provides two results. First, an MES regime provides greater incentives to produce high-quality drugs. Second, an MES + PC mix reduces the difference in price between the highest and lowest quality drugs on the market. Conclusion The empirical analysis based on United States and Italian data corroborates these results. PMID:22091623
78 FR 64425 - Current Good Manufacturing Practice and Hazard Analysis and Risk-Based Preventive Controls for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-29

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration 21 CFR Parts 16, 225, 500, 507, and 579 [Docket No. FDA-2011-N-0922] Current Good Manufacturing Practice and Hazard Analysis and Risk- Based Preventive Controls for Food for Animals; Public Meeting on Proposed Rule AGENCY: Food and...
First evaluation of illicit and licit drug consumption based on wastewater analysis in Fort de France urban area (Martinique, Caribbean), a transit area for drug smuggling.

PubMed

Damien, Devault A; Thomas, Néfau; Hélène, Pascaline; Sara, Karolak; Yves, Levi

2014-08-15

Drugs of abuse are increasingly consumed worldwide. Such consumption could be back-calculated based on wastewater content. The West Indies, with its coca production and its thriving illicit drug market, is both a hub of world cocaine trafficking and a place where its consumption is prevalent particularly in the form of crack. The present study will firstly investigate Caribbean consumption by a daily 5 to 7 day sampling campaign of composite wastewater samples from the four wastewater treatment plants of the Martinique capital, including working and non-working periods. The local consumption of cocaine is ten to thirty times higher than OECD standards because of the prevalence of crack. The excretion coefficient for crack consumption and the impact of temperature on drug stability need further investigation. However, the low diversity of illicit drugs consumed and the crack prevalence suggest practices driven by the transiting of drugs for international trafficking. Copyright © 2014 Elsevier B.V. All rights reserved.
Cost-offsets of prescription drug expenditures: data analysis via a copula-based bivariate dynamic hurdle model.

PubMed

Deb, Partha; Trivedi, Pravin K; Zimmer, David M

2014-10-01

In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.
Recent Advances in Electrochemical Biosensors Based on Enzyme Inhibition for Clinical and Pharmaceutical Applications

PubMed Central

El Harrad, Loubna; Bourais, Ilhame; Mohammadi, Hasna; Amine, Aziz

2018-01-01

A large number of enzyme inhibitors are used as drugs to treat several diseases such as gout, diabetes, AIDS, depression, Parkinson’s and Alzheimer’s diseases. Electrochemical biosensors based on enzyme inhibition are useful devices for an easy, fast and environment friendly monitoring of inhibitors like drugs. In the last decades, electrochemical biosensors have shown great potentials in the detection of different drugs like neostigmine, ketoconazole, donepezil, allopurinol and many others. They attracted increasing attention due to the advantage of being high sensitive and accurate analytical tools, able to reach low detection limits and the possibility to be performed on real samples. This review will spotlight the research conducted in the past 10 years (2007–2017) on inhibition based enzymatic electrochemical biosensors for the analysis of different drugs. New assays based on novel bio-devices will be debated. Moreover, the exploration of the recent graphical approach in diagnosis of reversible and irreversible inhibition mechanism will be discussed. The accurate and the fast diagnosis of inhibition type will help researchers in further drug design improvements and the identification of new molecules that will serve as new enzyme targets. PMID:29315246
A web-based quantitative signal detection system on adverse drug reaction in China.

PubMed

Li, Chanjuan; Xia, Jielai; Deng, Jianxiong; Chen, Wenge; Wang, Suzhen; Jiang, Jing; Chen, Guanquan

2009-07-01

To establish a web-based quantitative signal detection system for adverse drug reactions (ADRs) based on spontaneous reporting to the Guangdong province drug-monitoring database in China. Using Microsoft Visual Basic and Active Server Pages programming languages and SQL Server 2000, a web-based system with three software modules was programmed to perform data preparation and association detection, and to generate reports. Information component (IC), the internationally recognized measure of disproportionality for quantitative signal detection, was integrated into the system, and its capacity for signal detection was tested with ADR reports collected from 1 January 2002 to 30 June 2007 in Guangdong. A total of 2,496 associations including known signals were mined from the test database. Signals (e.g., cefradine-induced hematuria) were found early by using the IC analysis. In addition, 291 drug-ADR associations were alerted for the first time in the second quarter of 2007. The system can be used for the detection of significant associations from the Guangdong drug-monitoring database and could be an extremely useful adjunct to the expert assessment of very large numbers of spontaneously reported ADRs for the first time in China.
Effectiveness of Gross Model-Based Emotion Regulation Strategies Training on Anger Reduction in Drug-Dependent Individuals and its Sustainability in Follow-up.

PubMed

Massah, Omid; Sohrabi, Faramarz; A'azami, Yousef; Doostian, Younes; Farhoudian, Ali; Daneshmand, Reza

2016-03-01

Emotion plays an important role in adapting to life changes and stressful events. Difficulty regulating emotions is one of the problems drug abusers often face, and teaching these individuals to express and manage their emotions can be effective on improving their difficult circumstances. The present study aimed to determine the effectiveness of the Gross model-based emotion regulation strategies training on anger reduction in drug-dependent individuals. The present study had a quasi-experimental design wherein pretest-posttest evaluations were applied using a control group. The population under study included addicts attending Marivan's methadone maintenance therapy centers in 2012 - 2013. Convenience sampling was used to select 30 substance-dependent individuals undergoing maintenance treatment who were then randomly assigned to the experiment and control groups. The experiment group received its training in eight two-hour sessions. Data were analyzed using analysis of co-variance and paired t-test. There was significant reduction in anger symptoms of drug-dependent individuals after gross model based emotion regulation training (ERT) (P < 0.001). Moreover, the effectiveness of the training on anger was persistent in the follow-up period. Symptoms of anger in drug-dependent individuals of this study were reduced by gross model-based emotion regulation strategies training. Based on the results of this study, we may conclude that the gross model based emotion regulation strategies training can be applied alongside other therapies to treat drug abusers undergoing rehabilitation.
Longitudinal medical records as a complement to routine drug safety signal analysis†

PubMed Central

Watson, Sarah; Sandberg, Lovisa; Johansson, Jeanette; Edwards, I. Ralph

2015-01-01

Abstract Purpose To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database. Methods Drug and ADR combinations from the routine signal detection process of VigiBase® in 2011 were matched to combinations in The Health Improvement Network (THIN). The number and type of drugs and ADRs from the data sets were investigated. For unlabelled combinations, graphical display of longitudinal event patterns (chronographs) in THIN was inspected to determine if the pattern supported the VigiBase combination. Results Of 458 combinations in the VigiBase data set, 190 matched to corresponding combinations in THIN (after excluding drugs with less than 100 prescriptions in THIN). Eighteen percent of the VigiBase and 9% of the matched THIN combinations referred to new drugs reported with serious reactions. Of the 112 unlabelled combinations matched to THIN, 52 chronographs were inconclusive mainly because of lack of data; 34 lacked any outstanding pattern around the time of prescription; 24 had an elevation of events in the pre‐prescription period, hence weakened the suspicion of a drug relationship; two had an elevated pattern of events exclusively in the post‐prescription period that, after review of individual patient histories, did not support an association. Conclusions Longitudinal medical records were useful in understanding the clinical context around a drug and suspected ADR combination and the probability of a causal relationship. A drawback was the paucity of data for newly marketed drugs with serious reactions. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd. PMID:25623045

Did we get our money's worth? Bridging economic and behavioral measures of program success in adolescent drug prevention.

PubMed

Griffith, Kevin N; Scheier, Lawrence M

2013-11-08

The recent U.S. Congressional mandate for creating drug-free learning environments in elementary and secondary schools stipulates that education reform rely on accountability, parental and community involvement, local decision making, and use of evidence-based drug prevention programs. By necessity, this charge has been paralleled by increased interest in demonstrating that drug prevention programs net tangible benefits to society. One pressing concern is precisely how to integrate traditional scientific methods of program evaluation with economic measures of "cost efficiency". The languages and methods of each respective discipline don't necessarily converge on how to establish the true benefits of drug prevention. This article serves as a primer for conducting economic analyses of school-based drug prevention programs. The article provides the reader with a foundation in the relevant principles, methodologies, and benefits related to conducting economic analysis. Discussion revolves around how economists value the potential costs and benefits, both financial and personal, from implementing school-based drug prevention programs targeting youth. Application of heterogeneous costing methods coupled with widely divergent program evaluation findings influences the feasibility of these techniques and may hinder utilization of these practices. Determination of cost-efficiency should undoubtedly become one of several markers of program success and contribute to the ongoing debate over health policy.
Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research

PubMed Central

He, Yongqun

2016-01-01

Compared with controlled terminologies (e.g., MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network (i.e., OneNet). A new “OneNet effectiveness” tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research. PMID:27458549
Automated Liquid Microjunction Surface Sampling-HPLC-MS/MS Analysis of Drugs and Metabolites in Whole-Body Thin Tissue Sections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kertesz, Vilmos; Van Berkel, Gary J

A fully automated liquid extraction-based surface sampling system utilizing a commercially available autosampler coupled to high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) detection is reported. Discrete spots selected for droplet-based sampling and automated sample queue generation for both the autosampler and MS were enabled by using in-house developed software. In addition, co-registration of spatially resolved sampling position and HPLC-MS information to generate heatmaps of compounds monitored for subsequent data analysis was also available in the software. The system was evaluated with whole-body thin tissue sections from propranolol dosed rat. The hands-free operation of the system was demonstrated by creating heatmapsmore » of the parent drug and its hydroxypropranolol glucuronide metabolites with 1 mm resolution in the areas of interest. The sample throughput was approximately 5 min/sample defined by the time needed for chromatographic separation. The spatial distributions of both the drug and its metabolites were consistent with previous studies employing other liquid extraction-based surface sampling methodologies.« less
Characterization of drug authenticity using thin-layer chromatography imaging with a mobile phone.

PubMed

Yu, Hojeong; Le, Huy M; Kaale, Eliangiringa; Long, Kenneth D; Layloff, Thomas; Lumetta, Steven S; Cunningham, Brian T

2016-06-05

Thin-layer chromatography (TLC) has a myriad of separation applications in chemistry, biology, and pharmacology due to its simplicity and low cost. While benchtop laboratory sample application and detection systems for TLC provide accurate quantitation of TLC spot positions and densities, there are many applications where inexpensive and portable instruments would greatly expand the applicability of the technology. In this work, we demonstrate identity verification and concentration determination of pharmaceutical compounds via TLC using a custom 3D-printed cradle that interfaces with an ordinary mobile phone. The cradle holds the mobile phone's internal, rear-facing camera in a fixed position relative to a UV lamp and a TLC plate that includes a phosphor in the stationary phase. Analysis of photographs thus reveals the locations and intensities of principal spots of UV--absorbing drugs. Automated image analysis software determines the center location and density of dark spots, which, using integrated calibration spots of known drug compounds and concentrations, can be used to determine if a drug has been diluted or substituted. Two independent image processing approaches have been developed that may be selected based upon the processing capabilities of the smartphone. Each approach is able to discern 5% drug concentration differences. Using single-component solutions of nevirapine, amodiaquine, and paracetamol that have been manually applied, the mobile phone-based detection instrument provides measurements that are equivalent to those obtained with a commercially available lab-based desktop TLC densitometer. Copyright © 2016 Elsevier B.V. All rights reserved.
Random Forest Segregation of Drug Responses May Define Regions of Biological Significance

PubMed Central

Bukhari, Qasim; Borsook, David; Rudin, Markus; Becerra, Lino

2016-01-01

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies. PMID:27014046
Elemental Impurities in Pharmaceutical Excipients.

PubMed

Li, Gang; Schoneker, Dave; Ulman, Katherine L; Sturm, Jason J; Thackery, Lisa M; Kauffman, John F

2015-12-01

Control of elemental impurities in pharmaceutical materials is currently undergoing a transition from control based on concentrations in components of drug products to control based on permitted daily exposures in drug products. Within the pharmaceutical community, there is uncertainty regarding the impact of these changes on manufactures of drug products. This uncertainty is fueled in part by a lack of publically available information on elemental impurity levels in common pharmaceutical excipients. This paper summarizes a recent survey of elemental impurity levels in common pharmaceutical excipients as well as some drug substances. A widely applicable analytical procedure was developed and was shown to be suitable for analysis of elements that are subject to United States Pharmacopoeia Chapter <232> and International Conference on Harmonization's Q3D Guideline on Elemental Impurities. The procedure utilizes microwave-assisted digestion of pharmaceutical materials and inductively coupled plasma mass spectrometry for quantitative analysis of these elements. The procedure was applied to 190 samples from 31 different excipients and 15 samples from eight drug substances provided through the International Pharmaceutical Excipient Council of the Americas. The results of the survey indicate that, for the materials included in the study, relatively low levels of elemental impurities are present. © 2015 The Authors. Journal of Pharmaceutical Sciences published by Wiley Periodicals, Inc. and the American Pharmacists Association.
Comparative Study of Different Methods for the Prediction of Drug-Polymer Solubility.

PubMed

Knopp, Matthias Manne; Tajber, Lidia; Tian, Yiwei; Olesen, Niels Erik; Jones, David S; Kozyra, Agnieszka; Löbmann, Korbinian; Paluch, Krzysztof; Brennan, Claire Marie; Holm, René; Healy, Anne Marie; Andrews, Gavin P; Rades, Thomas

2015-09-08

In this study, a comparison of different methods to predict drug-polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug-polymer solubility at 25 °C was predicted using the Flory-Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine-PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug-polymer solubility.
Mining FDA drug labels using an unsupervised learning technique--topic modeling.

PubMed

Bisgin, Halil; Liu, Zhichao; Fang, Hong; Xu, Xiaowei; Tong, Weida

2011-10-18

The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving useful information from the labeling text in a consistent and accurate fashion for comparative analysis across drugs. Consequently, this task has largely relied on the manual reading of the full text by experts, which is time consuming and labor intensive. In this study, a novel text mining method with unsupervised learning in nature, called topic modeling, was applied to the drug labeling with a goal of discovering "topics" that group drugs with similar safety concerns and/or therapeutic uses together. A total of 794 FDA-approved drug labels were used in this study. First, the three labeling sections (i.e., Boxed Warning, Warnings and Precautions, Adverse Reactions) of each drug label were processed by the Medical Dictionary for Regulatory Activities (MedDRA) to convert the free text of each label to the standard ADR terms. Next, the topic modeling approach with latent Dirichlet allocation (LDA) was applied to generate 100 topics, each associated with a set of drugs grouped together based on the probability analysis. Lastly, the efficacy of the topic modeling was evaluated based on known information about the therapeutic uses and safety data of drugs. The results demonstrate that drugs grouped by topics are associated with the same safety concerns and/or therapeutic uses with statistical significance (P<0.05). The identified topics have distinct context that can be directly linked to specific adverse events (e.g., liver injury or kidney injury) or therapeutic application (e.g., antiinfectives for systemic use). We were also able to identify potential adverse events that might arise from specific medications via topics. The successful application of topic modeling on the FDA drug labeling demonstrates its potential utility as a hypothesis generation means to infer hidden relationships of concepts such as, in this study, drug safety and therapeutic use in the study of biomedical documents.
AOP: An R Package For Sufficient Causal Analysis in Pathway-based Screening of Drugs and Chemicals for Adversity

EPA Science Inventory

Summary: How can I quickly find the key events in a pathway that I need to monitor to predict that a/an beneficial/adverse event/outcome will occur? This is a key question when using signaling pathways for drug/chemical screening in pharma-cology, toxicology and risk assessment. ...
Microfluidics for cell-based high throughput screening platforms - A review.

PubMed

Du, Guansheng; Fang, Qun; den Toonder, Jaap M J

2016-01-15

In the last decades, the basic techniques of microfluidics for the study of cells such as cell culture, cell separation, and cell lysis, have been well developed. Based on cell handling techniques, microfluidics has been widely applied in the field of PCR (Polymerase Chain Reaction), immunoassays, organ-on-chip, stem cell research, and analysis and identification of circulating tumor cells. As a major step in drug discovery, high-throughput screening allows rapid analysis of thousands of chemical, biochemical, genetic or pharmacological tests in parallel. In this review, we summarize the application of microfluidics in cell-based high throughput screening. The screening methods mentioned in this paper include approaches using the perfusion flow mode, the droplet mode, and the microarray mode. We also discuss the future development of microfluidic based high throughput screening platform for drug discovery. Copyright © 2015 Elsevier B.V. All rights reserved.
Opportunities for Web-based Drug Repositioning: Searching for Potential Antihypertensive Agents with Hypotension Adverse Events.

PubMed

Wang, Kejian; Wan, Mei; Wang, Rui-Sheng; Weng, Zuquan

2016-04-01

Drug repositioning refers to the process of developing new indications for existing drugs. As a phenotypic indicator of drug response in humans, clinical side effects may provide straightforward signals and unique opportunities for drug repositioning. We aimed to identify drugs frequently associated with hypotension adverse reactions (ie, the opposite condition of hypertension), which could be potential candidates as antihypertensive agents. We systematically searched the electronic records of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) through the openFDA platform to assess the association between hypotension incidence and antihypertensive therapeutic effect regarding a list of 683 drugs. Statistical analysis of FAERS data demonstrated that those drugs frequently co-occurring with hypotension events were more likely to have antihypertensive activity. Ranked by the statistical significance of frequent hypotension reporting, the well-known antihypertensive drugs were effectively distinguished from others (with an area under the receiver operating characteristic curve > 0.80 and a normalized discounted cumulative gain of 0.77). In addition, we found a series of antihypertensive agents (particularly drugs originally developed for treating nervous system diseases) among the drugs with top significant reporting, suggesting the good potential of Web-based and data-driven drug repositioning. We found several candidate agents among the hypotension-related drugs on our list that may be redirected for lowering blood pressure. More important, we showed that a pharmacovigilance system could alternatively be used to identify antihypertensive agents and sustainably create opportunities for drug repositioning.
Structure-based discovery and binding site analysis of histamine receptor ligands.

PubMed

Kiss, Róbert; Keserű, György M

2016-12-01

The application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, the authors review the development of histamine receptor models and their application in drug discovery. Expert opinion: In the authors' opinion, the application of atomistic histamine receptor models has played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery; however, our analysis also demonstrates that for building H3 and H4 receptor homology models, other GPCRs may be more suitable as templates. For these receptors, the authors envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.
Sampling of illicit drugs for quantitative analysis--part II. Study of particle size and its influence on mass reduction.

PubMed

Bovens, M; Csesztregi, T; Franc, A; Nagy, J; Dujourdy, L

2014-01-01

The basic goal in sampling for the quantitative analysis of illicit drugs is to maintain the average concentration of the drug in the material from its original seized state (the primary sample) all the way through to the analytical sample, where the effect of particle size is most critical. The size of the largest particles of different authentic illicit drug materials, in their original state and after homogenisation, using manual or mechanical procedures, was measured using a microscope with a camera attachment. The comminution methods employed included pestle and mortar (manual) and various ball and knife mills (mechanical). The drugs investigated were amphetamine, heroin, cocaine and herbal cannabis. It was shown that comminution of illicit drug materials using these techniques reduces the nominal particle size from approximately 600 μm down to between 200 and 300 μm. It was demonstrated that the choice of 1 g increments for the primary samples of powdered drugs and cannabis resin, which were used in the heterogeneity part of our study (Part I) was correct for the routine quantitative analysis of illicit seized drugs. For herbal cannabis we found that the appropriate increment size was larger. Based on the results of this study we can generally state that: An analytical sample weight of between 20 and 35 mg of an illicit powdered drug, with an assumed purity of 5% or higher, would be considered appropriate and would generate an RSDsampling in the same region as the RSDanalysis for a typical quantitative method of analysis for the most common, powdered, illicit drugs. For herbal cannabis, with an assumed purity of 1% THC (tetrahydrocannabinol) or higher, an analytical sample weight of approximately 200 mg would be appropriate. In Part III we will pull together our homogeneity studies and particle size investigations and use them to devise sampling plans and sample preparations suitable for the quantitative instrumental analysis of the most common illicit drugs. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Cost-effectiveness analysis of introducing malaria diagnostic testing in drug shops: A cluster-randomised trial in Uganda.

PubMed

Hansen, Kristian Schultz; Clarke, Siân E; Lal, Sham; Magnussen, Pascal; Mbonye, Anthony K

2017-01-01

Private sector drug shops are an important source of malaria treatment in Africa, yet diagnosis without parasitological testing is common among these providers. Accurate rapid diagnostic tests for malaria (mRDTs) require limited training and present an opportunity to increase access to correct diagnosis. The present study was a cost-effectiveness analysis of the introduction of mRDTs in Ugandan drug shops. Drug shop vendors were trained to perform and sell subsidised mRDTs and artemisinin-based combination therapies (ACTs) in the intervention arm while vendors offered ACTs following presumptive diagnosis of malaria in the control arm. The effect on the proportion of customers with fever 'appropriately treated of malaria with ACT' was captured during a randomised trial in drug shops in Mukono District, Uganda. Health sector costs included: training of drug shop vendors, community sensitisation, supervision and provision of mRDTs and ACTs to drug shops. Household costs of treatment-seeking were captured in a representative sample of drug shop customers. The introduction of mRDTs in drug shops was associated with a large improvement of diagnosis and treatment of malaria, resulting in low incremental costs for the health sector at US$0.55 per patient appropriately treated of malaria. High expenditure on non-ACT drugs by households contributed to higher incremental societal costs of US$3.83. Sensitivity analysis showed that mRDTs would become less cost-effective compared to presumptive diagnosis with increasing malaria prevalence and lower adherence to negative mRDT results. mRDTs in drug shops improved the targeting of ACTs to malaria patients and are likely to be considered cost-effective compared to presumptive diagnosis, although the increased costs borne by households when the test result is negative are a concern.
Cost-effectiveness analysis of introducing malaria diagnostic testing in drug shops: A cluster-randomised trial in Uganda

PubMed Central

Hansen, Kristian Schultz; Clarke, Siân E.; Lal, Sham; Magnussen, Pascal; Mbonye, Anthony K.

2017-01-01

Background Private sector drug shops are an important source of malaria treatment in Africa, yet diagnosis without parasitological testing is common among these providers. Accurate rapid diagnostic tests for malaria (mRDTs) require limited training and present an opportunity to increase access to correct diagnosis. The present study was a cost-effectiveness analysis of the introduction of mRDTs in Ugandan drug shops. Methods Drug shop vendors were trained to perform and sell subsidised mRDTs and artemisinin-based combination therapies (ACTs) in the intervention arm while vendors offered ACTs following presumptive diagnosis of malaria in the control arm. The effect on the proportion of customers with fever ‘appropriately treated of malaria with ACT’ was captured during a randomised trial in drug shops in Mukono District, Uganda. Health sector costs included: training of drug shop vendors, community sensitisation, supervision and provision of mRDTs and ACTs to drug shops. Household costs of treatment-seeking were captured in a representative sample of drug shop customers. Findings The introduction of mRDTs in drug shops was associated with a large improvement of diagnosis and treatment of malaria, resulting in low incremental costs for the health sector at US$0.55 per patient appropriately treated of malaria. High expenditure on non-ACT drugs by households contributed to higher incremental societal costs of US$3.83. Sensitivity analysis showed that mRDTs would become less cost-effective compared to presumptive diagnosis with increasing malaria prevalence and lower adherence to negative mRDT results. Conclusion mRDTs in drug shops improved the targeting of ACTs to malaria patients and are likely to be considered cost-effective compared to presumptive diagnosis, although the increased costs borne by households when the test result is negative are a concern. PMID:29244829
Trust in online prescription drug information among internet users: the impact on information search behavior after exposure to direct-to-consumer advertising.

PubMed

Menon, Ajit M; Deshpande, Aparna D; Perri, Matthew; Zinkhan, George M

2002-01-01

The proliferation of both manufacturer-controlled and independent medication-related websites has aroused concern among consumers and policy-makers concerning the trustworthiness of Web-based drug information. The authors examine consumers' trust in on-line prescription drug information and its influence on information search behavior. The study design involves a retrospective analysis of data from a 1998 national survey. The findings reveal that trust in drug information from traditional media sources such as television and newspapers transfers to the domain of the Internet. Furthermore, a greater trust in on-line prescription drug information stimulates utilization of the Internet for information search after exposure to prescription drug advertising.
Combination of Osthole and Cisplatin Against Rhabdomyosarcoma TE671 Cells Yielded Additive Pharmacologic Interaction by Means of Isobolographic Analysis.

PubMed

Jarząb, Agata; Łuszczki, Jarogniew; Guz, Małgorzata; Skalicka-Woźniak, Krystyna; Hałasa, Marta; Smok-Kalwat, Jolanta; Polberg, Krzysztof; Stepulak, Andrzej

2018-01-01

Osthole is a simple coumarin that has been found to have anticancer, anti-inflammatory, antiviral, anticoagulant, anticonvulsant and antiallergic activities. The aim of this study was to analyze the combined anti-proliferative effect of cisplatin (CDDP) and osthole on a rhabdomyosarcoma cell line, and assess the pharmacology of drug-drug interaction between these drugs using isobolographic analysis. The anticancer actions of osthole in combination with CDDP were evaluated using the tetrazolium dye-based MTT cell proliferation assay. Osthole and CDDP applied together augmented their anti-cancer activities and yielded an additive type of pharmacologic interaction by means of isobolographic analysis. Combined therapy using osthole and cisplatin could be suggested as a potential chemotherapy regimen against rhabdomyosarcoma. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
Quantitative analysis of drug distribution by ambient mass spectrometry imaging method with signal extinction normalization strategy and inkjet-printing technology.

PubMed

Luo, Zhigang; He, Jingjing; He, Jiuming; Huang, Lan; Song, Xiaowei; Li, Xin; Abliz, Zeper

2018-03-01

Quantitative mass spectrometry imaging (MSI) is a robust approach that provides both quantitative and spatial information for drug candidates' research. However, because of complicated signal suppression and interference, acquiring accurate quantitative information from MSI data remains a challenge, especially for whole-body tissue sample. Ambient MSI techniques using spray-based ionization appear to be ideal for pharmaceutical quantitative MSI analysis. However, it is more challenging, as it involves almost no sample preparation and is more susceptible to ion suppression/enhancement. Herein, based on our developed air flow-assisted desorption electrospray ionization (AFADESI)-MSI technology, an ambient quantitative MSI method was introduced by integrating inkjet-printing technology with normalization of the signal extinction coefficient (SEC) using the target compound itself. The method utilized a single calibration curve to quantify multiple tissue types. Basic blue 7 and an antitumor drug candidate (S-(+)-deoxytylophorinidine, CAT) were chosen to initially validate the feasibility and reliability of the quantitative MSI method. Rat tissue sections (heart, kidney, and brain) administered with CAT was then analyzed. The quantitative MSI analysis results were cross-validated by LC-MS/MS analysis data of the same tissues. The consistency suggests that the approach is able to fast obtain the quantitative MSI data without introducing interference into the in-situ environment of the tissue sample, and is potential to provide a high-throughput, economical and reliable approach for drug discovery and development. Copyright © 2017 Elsevier B.V. All rights reserved.
The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life

PubMed Central

Chen, Lei; Lu, Jing; Kong, XiangYin; Huang, Tao; Li, HaiPeng

2016-01-01

A drug’s biological half-life is defined as the time required for the human body to metabolize or eliminate 50% of the initial drug dosage. Correctly measuring the half-life of a given drug is helpful for the safe and accurate usage of the drug. In this study, we investigated which gene ontology (GO) terms and biological pathways were highly related to the determination of drug half-life. The investigated drugs, with known half-lives, were analyzed based on their enrichment scores for associated GO terms and KEGG pathways. These scores indicate which GO terms or KEGG pathways the drug targets. The feature selection method, minimum redundancy maximum relevance, was used to analyze these GO terms and KEGG pathways and to identify important GO terms and pathways, such as sodium-independent organic anion transmembrane transporter activity (GO:0015347), monoamine transmembrane transporter activity (GO:0008504), negative regulation of synaptic transmission (GO:0050805), neuroactive ligand-receptor interaction (hsa04080), serotonergic synapse (hsa04726), and linoleic acid metabolism (hsa00591), among others. This analysis confirmed our results and may show evidence for a new method in studying drug half-lives and building effective computational methods for the prediction of drug half-lives. PMID:27780226
Biochemistry and biomedicine of quantum dots: from biodetection to bioimaging, drug discovery, diagnostics, and therapy.

PubMed

Yao, Jun; Li, Pingfan; Li, Lin; Yang, Mei

2018-07-01

According to recent research, nanotechnology based on quantum dots (QDs) has been widely applied in the field of bioimaging, drug delivery, and drug analysis. Therefore, it has become one of the major forces driving basic and applied research. The application of nanotechnology in bioimaging has been of concern. Through in vitro labeling, it was found that luminescent QDs possess many properties such as narrow emission, broad UV excitation, bright fluorescence, and high photostability. The QDs also show great potential in whole-body imaging. The QDs can be combined with biomolecules, and hence, they can be used for targeted drug delivery and diagnosis. The characteristics of QDs make them useful for application in pharmacy and pharmacology. This review focuses on various applications of QDs, especially in imaging, drug delivery, pharmaceutical analysis, photothermal therapy, biochips, and targeted surgery. Finally, conclusions are made by providing some critical challenges and a perspective of how this field can be expected to develop in the future. Quantum dots (QDs) is an emerging field of interdisciplinary subject that involves physics, chemistry, materialogy, biology, medicine, and so on. In addition, nanotechnology based on QDs has been applied in depth in biochemistry and biomedicine. Some forward-looking fields emphatically reflected in some extremely vital areas that possess inspiring potential applicable prospects, such as immunoassay, DNA analysis, biological monitoring, drug discovery, in vitro labelling, in vivo imaging, and tumor target are closely connected to human life and health and has been the top and forefront in science and technology to date. Furthermore, this review has not only involved the traditional biochemical detection but also particularly emphasized its potential applications in life science and biomedicine. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

“GETTING HIGH AND GETTING BY”: DIMENSIONS OF DRUG SELLING BEHAVIORS AMONG AMERICAN MEXICAN GANG MEMBERS IN SOUTH TEXAS

PubMed Central

Valdez, Avelardo; Sifaneck, Stephen J.

2010-01-01

This article discerns the role that Mexican American gang members play in drug markets, and the relationship between gang members’drug use and drug selling in South Texas. A four-part typology based on the two dimensions of gang type and gang member emerged from this qualitative analysis of 160 male gang members: Homeboys, Hustlers, Slangers, and Ballers. Major findings include the following: (1) many gang members are user/sellers and are not profit-oriented dealers, (2) gangs commonly do extend “protection” to drug-selling members, and (3) proximity to Mexican drug markets, adult prison gangs, and criminal family members may play important roles in whether these gang members have access and the profit potential to actually deal drugs. This research contributes to our complex intersections between gangs, drug using, and drug selling. PMID:21218191
The application of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the stratum corneum.

PubMed

Goh, Choon Fu; Craig, Duncan Q M; Hadgraft, Jonathan; Lane, Majella E

2017-02-01

Drug permeation through the intercellular lipids, which pack around and between corneocytes, may be enhanced by increasing the thermodynamic activity of the active in a formulation. However, this may also result in unwanted drug crystallisation on and in the skin. In this work, we explore the combination of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the skin. Ex vivo permeation studies of saturated solutions of diclofenac sodium (DF Na) in two vehicles, propylene glycol (PG) and dimethyl sulphoxide (DMSO), were carried out in porcine ear skin. Tape stripping and ATR-FTIR spectroscopy were conducted simultaneously to collect spectral data as a function of skin depth. Multivariate data analysis was applied to visualise and categorise the spectral data in the region of interest (1700-1500cm -1 ) containing the carboxylate (COO - ) asymmetric stretching vibrations of DF Na. Spectral data showed the redshifts of the COO - asymmetric stretching vibrations for DF Na in the solution compared with solid drug. Similar shifts were evident following application of saturated solutions of DF Na to porcine skin samples. Multivariate data analysis categorised the spectral data based on the spectral differences and drug crystallisation was found to be confined to the upper layers of the skin. This proof-of-concept study highlights the utility of ATR-FTIR spectroscopy in combination with multivariate data analysis as a simple and rapid approach in the investigation of drug deposition in the skin. The approach described here will be extended to the study of other actives for topical application to the skin. Copyright © 2016 Elsevier B.V. All rights reserved.
Measurement of drug-target engagement in live cells by two-photon fluorescence anisotropy imaging.

PubMed

Vinegoni, Claudio; Fumene Feruglio, Paolo; Brand, Christian; Lee, Sungon; Nibbs, Antoinette E; Stapleton, Shawn; Shah, Sunil; Gryczynski, Ignacy; Reiner, Thomas; Mazitschek, Ralph; Weissleder, Ralph

2017-07-01

The ability to directly image and quantify drug-target engagement and drug distribution with subcellular resolution in live cells and whole organisms is a prerequisite to establishing accurate models of the kinetics and dynamics of drug action. Such methods would thus have far-reaching applications in drug development and molecular pharmacology. We recently presented one such technique based on fluorescence anisotropy, a spectroscopic method based on polarization light analysis and capable of measuring the binding interaction between molecules. Our technique allows the direct characterization of target engagement of fluorescently labeled drugs, using fluorophores with a fluorescence lifetime larger than the rotational correlation of the bound complex. Here we describe an optimized protocol for simultaneous dual-channel two-photon fluorescence anisotropy microscopy acquisition to perform drug-target measurements. We also provide the necessary software to implement stream processing to visualize images and to calculate quantitative parameters. The assembly and characterization part of the protocol can be implemented in 1 d. Sample preparation, characterization and imaging of drug binding can be completed in 2 d. Although currently adapted to an Olympus FV1000MPE microscope, the protocol can be extended to other commercial or custom-built microscopes.
Mathematical modeling of efficacy and safety for anticancer drugs clinical development.

PubMed

Lavezzi, Silvia Maria; Borella, Elisa; Carrara, Letizia; De Nicolao, Giuseppe; Magni, Paolo; Poggesi, Italo

2018-01-01

Drug attrition in oncology clinical development is higher than in other therapeutic areas. In this context, pharmacometric modeling represents a useful tool to explore drug efficacy in earlier phases of clinical development, anticipating overall survival using quantitative model-based metrics. Furthermore, modeling approaches can be used to characterize earlier the safety and tolerability profile of drug candidates, and, thus, the risk-benefit ratio and the therapeutic index, supporting the design of optimal treatment regimens and accelerating the whole process of clinical drug development. Areas covered: Herein, the most relevant mathematical models used in clinical anticancer drug development during the last decade are described. Less recent models were considered in the review if they represent a standard for the analysis of certain types of efficacy or safety measures. Expert opinion: Several mathematical models have been proposed to predict overall survival from earlier endpoints and validate their surrogacy in demonstrating drug efficacy in place of overall survival. An increasing number of mathematical models have also been developed to describe the safety findings. Modeling has been extensively used in anticancer drug development to individualize dosing strategies based on patient characteristics, and design optimal dosing regimens balancing efficacy and safety.
DNetDB: The human disease network database based on dysfunctional regulation mechanism.

PubMed

Yang, Jing; Wu, Su-Juan; Yang, Shao-You; Peng, Jia-Wei; Wang, Shi-Nuo; Wang, Fu-Yan; Song, Yu-Xing; Qi, Ting; Li, Yi-Xue; Li, Yuan-Yuan

2016-05-21

Disease similarity study provides new insights into disease taxonomy, pathogenesis, which plays a guiding role in diagnosis and treatment. The early studies were limited to estimate disease similarities based on clinical manifestations, disease-related genes, medical vocabulary concepts or registry data, which were inevitably biased to well-studied diseases and offered small chance of discovering novel findings in disease relationships. In other words, genome-scale expression data give us another angle to address this problem since simultaneous measurement of the expression of thousands of genes allows for the exploration of gene transcriptional regulation, which is believed to be crucial to biological functions. Although differential expression analysis based methods have the potential to explore new disease relationships, it is difficult to unravel the upstream dysregulation mechanisms of diseases. We therefore estimated disease similarities based on gene expression data by using differential coexpression analysis, a recently emerging method, which has been proved to be more potential to capture dysfunctional regulation mechanisms than differential expression analysis. A total of 1,326 disease relationships among 108 diseases were identified, and the relevant information constituted the human disease network database (DNetDB). Benefiting from the use of differential coexpression analysis, the potential common dysfunctional regulation mechanisms shared by disease pairs (i.e. disease relationships) were extracted and presented. Statistical indicators, common disease-related genes and drugs shared by disease pairs were also included in DNetDB. In total, 1,326 disease relationships among 108 diseases, 5,598 pathways, 7,357 disease-related genes and 342 disease drugs are recorded in DNetDB, among which 3,762 genes and 148 drugs are shared by at least two diseases. DNetDB is the first database focusing on disease similarity from the viewpoint of gene regulation mechanism. It provides an easy-to-use web interface to search and browse the disease relationships and thus helps to systematically investigate etiology and pathogenesis, perform drug repositioning, and design novel therapeutic interventions.Database URL: http://app.scbit.org/DNetDB/ #.
An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.
What is the evidence behind the evidence-base? The premature death of block-replace antithyroid drug regimens for Graves' disease.

PubMed

Razvi, Salman; Vaidya, Bijay; Perros, Petros; Pearce, Simon H S

2006-06-01

Block-replace and titration antithyroid drug regimens both give similar rates of medium- to long-term remission of hyperthyroid Graves' disease. Recent meta-analysis, however, has suggested that titration regimens may be preferable owing to a higher rate of adverse events seen in the block-replace arms of published comparative studies. This article critically re-evaluates the evidence upon which these meta-analyses were based. We suggest that there is little objective evidence that is pertinent to current clinical practice to separate block-replace from titration antithyroid drug regimens and that both remain satisfactory approaches to the medical management of hyperthyroid Graves' disease.
Building a Web-based drug ordering system for hospitals: from requirements engineering to prototyping.

PubMed

Hübner, U; Klein, F; Hofstetter, J; Kammeyer, G; Seete, H

2000-01-01

Web-based drug ordering allows a growing number of hospitals without pharmacy to communicate seamlessly with their external pharmacy. Business process analysis and object oriented modelling performed together with the users at a pilot hospital resulted in a comprehensive picture of the user and business requirements for electronic drug ordering. The user requirements were further validated with the help of a software prototype. In order to capture the needs of a large number of users CAP10, a new method making use of pre-built models, is proposed. Solutions for coping with the technical requirements (interfacing the business software at the pharmacy) and with the legal requirements (signing the orders) are presented.
Overcoming Cost Implications of Mutational Analysis in Patients with Gastrointestinal Stromal Tumors: A Pragmatic Approach.

PubMed

Schöffski, Patrick; Wozniak, Agnieszka; Schöffski, Oliver; van Eycken, Liesbet; Debiec-Rychter, Maria

2016-01-01

Genetic analysis of tissue derived from patients with advanced gastrointestinal stromal tumors (GISTs) is not uniformly applied on a national and international level, even though mutational data can provide clinically relevant prognostic and predictive information, especially in patients qualifying for treatment with expensive targeted agents. The current article describes the rationale for genetic testing of GIST tissue, looks at financial implications associated with such analysis and speculates on potential cost savings introduced by routine mutational testing and tailored use of tyrosine kinase inhibitors based on genotyping. This work is based on a hypothetical analysis of epidemiological data, drug costs, reimbursement criteria and market research figures. The cost burden for routine genotyping of important genes in GISTs, especially in patients at high risk for relapse after primary surgery and in advanced, inoperable metastatic disease, is relatively low. The early identification of GISTs with primary resistance mutations should be the basis for personalized GIST treatment and reimbursement of drugs. As illustrated by Belgian figures, the exclusive use of a drug such as imatinib in patients who are likely to benefit from the agent based on genetic information can lead to significant cost savings, which outweigh the costs for testing. Mutational analysis of GIST should be considered early in all patients at risk for relapse after curative surgery and in the case of advanced, inoperable, metastatic disease. The costs for the actual genotyping should not be used as an argument against profiling of the tumor. The adjuvant and palliative systemic treatment of GISTs should be personalized based on the genotype and other known prognostic and predictive factors. Reimbursement criteria for essential agents such as imatinib should be adapted accordingly. © 2016 S. Karger GmbH, Freiburg.
Spray-dried casein-based micelles as a vehicle for solubilization and controlled delivery of flutamide: formulation, characterization, and in vivo pharmacokinetics.

PubMed

Elzoghby, Ahmed O; Helmy, Maged W; Samy, Wael M; Elgindy, Nazik A

2013-08-01

Novel casein (CAS)-based micelles loaded with the poorly soluble anti-cancer drug, flutamide (FLT), were successfully developed in a powdered form via spray-drying technique. Genipin (GNP) was used to crosslink CAS micelles as demonstrated by color variation of the micelles. Drug solubilization was enhanced by incorporation within the hydrophobic micellar core which was confirmed by solubility study and UV spectra. Spherical core-shell micelles were obtained with a particle size below 100 nm and zeta potential around -30 mV. At low drug loading, FLT was totally incorporated within micellar core as revealed by thermal analysis. However, at higher loading, excess non-incorporated drug at micelle surface caused a significant reduction in the surface charge density. Turbidity measurements demonstrated the high physical stability of micelles for 2 weeks dependent on GNP-crosslinking degree. In a dry powdered form, the micelles were stable for 6 months with no significant changes in drug content or particle size. A sustained drug release from CAS micelles up to 5 days was observed. After i.v. administration into rats, CAS micelles exhibited a prolonged plasma circulation of FLT compared to drug solution. Furthermore, a more prolonged drug systemic circulation was observed for GNP-crosslinked micelles. Overall, this study reports the application of spray-dried natural protein-based micelles for i.v. delivery of hydrophobic anti-cancer drugs such as FLT. Copyright © 2013 Elsevier B.V. All rights reserved.
Will Decision Support in Medications Order Entry Save Money? A Return On Investment Analysis of the Case of the Hong Kong Hospital Authority

PubMed Central

Fung, Kin Wah; Vogel, Lynn Harold

2003-01-01

The computerized medications order entry system currently used in the public hospitals of Hong Kong does not have decision support features. Plans are underway to add decision support to this system to alert physicians on drug-allergy conflicts, drug-lab result conflicts, drug-drug interactions and atypical dosages. A return on investment analysis is done on this enhancement, both as an examination of whether there is a positive return on the investment and as a contribution to the ongoing discussion of the use of return on investment models in health care information technology investments. It is estimated that the addition of decision support will reduce adverse drug events by 4.2 – 8.4%. Based on this estimate, a total net saving of $44,000 – $586,000 is expected over five years. The breakeven period is estimated to be between two to four years. PMID:14728171
Development and validation of a multiclass method for the quantification of veterinary drug residues in honey and royal jelly by liquid chromatography-tandem mass spectrometry.

PubMed

Jin, Yue; Zhang, Jinzhen; Zhao, Wen; Zhang, Wenwen; Wang, Lin; Zhou, Jinhui; Li, Yi

2017-04-15

The aim of this study was to develop an analytical method for the analysis of a wide range of veterinary drugs in honey and royal jelly. A modified sample preparation procedure based on the quick, easy, cheap, effective, rugged and safe (QuEChERS) method was developed, followed by liquid chromatography tandem mass spectrometry determination. Use of the single sample preparation method for analysis of 42 veterinary drugs becomes more valuable because honey and royal jelly belong to completely different complex matrices. Another main advantage of the proposed method is its ability to identify and quantify 42 veterinary drugs with higher sensitivity than reference methods of China. This work has shown that the reported method was demonstrated to be convenient and reliable for the quick monitoring of veterinary drugs in honey and royal jelly samples. Copyright © 2016 Elsevier Ltd. All rights reserved.
Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

PubMed

Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.
Physicians' decision process for drug prescription and the impact of pharmaceutical marketing mix instruments.

PubMed

Campo, Katia; De Staebel, Odette; Gijsbrechts, Els; van Waterschoot, Walter

2005-01-01

This paper provides an in-depth, qualitative analysis of the physicians' decision process for drug prescription. Drugs in the considered therapeutic classes are mainly prescribed by specialists, treating patients with obligatory medical insurance, for a prolonged period of time. The research approach is specifically designed to capture the full complexity and sensitive nature of the physician's choice behavior, which appears to be more hybrid and less rational in nature than is often assumed in quantitative, model-based analyses of prescription behavior. Several interesting findings emerge from the analysis: (i) non-compensatory decision rules seem to dominate the decision process, (ii) consideration sets are typically small and change-resistant, (iii) drug cost is not a major issue for most physicians, (iv) detailing remains one of the most powerful pharmaceutical marketing instruments and is highly appreciated as a valuable and quick source of information, and (v) certain types of non-medical marketing incentives (such as free conference participation) may in some situations also influence drug choices.
Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

PubMed Central

Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032
Clinical Evidence Supporting US Food and Drug Administration Approval of Otolaryngologic Prescription Drug Indications, 2005-2014.

PubMed

Rathi, Vinay K; Wang, Bo; Ross, Joseph S; Downing, Nicholas S; Kesselheim, Aaron S; Gray, Stacey T

2017-04-01

Objective The US Food and Drug Administration (FDA) approves indications for prescription drugs based on premarket pivotal clinical studies designed to demonstrate safety and efficacy. We characterized the pivotal studies supporting FDA approval of otolaryngologic prescription drug indications. Study Design Retrospective cross-sectional analysis. Setting Publicly available FDA documents. Subjects Recently approved (2005-2014) prescription drug indications for conditions treated by otolaryngologists or their multidisciplinary teams. Drugs could be authorized for treatment of otolaryngologic disease upon initial approval (original indications) or thereafter via supplemental applications (supplemental indications). Methods Pivotal studies were categorized by enrollment, randomization, blinding, comparator type, and primary endpoint. Results Between 2005 and 2014, the FDA approved 48 otolaryngologic prescription drug indications based on 64 pivotal studies, including 21 original indications (19 drugs, 31 studies) and 27 supplemental indications (18 drugs, 33 studies). Median enrollment was 299 patients (interquartile range, 198-613) for original indications and 197 patients (interquartile range, 64-442) for supplemental indications. Most indications were supported by ≥1 randomized study (original: 20/21 [95%], supplemental: 21/27 [78%]) and ≥1 double-blinded study (original: 14/21 [67%], supplemental: 17/27 [63%]). About half of original indications (9/21 [43%]) and one-quarter of supplemental indications (7/27 [26%]) were supported by ≥1 active-controlled study. Nearly half (original: 8/21 [38%], supplemental: 14/27 [52%]) of all indications were approved based exclusively on studies using surrogate markers as primary endpoints. Conclusion The quality of clinical evidence supporting FDA approval of otolaryngologic prescription drug indications varied widely. Otolaryngologists should consider limitations in premarket evidence when helping patients make informed treatment decisions about newly approved drugs.
Metabolic profiling using HPLC allows classification of drugs according to their mechanisms of action in HL-1 cardiomyocytes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strigun, Alexander; Wahrheit, Judith; Beckers, Simone

Along with hepatotoxicity, cardiotoxic side effects remain one of the major reasons for drug withdrawals and boxed warnings. Prediction methods for cardiotoxicity are insufficient. High content screening comprising of not only electrophysiological characterization but also cellular molecular alterations are expected to improve the cardiotoxicity prediction potential. Metabolomic approaches recently have become an important focus of research in pharmacological testing and prediction. In this study, the culture medium supernatants from HL-1 cardiomyocytes after exposure to drugs from different classes (analgesics, antimetabolites, anthracyclines, antihistamines, channel blockers) were analyzed to determine specific metabolic footprints in response to the tested drugs. Since most drugsmore » influence energy metabolism in cardiac cells, the metabolite 'sub-profile' consisting of glucose, lactate, pyruvate and amino acids was considered. These metabolites were quantified using HPLC in samples after exposure of cells to test compounds of the respective drug groups. The studied drug concentrations were selected from concentration response curves for each drug. The metabolite profiles were randomly split into training/validation and test set; and then analysed using multivariate statistics (principal component analysis and discriminant analysis). Discriminant analysis resulted in clustering of drugs according to their modes of action. After cross validation and cross model validation, the underlying training data were able to predict 50%-80% of conditions to the correct classification group. We show that HPLC based characterisation of known cell culture medium components is sufficient to predict a drug's potential classification according to its mode of action.« less
Adverse Drug Event Causality Analysis (ADECA): A Process for Evaluating Evidence and Assigning Drugs to Risk Categories for Sudden Death.

PubMed

Woosley, Raymond L; Romero, Klaus; Heise, Craig W; Gallo, Tyler; Tate, Jared; Woosley, Raymond David; Ward, Sophie

2017-06-01

Growing evidence indicates that many drugs have the ability to cause a potentially lethal cardiac arrhythmia, torsades de pointes (TdP). This necessitates the development of a compilation of drugs that have this potential toxicity. Such a list is helpful in identifying the etiology of TdP in patients taking multiple drugs and assists decision making by those caring for patients at high risk of TdP. The Arizona Center for Education and Research on Therapeutics (AZCERT) has developed a process to standardize the identification of drugs and place them in risk categories for their clinical ability to cause TdP and QT prolongation. AZCERT's Adverse Drug Event Causality Analysis (ADECA) utilizes 16 types of data drawn from four sources to compile an open-source knowledge base, QTdrugs, which is maintained on the CredibleMeds.org website. Because the evidence for most drugs is incomplete, the ADECA process is used to place drugs into one of three categories that represent different levels of certainty: known TdP risk, possible TdP risk, and conditional TdP risk. Each category has strict evidentiary requirements for clinical evidence of TdP and/or QT prolongation. These are described in this paper. Because evidence can evolve over time, the ADECA process includes the continuous gathering and analysis of newly emerging evidence to revise the lists. The QTdrugs lists have proven to be a valued, readily available, commercial influence-free resource for healthcare providers, patients, researchers, and authors of consensus guidelines for the safe use of medicines.
78 FR 64735 - Current Good Manufacturing Practice and Hazard Analysis and Risk-Based Preventive Controls for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-29

...The Food and Drug Administration (FDA) is proposing regulations for domestic and foreign facilities that are required to register under the Federal Food, Drug, and Cosmetic Act (the FD&C Act) to establish requirements for current good manufacturing practice in manufacturing, processing, packing, and holding of animal food. FDA also is proposing regulations to require that certain facilities establish and implement hazard analysis and risk-based preventive controls for food for animals. FDA is taking this action to provide greater assurance that animal food is safe and will not cause illness or injury to animals or humans and is intended to build an animal food safety system for the future that makes modern, science and risk-based preventive controls the norm across all sectors of the animal food system.
Dispersive Solid Phase Extraction for the Analysis of Veterinary Drugs Applied to Food Samples: A Review

PubMed Central

Islas, Gabriela; Hernandez, Prisciliano

2017-01-01

To achieve analytical success, it is necessary to develop thorough clean-up procedures to extract analytes from the matrix. Dispersive solid phase extraction (DSPE) has been used as a pretreatment technique for the analysis of several compounds. This technique is based on the dispersion of a solid sorbent in liquid samples in the extraction isolation and clean-up of different analytes from complex matrices. DSPE has found a wide range of applications in several fields, and it is considered to be a selective, robust, and versatile technique. The applications of dispersive techniques in the analysis of veterinary drugs in different matrices involve magnetic sorbents, molecularly imprinted polymers, carbon-based nanomaterials, and the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method. Techniques based on DSPE permit minimization of additional steps such as precipitation, centrifugation, and filtration, which decreases the manipulation of the sample. In this review, we describe the main procedures used for synthesis, characterization, and application of this pretreatment technique and how it has been applied to food analysis. PMID:29181027

Finite element analysis of hollow out-of-plane HfO2 microneedles for transdermal drug delivery applications.

PubMed

Zhang, Yong-Hua; A Campbell, Stephen; Karthikeyan, Sreejith

2018-02-17

Transdermal drug delivery (TDD) based on microneedles is an excellent approach due to its advantages of both traditional transdermal patch and hypodermic syringes. In this paper, the fabrication method of hollow out-of-layer hafnium oxide (HfO 2 ) microneedles mainly based on deep reactive ion etching of silicon and atomic layer deposition of HfO 2 is described, and the finite element analysis of the microneedles based on ANSYS software is also presented. The fabrication process is simplified by using a single mask. The finite element analysis of a single microneedle shows that the flexibility of the microneedles can be easily adjusted for various applications. The finite element analysis of a 3 × 3 HfO 2 microneedle array applied on the skin well explains the "bed of nail" effect, i.e., the skin is not liable to be pierced when the density of microneedles in array increases. The presented research work here provides useful information for design optimization of HfO 2 microneedles used for TDD applications.
Reverse translation of adverse event reports paves the way for de-risking preclinical off-targets

PubMed Central

Maciejewski, Mateusz; Lounkine, Eugen; Whitebread, Steven; Farmer, Pierre; DuMouchel, William; Shoichet, Brian K; Urban, Laszlo

2017-01-01

The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events. Our analysis exposed key idiosyncrasies in FAERS, for example reports of thalidomide causing a deadly ADR when used against myeloma, a likely result of the disease itself; multiplications of the same report, unjustifiably increasing its importance; correlation of reported ADRs with public events, regulatory announcements, and with publications. Comparing the pharmacological, pharmacokinetic, and clinical ADR profiles of methylphenidate, aripiprazole, and risperidone, and of kinase drugs targeting the VEGF receptor, demonstrates how underlying molecular mechanisms can emerge from ADR co-analysis. The precautions and methods we describe may enable investigators to avoid confounding chemistry-based associations and reporting biases in FAERS, and illustrate how comparative analysis of ADRs can reveal underlying mechanisms. DOI: http://dx.doi.org/10.7554/eLife.25818.001 PMID:28786378
Mechlorethamine-based drug structures for intervention of central nervous system tumors.

PubMed

Bartzatt, Ronald

2013-06-01

Tumors of the central nervous system are the third most common type of childhood cancers. Brain tumors occur in children and adults; however pediatric patients require a different treatment process. Thirteen drugs similar to mechlorethamine are analyzed in this study. These drugs possess molecular properties enabling substantial and successful access to tumors of the central nervous system. All drugs exhibit zero violations of the Rule of 5, which indicate favorable bioavailability. Ranges in Log P, formula weight, and polar surface area for these drugs are: 1.554 to 3.52, 156.06 to 460.45, and 3.238 Angstroms(2) to 45.471 Angstroms(2), respectively. Hierarchical cluster analysis determined that agents 7 and 12 are most similar to the parent compound mechlorethamine. The mean values of Log P, formula weight, polar surface area, and molecular volume are 2.25, 268.51, 16.57 Angstroms(2), and 227.01 Angstroms(3), respectively. Principal component analysis indicates that agents 7 and 12 are most similar to mechlorethamine and multiple regression analysis of molecular properties produced a model to enable the design of similar alkylating agents. Values of Log (Cbrain/Cblood) indicate these agents will have very high permeation into the central nervous system.
Development, validation and comparison of NIR and Raman methods for the identification and assay of poor-quality oral quinine drops.

PubMed

Mbinze, J K; Sacré, P-Y; Yemoa, A; Mavar Tayey Mbay, J; Habyalimana, V; Kalenda, N; Hubert, Ph; Marini, R D; Ziemons, E

2015-01-01

Poor quality antimalarial drugs are one of the public's major health problems in Africa. The depth of this problem may be explained in part by the lack of effective enforcement and the lack of efficient local drug analysis laboratories. To tackle part of this issue, two spectroscopic methods with the ability to detect and to quantify quinine dihydrochloride in children's oral drops formulations were developed and validated. Raman and near infrared (NIR) spectroscopy were selected for the drug analysis due to their low cost, non-destructive and rapid characteristics. Both of the methods developed were successfully validated using the total error approach in the range of 50-150% of the target concentration (20%W/V) within the 10% acceptance limits. Samples collected on the Congolese pharmaceutical market were analyzed by both techniques to detect potentially substandard drugs. After a comparison of the analytical performance of both methods, it has been decided to implement the method based on NIR spectroscopy to perform the routine analysis of quinine oral drop samples in the Quality Control Laboratory of Drugs at the University of Kinshasa (DRC). Copyright © 2015 Elsevier B.V. All rights reserved.
Therapeutic non-adherence: a rational behavior revealing patient preferences?

PubMed

Lamiraud, Karine; Geoffard, Pierre-Yves

2007-11-01

This paper offers an indirect measure of patient welfare based on whether patients comply with the prescription they receive. Adherence behavior is supposed to reveal patients' subjective valuations of particular therapies. We write a simple theoretical model of patient adherence behavior, that reflects the trade-off between perceived costs and observed regimen efficacy. A discrete choice framework is then used for the estimation, i.e. the comparison of the incremental benefit of drug intake between two regimens. Consequently, the empirical analysis is based on the identification of patient and drug characteristics associated with adherence. The econometric approach is implemented through a bivariate panel two-equation simultaneous system studying jointly the factors associated with adherence and response to treatment. The data come from a randomized clinical trial conducted in France between 1999 and 2001 and comparing the efficacy of two tritherapy strategies in HIV disease. Both the theoretical and empirical results suggest that, for comparable clinical efficacy and toxicity levels, a higher adherence level is associated with higher patient welfare, thus adding valuable information to conclusions drawn by a mere biostatistical analysis. Therefore, from the perspective of the patient, the adherence-enhancing drug must be favored. Our results based on panel data also stress that unobserved patient characteristics account substantially for drug valuation and that the assessment evolves during the course of the treatment. Furthermore, we provide a new framework for the analysis of adherence data. The microeconometric framework highlights that non-adherence is an endogenous behavior, thus suggesting new ways for improving adherence. (c) 2007 John Wiley & Sons, Ltd.
OpenVigil FDA - Inspection of U.S. American Adverse Drug Events Pharmacovigilance Data and Novel Clinical Applications.

PubMed

Böhm, Ruwen; von Hehn, Leocadie; Herdegen, Thomas; Klein, Hans-Joachim; Bruhn, Oliver; Petri, Holger; Höcker, Jan

2016-01-01

Pharmacovigilance contributes to health care. However, direct access to the underlying data for academic institutions and individual physicians or pharmacists is intricate, and easily employable analysis modes for everyday clinical situations are missing. This underlines the need for a tool to bring pharmacovigilance to the clinics. To address these issues, we have developed OpenVigil FDA, a novel web-based pharmacovigilance analysis tool which uses the openFDA online interface of the Food and Drug Administration (FDA) to access U.S. American and international pharmacovigilance data from the Adverse Event Reporting System (AERS). OpenVigil FDA provides disproportionality analyses to (i) identify the drug most likely evoking a new adverse event, (ii) compare two drugs concerning their safety profile, (iii) check arbitrary combinations of two drugs for unknown drug-drug interactions and (iv) enhance the relevance of results by identifying confounding factors and eliminating them using background correction. We present examples for these applications and discuss the promises and limits of pharmacovigilance, openFDA and OpenVigil FDA. OpenVigil FDA is the first public available tool to apply pharmacovigilance findings directly to real-life clinical problems. OpenVigil FDA does not require special licenses or statistical programs.
Microsponges based novel drug delivery system for augmented arthritis therapy.

PubMed

Osmani, Riyaz Ali M; Aloorkar, Nagesh H; Ingale, Dipti J; Kulkarni, Parthasarathi K; Hani, Umme; Bhosale, Rohit R; Jayachandra Dev, Dandasi

2015-10-01

The motive behind present work was to formulate and evaluate gel containing microsponges of diclofenac diethylamine to provide prolonged release for proficient arthritis therapy. Quasi-emulsion solvent diffusion method was implied using Eudragit RS-100 and microsponges with varied drug-polymer ratios were prepared. For the sake of optimization, diverse factors affecting microparticles physical properties were too investigated. Microsponges were characterized by SEM, DSC, FT-IR, XRPD and particle size analysis, and evaluated for morphology, drug loading, in vitro drug release and ex vivo diffusion as well. There were no chemical interactions between drug and polymers used as revealed by compatibility studies outcomes. The drug polymer ratio reflected notable effect on drug content, encapsulation efficiency and particle size. SEM results revealed spherical microsponges with porous surface, and had 7.21 μm mean particle size. The microsponges were then incorporated in gel; which exhibited viscous modulus along with pseudoplastic behavior. In vitro drug release results depicted that microsponges with 1:2 drug-polymer ratio were more efficient to give extended drug release of 75.88% at the end of 8 h; while conventional formulation get exhausted incredibly earlier by releasing 81.11% drug at the end of 4 h only. Thus the formulated microsponge-based gel of diclofenac diethylamine would be a promising alternative to conventional therapy for safer and efficient treatment of arthritis and musculoskeletal disorders.
Community-based interventions to prevent fatal overdose from illegal drugs: a systematic review protocol.

PubMed

Okolie, Chukwudi; Evans, Bridie Angela; John, Ann; Moore, Chris; Russell, Daphne; Snooks, Helen

2015-11-03

Drug overdose is the most frequent cause of death among people who misuse illegal drugs. People who inject these drugs are 14-17 times more likely to die than their non-drug using peers. Various strategies to reduce drug-related deaths have failed to meet target reductions. Research into community-based interventions for preventing drug overdose deaths is promising. This review seeks to identify published studies describing community-based interventions and to evaluate their effectiveness at reducing drug overdose deaths. We will systematically search key electronic databases using a search strategy which groups terms into four facets: (1) Overdose event, (2) Drug classification, (3) Intervention and (4) Setting. Searches will be limited where possible to international literature published in English between 1998 and 2014. Data will be extracted by two independent reviewers using a predefined table adapted from the Cochrane Collaboration handbook. The quality of included studies will be evaluated using the Cochrane Collaboration's tool for assessing risk of bias. We will conduct a meta-analysis for variables which can be compared across studies, using statistical methods to control for heterogeneity where appropriate. Where clinical or statistical heterogeneity prevents a valid numerical synthesis, we will employ a narrative synthesis to describe community-based interventions, their delivery and use and how effectively they prevent fatal overdoses. We will publish findings from this systematic review in a peer-reviewed scientific journal and present results at national and international conferences. It will be disseminated electronically and in print. PROSPERO CRD42015017833. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Economic and policy analysis of university-based drug "detailing".

PubMed

Soumerai, S B; Avorn, J

1986-04-01

The cost-effectiveness of quality assurance programs is often poorly documented, especially for innovative approaches. The authors analyzed the economic effects of an experimental educational outreach program designed to reduce inappropriate drug prescribing, based on a four-state randomized controlled trial (N = 435 physicians). Primary care physicians randomized into the face-to-face group were offered two individualized educational sessions with clinical pharmacists, lasting an average of 18 minutes each, concerning optimal use of three drug groups that are often used inappropriately. After the program, expenditures for target drugs prescribed by these physicians to Medicaid patients decreased by 13%, compared with controls (P = 0.002); this effect was stable over three quarters. Implementation of this program for 10,000 physicians would lead to projected drug savings (to Medicaid only) of $2,050,000, compared with resource costs of $940,000. Net savings remain high, even after adjustment for use of substitution medications. Although there was a ninefold difference in average preintervention prescribing levels between the highest and lowest thirds of the sample, all groups reduced target drug expenditures at the same rate. Targeting of higher-volume prescribers would thus further raise the observed benefit-to-cost ratio from approximately 1.8 to at least 3.0. Net benefits would also increase further if non-Medicaid savings were added, or if the analysis included quality-of-care considerations. Although print materials alone may be marginally cost-effective, print plus face-to-face approaches offer greater net benefits. The authors conclude that a program of brief, face-to-face "detailing" visits conducted by academic rather than commercial sources can be a highly cost-effective method for improving drug therapy decisions. Such an approach makes possible the enhancement of physicians' clinical expertise without relying on restriction of drug choices.
The AGNP-TDM Expert Group Consensus Guidelines: focus on therapeutic monitoring of antidepressants

PubMed Central

Baumann, Pierre; Ulrich, Sven; Eckermann, Gabriel; Gerlach, Manfred; Kuss, Hans-Joachim; Laux, Gerd; Müller-Oerlinghausen, Bruno; Rao, Marie Luise; Riederer, Peter; Zernig, Gerald; Hiemke, Christoph

2005-01-01

Therapeutic drug monitoring (TDM) of psychotropic drugs such as antidepressants has been widely introduced for optimization of pharmacotherapy in psychiatric patients. The interdisciplinary TDM group of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) has worked out consensus guidelines with the aim of providing psychiatrists and TDM laboratories with a tool to optimize the use of TDM. Five research-based levels of recommendation were defined with regard to routine monitoring of drug plasma concentrations: (i) strongly recommended; (ii) recommended; (iii) useful; (iv) probably useful; and (v) not recommended. In addition, a list of indications that justify the use of TDM is presented, eg, control of compliance, lack of clinical response or adverse effects at recommended doses, drug interactions, pharmacovigilance programs, presence of a genetic particularity concerning drug metabolism, and children, adolescents, and elderly patients. For some drugs, studies on therapeutic ranges are lacking, but target ranges for clinically relevant plasma concentrations are presented for most drugs, based on pharmacokinetic studies reported in the literature. For many antidepressants, a thorough analysis of the literature on studies dealing with the plasma concentration–clinical effectiveness relationship allowed inclusion of therapeutic ranges of plasma concentrations. In addition, recommendations are made with regard to the combination of pharmacogenetic (phenotyping or genotyping) tests with TDM, Finally, practical instructions are given for the laboratory practitioners and the treating physicians how to use TDM: preparation of TDM, drug analysis, reporting and interpretation of results, and adequate use of information for patient treatment. TDM is a complex process that needs optimal interdisciplinary coordination of a procedure implicating patients, treating physicians, clinical pharmacologists, and clinical laboratory specialists. These consensus guidelines should be helpful for optimizing TDM of antidepressants. PMID:16156382
[Common mental disorders and the use of psychoactive drugs: the impact of socioeconomic conditions].

PubMed

Lima, Maria Cristina Pereira; Menezes, Paulo Rossi; Carandina, Luana; Cesar, Chester Luiz Galvão; Barros, Marilisa Berti de Azevedo; Goldbaum, Moisés

2008-08-01

To evaluate the influence of socioeconomic conditions on the association between common mental disorders and the use of health services and psychoactive drugs. This was a population-based cross-sectional study conducted in the city of Botucatu, Southeastern Brazil. The sample was probabilistic, stratified and cluster-based. Interviews with 1,023 subjects aged 15 years or over were held in their homes between 2001 and 2002. Common mental disorders were evaluated using the Self-Reporting Questionnaire (SRQ-20). The use of services was investigated in relation to the fortnight preceding the interview and the use of psychotropic drugs, over the preceding three days. Logistic regression was used for multivariable analysis, and the design effect was taken into consideration. Out of the whole sample, 13.4% (95% CI: 10.7;16.0) had sought health services over the fortnight preceding the interview. Seeking health services was associated with female gender (OR=2.0) and the presence of common mental disorders (OR=2.2). 13.3% of the sample (95% CI: 9.2;17.5) said they had used at least one psychotropic drug, especially antidepressives (5.0%) and benzodiazepines (3.1%). In the multivariable analysis, female gender and the presence of common mental disorders remained associated with the use of benzodiazepines. Per capita income presented a direct and independent association with the use of psychoactive drugs: the greater the income, the greater the use of these drugs was. Lower income was associated with the presence of common mental disorders, but not with the use of psychotropic drugs. The association of common mental disorders and the use of psychotropic drugs in relation to higher income strengthens the hypothesis that inequality of access to medical services exists among this population.
Monitoring compliance to therapy during addiction treatments by means of hair analysis for drugs and drug metabolites using capillary zone electrophoresis coupled to time-of-flight mass spectrometry.

PubMed

Gottardo, Rossella; Fanigliulo, Ameriga; Sorio, Daniela; Liotta, Eloisa; Bortolotti, Federica; Tagliaro, Franco

2012-03-10

Capillary electrophoresis coupled to time-of-flight mass spectrometry was used in the present work for the determination of therapeutic and abused drugs and their metabolites in the hair of subjects undergoing addiction treatments, in order to monitor their compliance to therapy. For this purpose a rapid, qualitative drug screening method was adopted based on capillary electrophoresis hyphenated with time-of-flight mass spectrometry, which had earlier been developed and validated for the forensic-toxicological analysis of hair, limitedly to illicit/abused drugs [1]. Sampling of hair was carried out in order to refer to a time window of about two months from the date of sampling (i.e. 2cm ca. from cortex). A single extraction procedure was applied, allowing the determination in the hair matrix of "drugs of abuse" referred to the past abuses, and therapeutic drugs prescribed in the detoxification program as well as their metabolites. Analyte identification was based on accurate mass measurements and comparison of isotope patterns, providing the most likely matching between accurate mass value and elemental formula. Small molecules (<500Da) of forensic and toxicological interest could be identified unambiguously using mass spectrometric conditions tailored to meet a mass accuracy ≤5ppm. In the present study, the proposed approach proved suitable for the rapid broad spectrum screening of hair samples, although needing further confirmation of results by using fragmentation mass spectrometry. Copyright Â© 2011 Elsevier Ireland Ltd. All rights reserved.
Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

PubMed

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.
Quantifying antiviral activity optimizes drug combinations against hepatitis C virus infection.

PubMed

Koizumi, Yoshiki; Ohashi, Hirofumi; Nakajima, Syo; Tanaka, Yasuhito; Wakita, Takaji; Perelson, Alan S; Iwami, Shingo; Watashi, Koichi

2017-02-21

With the introduction of direct-acting antivirals (DAAs), treatment against hepatitis C virus (HCV) has significantly improved. To manage and control this worldwide infectious disease better, the "best" multidrug treatment is demanded based on scientific evidence. However, there is no method available that systematically quantifies and compares the antiviral efficacy and drug-resistance profiles of drug combinations. Based on experimental anti-HCV profiles in a cell culture system, we quantified the instantaneous inhibitory potential (IIP), which is the logarithm of the reduction in viral replication events, for both single drugs and multiple-drug combinations. From the calculated IIP of 15 anti-HCV drugs from different classes [telaprevir, danoprevir, asunaprevir, simeprevir, sofosbuvir (SOF), VX-222, dasabuvir, nesbuvir, tegobuvir, daclatasvir, ledipasvir, IFN-α, IFN-λ1, cyclosporin A, and SCY-635], we found that the nucleoside polymerase inhibitor SOF had one of the largest potentials to inhibit viral replication events. We also compared intrinsic antiviral activities of a panel of drug combinations. Our quantification analysis clearly indicated an advantage of triple-DAA treatments over double-DAA treatments, with triple-DAA treatments showing enhanced antiviral activity and a significantly lower probability for drug resistance to emerge at clinically relevant drug concentrations. Our framework provides quantitative information to consider in designing multidrug strategies before costly clinical trials.
A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.

PubMed

Ekins, Sean; Freundlich, Joel S; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.
The right drug, but from whose perspective? A framework for analysing the structure and activities of drug and therapeutics committees.

PubMed

Hoffmann, Mikael

2013-05-01

During the last five decades drug and therapeutics committees (DTCs), have evolved from mainly hospital-based groups of experts in pharmacotherapy and drug logistics into an arena for healthcare professionals employing evidence-based methods of promoting rational drug use. The purpose of this study was to suggest a framework for analysing the structure and activities of DTCs. A literature search was carried out in the Medline, Cinahl and Web of Sciences databases for the period 1993-2012. A total of 207 articles were included. Based on these articles a framework for the analysis of the DTCs based on the role of the DTC, target groups, budget perspective and type of economic decisions could be suggested. In order to respond to future demands the DTCs will have to develop their skill in pharmacoeconomics. Their processes will have to be standardised and made more transparent in order to be better adapted to evidence-based decision-making. They will also have to embrace the possibilities created by electronic health records in both influencing the decisions of physicians, and in improving quality assurance programmes and longitudinal follow-up of drug therapy and outcomes. They will have to find new ways of interacting with the public and policy makers in order to get the resources needed for their work. Finally, they will have to handle the conflict among national, regional and local decision-making processes and the relationship between formularies and therapeutic guidelines.
A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested. PMID:25653841
FAPA mass spectrometry of designer drugs.

PubMed

Smoluch, Marek; Gierczyk, Blazej; Reszke, Edward; Babij, Michal; Gotszalk, Teodor; Schroeder, Grzegorz; Silberring, Jerzy

2016-01-01

Application of a flowing atmospheric-pressure afterglow ion source for mass spectrometry (FAPA-MS) for the analysis of designer drugs is described. In this paper, we present application of FAPA MS for identification of exemplary psychotropic drugs: JWH-122, 4BMC, Pentedrone, 3,4-DNNC and ETH-CAT. We have utilized two approaches for introducing samples into the plasma stream; first in the form of a methanolic aerosol from the nebulizer, and the second based on a release of vapors from the electrically heated crucible by thermal desorption. The analytes were ionized by FAPA and identified in the mass analyzer. The order of release of the compounds depends on their volatility. These methods offer fast and reliable structural information, without pre-separation, and can be an alternative to the Electron Impact, GC/MS, and ESI for fast analysis of designer-, and other psychoactive drugs. Copyright © 2015 Elsevier B.V. All rights reserved.
Fast Metabolic Response to Drug Intervention through Analysis on a Miniaturized, Highly Integrated Molecular Imaging System

PubMed Central

Wang, Jun; Hwang, Kiwook; Braas, Daniel; Dooraghi, Alex; Nathanson, David; Campbell, Dean O.; Gu, Yuchao; Sandberg, Troy; Mischel, Paul; Radu, Caius; Chatziioannou, Arion F.; Phelps, Michael E.; Christofk, Heather; Heath, James R.

2014-01-01

We report on a radiopharmaceutical imaging platform designed to capture the kinetics of cellular responses to drugs. Methods A portable in vitro molecular imaging system, comprised of a microchip and a beta-particle imaging camera, permits routine cell-based radioassays on small number of either suspension or adherent cells. We investigate the response kinetics of model lymphoma and glioblastoma cancer cell lines to [18F]fluorodeoxyglucose ([18F]FDG) uptake following drug exposure. Those responses are correlated with kinetic changes in the cell cycle, or with changes in receptor-tyrosine kinase signaling. Results The platform enables radioassays directly on multiple cell types, and yields results comparable to conventional approaches, but uses smaller sample sizes, permits a higher level of quantitation, and doesn’t require cell lysis. Conclusion The kinetic analysis enabled by the platform provides a rapid (~1 hour) drug screening assay. PMID:23978446
Assessment of the Impact of Scheduled Postmarketing Safety Summary Analyses on Regulatory Actions

PubMed Central

Sekine, S; Pinnow, EE; Wu, E; Kurtzig, R; Hall, M; Dal Pan, GJ

2016-01-01

In addition to standard postmarketing drug safety monitoring, Section 915 of the Food and Drug Administration Amendments Act of 2007 (FDAAA) requires the US Food and Drug Administration (FDA) to conduct a summary analysis of adverse event reports to identify risks of a drug or biologic product 18 months after product approval, or after 10,000 patients have used the product, whichever is later. We assessed the extent to which these analyses identified new safety signals and resultant safety-related label changes. Among 458 newly approved products, 300 were the subjects of a scheduled analysis; a new safety signal that resulted in a safety-related label change was found for 11 of these products. Less than 2% of 713 safety-related label changes were based on the scheduled analyses. Our study suggests that the safety summary analyses provide only marginal value over other pharmacovigilance activities. PMID:26853718

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

PubMed

Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Pharmacogenomics of the human ABC transporter ABCG2: from functional evaluation to drug molecular design

NASA Astrophysics Data System (ADS)

Ishikawa, Toshihisa; Tamura, Ai; Saito, Hikaru; Wakabayashi, Kanako; Nakagawa, Hiroshi

2005-10-01

In the post-genome-sequencing era, emerging genomic technologies are shifting the paradigm for drug discovery and development. Nevertheless, drug discovery and development still remain high-risk and high-stakes ventures with long and costly timelines. Indeed, the attrition of drug candidates in preclinical and development stages is a major problem in drug design. For at least 30% of the candidates, this attrition is due to poor pharmacokinetics and toxicity. Thus, pharmaceutical companies have begun to seriously re-evaluate their current strategies of drug discovery and development. In that light, we propose that a transport mechanism-based design might help to create new, pharmacokinetically advantageous drugs, and as such should be considered an important component of drug design strategy. Performing enzyme- and/or cell-based drug transporter, interaction tests may greatly facilitate drug development and allow the prediction of drug-drug interactions. We recently developed methods for high-speed functional screening and quantitative structure-activity relationship analysis to study the substrate specificity of ABC transporters and to evaluate the effect of genetic polymorphisms on their function. These methods would provide a practical tool to screen synthetic and natural compounds, and these data can be applied to the molecular design of new drugs. In this review article, we present an overview on the genetic polymorphisms of human ABC transporter ABCG2 and new camptothecin analogues that can circumvent AGCG2-associated multidrug resistance of cancer.
78 FR 6762 - Food and Drug Administration Food Safety Modernization Act: Proposed Rules To Establish Standards...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-31

... Manufacturing Practice and Hazard Analysis and Risk-Based Preventive Controls for Human Food; Public Meeting... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration 21 CFR Parts 1, 16, 106, 110, 112, 114, 117, 120, 123, 129, 179, and 211 [Docket Nos. FDA-2011-N-0920 and FDA-2011-N-0921] Food and...
78 FR 10107 - Food and Drug Administration Food Safety Modernization Act: Proposed Rules To Establish Standards...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-13

... Manufacturing Practice and Hazard Analysis and Risk-Based Preventive Controls for Human Food; Public Meeting... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration 21 CFR Parts 1, 16, 106, 110, 112, 114, 117, 120, 123, 129, 179, and 211 [Docket Nos. FDA-2011-N-0920 and FDA-2011-N-0921] Food and...
Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.
Increases and decreases in drug use attributed to housing status among street-involved youth in a Canadian setting.

PubMed

Cheng, Tessa; Wood, Evan; Nguyen, Paul; Kerr, Thomas; DeBeck, Kora

2014-04-10

Among a cohort of drug-using street-involved youth, we sought to identify the prevalence of reporting increases and decreases in illicit drug use due to their current housing status and to identify factors associated with reporting these changes. This longitudinal study was based on data collected between June 2008 and May 2012 from a prospective cohort of street-involved youth aged 14-26 in Vancouver, Canada. At semi-annual study follow-up visits, youth were asked if their drug use was affected by their housing status. Using generalized estimating equations, we identified factors associated with perceived increases and decreases in drug use attributed to housing status. Among our sample of 536 participants at baseline, 164 (31%) youth reported increasing their drug use due to their housing situation and 71 (13%) reported decreasing their drug use. In multivariate analysis, factors that were positively associated with perceived increases in drug use attributed to housing status included the following: being homeless, engaging in sex work and drug dealing. Regular employment was negatively associated with increasing drug use due to housing status. Among those who reported decreasing their drug use, only homelessness was significant in bivariate analysis. Perceived changes in drug use due to housing status were relatively common in this setting and were associated with being homeless and, among those who increased their drug use, engaging in risky income generation activities. These findings suggest that structural factors, particularly housing and economic opportunities, may be crucial interventions for reducing or limiting drug use among street-involved youth.
Increases and decreases in drug use attributed to housing status among street-involved youth in a Canadian setting

PubMed Central

2014-01-01

Background Among a cohort of drug-using street-involved youth, we sought to identify the prevalence of reporting increases and decreases in illicit drug use due to their current housing status and to identify factors associated with reporting these changes. Findings This longitudinal study was based on data collected between June 2008 and May 2012 from a prospective cohort of street-involved youth aged 14–26 in Vancouver, Canada. At semi-annual study follow-up visits, youth were asked if their drug use was affected by their housing status. Using generalized estimating equations, we identified factors associated with perceived increases and decreases in drug use attributed to housing status. Among our sample of 536 participants at baseline, 164 (31%) youth reported increasing their drug use due to their housing situation and 71 (13%) reported decreasing their drug use. In multivariate analysis, factors that were positively associated with perceived increases in drug use attributed to housing status included the following: being homeless, engaging in sex work and drug dealing. Regular employment was negatively associated with increasing drug use due to housing status. Among those who reported decreasing their drug use, only homelessness was significant in bivariate analysis. Conclusion Perceived changes in drug use due to housing status were relatively common in this setting and were associated with being homeless and, among those who increased their drug use, engaging in risky income generation activities. These findings suggest that structural factors, particularly housing and economic opportunities, may be crucial interventions for reducing or limiting drug use among street-involved youth. PMID:24721725
Application of the fragment molecular orbital method analysis to fragment-based drug discovery of BET (bromodomain and extra-terminal proteins) inhibitors.

PubMed

Ozawa, Motoyasu; Ozawa, Tomonaga; Ueda, Kazuyoshi

2017-06-01

The molecular interactions of inhibitors of bromodomains (BRDs) were investigated. BRDs are protein interaction modules that recognizing ε-N-acetyl-lysine (εAc-Lys) motifs found in histone tails and are promising protein-protein interaction (PPI) targets. First, we analyzed a peptide ligand containing εAc-Lys to evaluate native PPIs. We then analyzed tetrahydroquinazoline-6-yl-benzensulfonamide derivatives found by fragment-based drug design (FBDD) and examined their interactions with the protein compared with the peptide ligand in terms of the inter-fragment interaction energy. In addition, we analyzed benzodiazepine derivatives that are high-affinity ligands for BRDs and examined differences in the CH/π interactions of the amino acid residues. We further surveyed changes in the charges of the amino acid residues among individual ligands, performed pair interaction energy decomposition analysis and estimated the water profile within the ligand binding site. Thus, useful insights for drug design were provided. Through these analyses and considerations, we show that the FMO method is a useful drug design tool to evaluate the process of FBDD and to explore PPI inhibitors. Copyright © 2017 Elsevier Inc. All rights reserved.
Gathering and Exploring Scientific Knowledge in Pharmacovigilance

PubMed Central

Lopes, Pedro; Nunes, Tiago; Campos, David; Furlong, Laura Ines; Bauer-Mehren, Anna; Sanz, Ferran; Carrascosa, Maria Carmen; Mestres, Jordi; Kors, Jan; Singh, Bharat; van Mulligen, Erik; Van der Lei, Johan; Diallo, Gayo; Avillach, Paul; Ahlberg, Ernst; Boyer, Scott; Diaz, Carlos; Oliveira, José Luís

2013-01-01

Pharmacovigilance plays a key role in the healthcare domain through the assessment, monitoring and discovery of interactions amongst drugs and their effects in the human organism. However, technological advances in this field have been slowing down over the last decade due to miscellaneous legal, ethical and methodological constraints. Pharmaceutical companies started to realize that collaborative and integrative approaches boost current drug research and development processes. Hence, new strategies are required to connect researchers, datasets, biomedical knowledge and analysis algorithms, allowing them to fully exploit the true value behind state-of-the-art pharmacovigilance efforts. This manuscript introduces a new platform directed towards pharmacovigilance knowledge providers. This system, based on a service-oriented architecture, adopts a plugin-based approach to solve fundamental pharmacovigilance software challenges. With the wealth of collected clinical and pharmaceutical data, it is now possible to connect knowledge providers’ analysis and exploration algorithms with real data. As a result, new strategies allow a faster identification of high-risk interactions between marketed drugs and adverse events, and enable the automated uncovering of scientific evidence behind them. With this architecture, the pharmacovigilance field has a new platform to coordinate large-scale drug evaluation efforts in a unique ecosystem, publicly available at http://bioinformatics.ua.pt/euadr/. PMID:24349421
Mobile TNA system to detect explosives and drugs concealed in cars and trucks

NASA Astrophysics Data System (ADS)

Bendahan, Joseph; Gozani, Tsahi

1998-12-01

The drug problem in the U.S. is serious and efforts to fight it are constrained by the lack of adequate means to curb the inflow of smuggled narcotics into the country through cargo containers. Also, events such as the disastrous explosion in Oklahoma City, the IRA bombing in London, and the bombing of the U.S. military residence in Dharan make the development of new tools for the detection of explosives and drugs in vehicles imperative. Thermal neutron analysis (TNA) technology, developed for the detection of explosives in suitcases, and detection of landmines and unexploded ordnance is presently being applied to the nonintrusive detection of significant amounts of explosives and drugs concealed in cars, trucks and large cargo containers. TNA technology is based on the analysis of characteristic gamma rays emitted following thermal neutron capture. A TNA system can be used in a variety of operational scenarios, such as inspection before an unloaded cargo container from a spit is moved to temporary storage, inspection of trucks unloaded from a ferry, or inspection of vehicles parked close to Federal building or military bases. This paper will discuss the detection process and operational scenarios, and will present results from recent simulations and measurements.
The study of direct-to-consumer advertising for prescription drugs.

PubMed

Schommer, Jon C; Hansen, Richard A

2005-06-01

The objectives of this article are to (1) identify key methodological issues related to investigating the effects of direct-to-consumer advertising (DTCA) for prescription drugs, (2) highlight opportunities and challenges that these issues pose, and (3) provide suggestions to address these challenges and opportunities from a social and administrative pharmacy perspective. Through a review of existing literature and consultation with research colleagues, we identified 3 broad issues regarding the study of DTCA for prescription drugs: (1) the importance of problem formulation, (2) the role of health behavior and decision-making perspectives, and (3) data collection and data analysis challenges and opportunities. Based upon our findings, we developed recommendations for future research in this area. Clear problem formulation will be instructive for prioritizing research needs and for determining the role that health behavior and decision-making perspectives can serve in DTCA research. In addition, it appears that cluster bias, nonlinear relationships, mediating/moderating effects, time effects, acquiescent response, and case mix are particularly salient challenges for the DTCA research domain. We suggest that problem formulation, selection of sound theories upon which to base research, and data collection and data analysis challenges are key methodological issues related to investigating the effects of DTCA for prescription drugs.
Acquisition of second-line drug resistance and extensive drug resistance during recent transmission of Mycobacterium tuberculosis in rural China.

PubMed

Hu, Y; Mathema, B; Zhao, Q; Chen, L; Lu, W; Wang, W; Kreiswirth, B; Xu, B

2015-12-01

Multidrug-resistant tuberculosis (MDR-TB) is prevalent in countries with a high TB burden, like China. As little is known about the emergence and spread of second-line drug (SLD) -resistant TB, we investigate the emergence and transmission of SLD-resistant Mycobacterium tuberculosis in rural China. In a multi-centre population-based study, we described the bacterial population structure and the transmission characteristics of SLD-resistant TB using Spoligotyping in combination with genotyping based on 24-locus MIRU-VNTR (mycobacterial interspersed repetitive unit-variable-number tandem repeat) plus four highly variable loci for the Beijing family, in four rural Chinese regions with diverse geographic and socio-demographic characteristics. Transmission networks among genotypically clustered patients were constructed using social network analysis. Of 1332 M. tuberculosis patient isolates recovered, the Beijing family represented 74.8% of all isolates and an association with MDR and simultaneous resistance between first-line drugs and SLDs. The genotyping analysis revealed that 189 isolates shared MIRU-VNTR patterns in 78 clusters with clustering rate and recent transmission rate of 14.2% and 8.3%, respectively. Fifty-three SLD-resistant isolates were observed in 31 clusters, 30 of which contained the strains with different drug susceptibility profiles and genetic mutations. In conjunction with molecular data, socio-network analysis indicated a key role of Central Township in the transmission across a highly interconnected network where SLD resistance accumulation occurred during transmission. SLD-resistant M. tuberculosis has been spreading in rural China with Beijing family being the dominant strains. Primary transmission of SLD-resistant strains in the population highlights the importance of routine drug susceptibility testing and effective anti-tuberculosis regimens for drug-resistant TB. Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
The role of the media in the science-policy nexus. Some critical reflections based on an analysis of the Belgian drug policy debate (1996-2003).

PubMed

Tieberghien, Julie

2014-03-01

Drug policy is one of the most polarised subjects of public debate and media coverage, which frequently tend to be dramatic and event-centred. Although the role of the media in directing the drug discourse is widely acknowledged, limited research has been conducted in examining the particular role of the media in the science-policy nexus. We sought to determine how the (mis)representation of scientific knowledge in the media may, or may not, have an impact on the contribution of scientific knowledge to the drug-policy making process. Using a case study of the Belgian drug-policy debates between 1996 and 2003, we conducted a discourse analysis of specially selected 1067 newspaper articles and 164 policy documents. Our analysis focused on: textual elements that feature intra-discourse differences, how players and scientific knowledge are represented in the text, the arguments used and claims made, and the various types of research utilisation. Media discourse strongly influenced the public's and policy makers' understanding as well as the content of the Belgian drug policy debate between 1996 and 2003. As a major source of scientific knowledge, media coverage supported the 'enlightenment' role of scientific knowledge in the policy-making process by broadening and even determining frames of reference. However, as the presentation of scientific knowledge in the media was often inaccurate or distorted due to the lack of contextual information or statistical misinformation, the media may also support the selective utilisation of scientific knowledge. Many challenges as well as opportunities lie ahead for researchers who want to influence the policy-making process since most research fails to go beyond academic publications. Although media is a valuable linking mechanism between science and policy, by no means does it provide scientists with a guarantee of a more 'evidence-based' drug policy. Copyright © 2013 Elsevier B.V. All rights reserved.
Potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement process of orphan drugs.

PubMed

Kolasa, Katarzyna; Zwolinski, Krzysztof M; Kalo, Zoltan; Hermanowski, Tomasz

2016-03-10

The objective of this study was to assess the potential impact of the implementation of multiple-criteria decision analysis (MCDA) on the Polish pricing and reimbursement (P&R) process with regard to orphan drugs. A four step approach was designed. Firstly, a systematic literature review was conducted to select the MCDA criteria. Secondly, a database of orphan drugs was established. Thirdly, health technology appraisals (HTA recommendations) were categorized and an MCDA appraisal was conducted. Finally, a comparison of HTA and MCDA outcomes was carried out. An MCDA outcome was considered positive if more than 50% of the maximum number of points was reached (base case). In the sensitivity analysis, 25% and 75% thresholds were tested as well. Out of 2242 publications, 23 full-text articles were included. The final MCDA tool consisted of ten criteria. In total, 27 distinctive drug-indication pairs regarding 21 drugs were used for the study. Six negative and 21 positive HTA recommendations were issued. In the base case, there were 19 positive MCDA outcomes. Of the 27 cases, there were 12 disagreements between the HTA and MCDA outcomes, the majority of which related to positive HTA guidance for negative MCDA outcomes. All drug-indication pairs with negative HTA recommendations were appraised positively in the MCDA framework. Economic details were available for 12 cases, of which there were 9 positive MCDA outcomes. Amongst the 12 drug-indication pairs, two were negatively appraised in the HTA process, with positive MCDA guidance, and two were appraised in the opposite direction. An MCDA approach may lead to different P&R outcomes compared to a standard HTA process. On the one hand, enrichment of the list of decision making criteria means further scrutiny of a given health technology and as such increases the odds of a negative P&R outcome. On the other hand, it may uncover additional values and as such increase the odds of positive P&R outcomes.
Exploring the relationship between online buyers and sellers of image and performance enhancing drugs (IPEDs): Quality issues, trust and self-regulation.

PubMed

van de Ven, Katinka; Koenraadt, Rosa

2017-12-01

Online drug markets are expanding the boundaries of drug supply including the sale and purchase of image and performance enhancing drugs (IPEDs). However, the role of the internet in IPED markets, and in particular the ways in which these substances are supplied via the surface web, has rarely been considered. This article examines the online IPED market in order to inform drug policy and to provide a nuanced understanding of retailers involved, particularly exploring the relationship between buyers and sellers. This paper is based on two extensive research projects conducted in the Netherlands and Belgium. The first project focuses on muscle drugs and is based on 64 IPED dealing cases, semi-structured interviews with authorities (N=32), and dealers (N=15), along with an analysis of 10 steroid-selling websites. The second research project primarily focuses on weight loss drugs and sexual enhancers in the Netherlands, and relies on interviews with authorities (N=38), suppliers (N=30), and consumers (N=10), analysis of 69 criminal case files, and an online analysis. In the literature, the illicit online sale of IPEDs is generally associated with illegal online pharmacies that try to mislead buyers. While confirmed in our research, we also illustrate that there are online suppliers who invest in customer relationships and services, and that users are aware of the illegal nature of their business. These e-vendors incorporate a 'social supply business model' by providing the best possible service to their customers and attempting to minimise risks in order to attract, satisfy and maintain customers. As it is likely that users will continue to make use of the internet to order IPEDs, regardless of closing down selling websites, it is first of all important to counteract these online sources by educating all types of consumers and providing harm reduction services. Copyright © 2017 Elsevier B.V. All rights reserved.
Engagement of the private pharmaceutical sector for TB control: rhetoric or reality?

PubMed

Konduri, Niranjan; Delmotte, Emily; Rutta, Edmund

2017-01-01

Private-sector retail drug outlets are often the first point of contact for common health ailments, including tuberculosis (TB). Systematic reviews on public-private mix (PPM) interventions for TB did not perform in-depth reviews specifically on engaging retail drug outlets and related stakeholders in the pharmaceutical sector. Our objective was to better understand the extent to which the World Health Organization's (WHO) recommendation on engaging retail drug outlets has been translated into programmatic policy, strategy, and intervention in low- and middle-income countries. The study included a content analysis of global-level documents from WHO and the Stop TB Partnership in five phases. A country-level content analysis from four data sources was performed. Global-level findings were tabulated based on key messages related to engaging retail drug outlets. Country-level findings were analyzed based on four factors and tabulated. National strategic plans for TB control from 14 countries with varying TB burdens and a strong private sector were reviewed. 33 global-level documents and 77 full-text articles and Union World Lung Health conference abstracts were included for review. Based on experience of engaging retail drug outlets that has emerged since the mid-2000s, in 2011 WHO and the International Pharmaceutical Federation released a joint statement on promoting the engagement of national pharmacy associations in partnership with national TB programs. Only two of 14 countries' national strategic plans had explicit statements on the need to engage their national pharmacy professional association. The success rate of referrals from retail drug outlets who visited an approved health facility for TB screening ranged from 48% in Vietnam to 86% in Myanmar. Coverage of retail drug outlets ranged from less than 5 to 9% of the universe of retail drug outlets. For WHO's End TB Strategy to be successful, scaling up retail drug outlets to increase national coverage, at least in countries with a thriving private sector, will be instrumental in accelerating the early detection and referral of the 3 million missing TB cases. The proposed PPM pharmacy model is applicable not only for TB control but also to tackle the antimicrobial resistance crisis in these countries.
Food and Drug Administration criteria for the diagnosis of drug-induced valvular heart disease in patients previously exposed to benfluorex: a prospective multicentre study.

PubMed

Maréchaux, Sylvestre; Rusinaru, Dan; Jobic, Yannick; Ederhy, Stéphane; Donal, Erwan; Réant, Patricia; Arnalsteen, Elise; Boulanger, Jacques; Garban, Thierry; Ennezat, Pierre-Vladimir; Jeu, Antoine; Szymanski, Catherine; Tribouilloy, Christophe

2015-02-01

The Food and Drug Administration (FDA) criteria for diagnosis of drug-induced valvular heart disease (DIVHD) are only based on the observation of aortic regurgitation ≥ mild and/or mitral regurgitation ≥ moderate. We sought to evaluate the diagnostic value of FDA criteria in a cohort of control patients and in a cohort of patients exposed to a drug (benfluorex) known to induce VHD. This prospective, multicentre study included 376 diabetic control patients not exposed to valvulopathic drugs and 1000 subjects previously exposed to benfluorex. Diagnosis of mitral or aortic DIVHD was based on a combined functional and morphological echocardiographic analysis of cardiac valves. Patients were classified according to the FDA criteria [mitral or aortic-FDA(+) and mitral or aortic-FDA(-)]. Among the 376 control patients, 2 were wrongly classified as mitral-FDA(+) and 17 as aortic-FDA(+) (0.53 and 4.5% of false positives, respectively). Of those exposed to benfluorex, 48 of 58 with a diagnosis of mitral DIVHD (83%) were classified as mitral-FDA(-), and 901 of the 910 patients (99%) without a diagnosis of the mitral DIVHD group were classified as mitral-FDA(-). All 40 patients with a diagnosis of aortic DIVHD were classified as aortic-FDA(+), and 105 of the 910 patients without a diagnosis of aortic DIVHD (12%) were classified aortic-FDA(+). Older age and lower BMI were independent predictors of disagreement between FDA criteria and the diagnosis of DIVHD in patients exposed to benfluorex (both P ≤ 0.001). FDA criteria solely based on the Doppler detection of cardiac valve regurgitation underestimate for the mitral valve and overestimate for the aortic valve the frequency of DIVHD. Therefore, the diagnosis of DIVHD must be based on a combined echocardiographic and Doppler morphological and functional analysis of cardiac valves. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.
Glutathione S-transferase P1 (GSTP1) directly influences platinum drug chemosensitivity in ovarian tumour cell lines

PubMed Central

Sawers, L; Ferguson, M J; Ihrig, B R; Young, H C; Chakravarty, P; Wolf, C R; Smith, G

2014-01-01

Background: Chemotherapy response in ovarian cancer patients is frequently compromised by drug resistance, possibly due to altered drug metabolism. Platinum drugs are metabolised by glutathione S-transferase P1 (GSTP1), which is abundantly, but variably expressed in ovarian tumours. We have created novel ovarian tumour cell line models to investigate the extent to which differential GSTP1 expression influences chemosensitivity. Methods: Glutathione S-transferase P1 was stably deleted in A2780 and expression significantly reduced in cisplatin-resistant A2780DPP cells using Mission shRNA constructs, and MTT assays used to compare chemosensitivity to chemotherapy drugs used to treat ovarian cancer. Differentially expressed genes in GSTP1 knockdown cells were identified by Illumina HT-12 expression arrays and qRT–PCR analysis, and altered pathways predicted by MetaCore (GeneGo) analysis. Cell cycle changes were assessed by FACS analysis of PI-labelled cells and invasion and migration compared in quantitative Boyden chamber-based assays. Results: Glutathione S-transferase P1 knockdown selectively influenced cisplatin and carboplatin chemosensitivity (2.3- and 4.83-fold change in IC50, respectively). Cell cycle progression was unaffected, but cell invasion and migration was significantly reduced. We identified several novel GSTP1 target genes and candidate platinum chemotherapy response biomarkers. Conclusions: Glutathione S-transferase P1 has an important role in cisplatin and carboplatin metabolism in ovarian cancer cells. Inter-tumour differences in GSTP1 expression may therefore influence response to platinum-based chemotherapy in ovarian cancer patients. PMID:25010864
Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis.

PubMed

Ding, Kuan-Fu; Petricoin, Emanuel F; Finlay, Darren; Yin, Hongwei; Hendricks, William P D; Sereduk, Chris; Kiefer, Jeffrey; Sekulic, Aleksandar; LoRusso, Patricia M; Vuori, Kristiina; Trent, Jeffrey M; Schork, Nicholas J

2018-01-12

Cancer cell lines are often used in high throughput drug screens (HTS) to explore the relationship between cell line characteristics and responsiveness to different therapies. Many current analysis methods infer relationships by focusing on one aspect of cell line drug-specific dose-response curves (DRCs), the concentration causing 50% inhibition of a phenotypic endpoint (IC 50 ). Such methods may overlook DRC features and do not simultaneously leverage information about drug response patterns across cell lines, potentially increasing false positive and negative rates in drug response associations. We consider the application of two methods, each rooted in nonlinear mixed effects (NLME) models, that test the relationship relationships between estimated cell line DRCs and factors that might mitigate response. Both methods leverage estimation and testing techniques that consider the simultaneous analysis of different cell lines to draw inferences about any one cell line. One of the methods is designed to provide an omnibus test of the differences between cell line DRCs that is not focused on any one aspect of the DRC (such as the IC 50 value). We simulated different settings and compared the different methods on the simulated data. We also compared the proposed methods against traditional IC 50 -based methods using 40 melanoma cell lines whose transcriptomes, proteomes, and, importantly, BRAF and related mutation profiles were available. Ultimately, we find that the NLME-based methods are more robust, powerful and, for the omnibus test, more flexible, than traditional methods. Their application to the melanoma cell lines reveals insights into factors that may be clinically useful.
Experimental design and statistical analysis for three-drug combination studies.

PubMed

Fang, Hong-Bin; Chen, Xuerong; Pei, Xin-Yan; Grant, Steven; Tan, Ming

2017-06-01

Drug combination is a critically important therapeutic approach for complex diseases such as cancer and HIV due to its potential for efficacy at lower, less toxic doses and the need to move new therapies rapidly into clinical trials. One of the key issues is to identify which combinations are additive, synergistic, or antagonistic. While the value of multidrug combinations has been well recognized in the cancer research community, to our best knowledge, all existing experimental studies rely on fixing the dose of one drug to reduce the dimensionality, e.g. looking at pairwise two-drug combinations, a suboptimal design. Hence, there is an urgent need to develop experimental design and analysis methods for studying multidrug combinations directly. Because the complexity of the problem increases exponentially with the number of constituent drugs, there has been little progress in the development of methods for the design and analysis of high-dimensional drug combinations. In fact, contrary to common mathematical reasoning, the case of three-drug combinations is fundamentally more difficult than two-drug combinations. Apparently, finding doses of the combination, number of combinations, and replicates needed to detect departures from additivity depends on dose-response shapes of individual constituent drugs. Thus, different classes of drugs of different dose-response shapes need to be treated as a separate case. Our application and case studies develop dose finding and sample size method for detecting departures from additivity with several common (linear and log-linear) classes of single dose-response curves. Furthermore, utilizing the geometric features of the interaction index, we propose a nonparametric model to estimate the interaction index surface by B-spine approximation and derive its asymptotic properties. Utilizing the method, we designed and analyzed a combination study of three anticancer drugs, PD184, HA14-1, and CEP3891 inhibiting myeloma H929 cell line. To our best knowledge, this is the first ever three drug combinations study performed based on the original 4D dose-response surface formed by dose ranges of three drugs.

Drugs As Instruments: Describing and Testing a Behavioral Approach to the Study of Neuroenhancement

PubMed Central

Brand, Ralf; Wolff, Wanja; Ziegler, Matthias

2016-01-01

Neuroenhancement (NE) is the non-medical use of psychoactive substances to produce a subjective enhancement in psychological functioning and experience. So far empirical investigations of individuals' motivation for NE however have been hampered by the lack of theoretical foundation. This study aimed to apply drug instrumentalization theory to user motivation for NE. We argue that NE should be defined and analyzed from a behavioral perspective rather than in terms of the characteristics of substances used for NE. In the empirical study we explored user behavior by analyzing relationships between drug options (use over-the-counter products, prescription drugs, illicit drugs) and postulated drug instrumentalization goals (e.g., improved cognitive performance, counteracting fatigue, improved social interaction). Questionnaire data from 1438 university students were subjected to exploratory and confirmatory factor analysis to address the question of whether analysis of drug instrumentalization should be based on the assumption that users are aiming to achieve a certain goal and choose their drug accordingly or whether NE behavior is more strongly rooted in a decision to try or use a certain drug option. We used factor mixture modeling to explore whether users could be separated into qualitatively different groups defined by a shared “goal × drug option” configuration. Our results indicate, first, that individuals' decisions about NE are eventually based on personal attitude to drug options (e.g., willingness to use an over-the-counter product but not to abuse prescription drugs) rather than motivated by desire to achieve a specific goal (e.g., fighting tiredness) for which different drug options might be tried. Second, data analyses suggested two qualitatively different classes of users. Both predominantly used over-the-counter products, but “neuroenhancers” might be characterized by a higher propensity to instrumentalize over-the-counter products for virtually all investigated goals whereas “fatigue-fighters” might be inclined to use over-the-counter products exclusively to fight fatigue. We believe that psychological investigations like these are essential, especially for designing programs to prevent risky behavior. PMID:27582720
RADIOISOTOPES USED IN PHARMACY. 5. IONIZING RADIATION IN PHARMACEUTICAL ANALYSIS (in Danish)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kristensen, K.

1962-09-01

The use of radioisotope methods for analyzing drugs is reviewed. It is pointed out that heretofore most methods have been based on isotope dilution principles whereas in the future radioactivation analysis, especially with neutron sources, offers great possibilities. (BBB)
Time-Gated Raman Spectroscopy for Quantitative Determination of Solid-State Forms of Fluorescent Pharmaceuticals.

PubMed

Lipiäinen, Tiina; Pessi, Jenni; Movahedi, Parisa; Koivistoinen, Juha; Kurki, Lauri; Tenhunen, Mari; Yliruusi, Jouko; Juppo, Anne M; Heikkonen, Jukka; Pahikkala, Tapio; Strachan, Clare J

2018-04-03

Raman spectroscopy is widely used for quantitative pharmaceutical analysis, but a common obstacle to its use is sample fluorescence masking the Raman signal. Time-gating provides an instrument-based method for rejecting fluorescence through temporal resolution of the spectral signal and allows Raman spectra of fluorescent materials to be obtained. An additional practical advantage is that analysis is possible in ambient lighting. This study assesses the efficacy of time-gated Raman spectroscopy for the quantitative measurement of fluorescent pharmaceuticals. Time-gated Raman spectroscopy with a 128 × (2) × 4 CMOS SPAD detector was applied for quantitative analysis of ternary mixtures of solid-state forms of the model drug, piroxicam (PRX). Partial least-squares (PLS) regression allowed quantification, with Raman-active time domain selection (based on visual inspection) improving performance. Model performance was further improved by using kernel-based regularized least-squares (RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized. Overall, time-gated Raman spectroscopy, especially with optimized data analysis in both the spectral and time dimensions, shows potential for sensitive and relatively routine quantitative analysis of photoluminescent pharmaceuticals during drug development and manufacturing.
[Predictive factors of clinically significant drug-drug interactions among regimens based on protease inhibitors, non-nucleoside reverse transcriptase inhibitors and raltegravir].

PubMed

Cervero, Miguel; Torres, Rafael; Jusdado, Juan José; Pastor, Susana; Agud, Jose Luis

2016-04-15

To determine the prevalence and types of clinically significant drug-drug interactions (CSDI) in the drug regimens of HIV-infected patients receiving antiretroviral treatment. retrospective review of database. Centre: Hospital Universitario Severo Ochoa, Infectious Unit. one hundred and forty-two participants followed by one of the authors were selected from January 1985 to December 2014. from their outpatient medical records we reviewed information from the last available visit of the participants, in relation to HIV infection, comorbidities, demographics and the drugs that they were receiving; both antiretroviral drugs and drugs not related to HIV infection. We defined CSDI from the information sheet and/or database on antiretroviral drug interactions of the University of Liverpool (http://www.hiv-druginteractions.org) and we developed a diagnostic tool to predict the possibility of CSDI. By multivariate logistic regression analysis and by estimating the diagnostic performance curve obtained, we identified a quick tool to predict the existence of drug interactions. Of 142 patients, 39 (29.11%) had some type of CSDI and in 11.2% 2 or more interactions were detected. In only one patient the combination of drugs was contraindicated (this patient was receiving darunavir/r and quetiapine). In multivariate analyses, predictors of CSDI were regimen type (PI or NNRTI) and the use of 3 or more non-antiretroviral drugs (AUC 0.886, 95% CI 0.828 to 0.944; P=.0001). The risk was 18.55 times in those receiving NNRTI and 27,95 times in those receiving IP compared to those taking raltegravir. Drug interactions, including those defined as clinically significant, are common in HIV-infected patients treated with antiretroviral drugs, and the risk is greater in IP-based regimens. Raltegravir-based prescribing, especially in patients who receive at least 3 non-HIV drugs could avoid interactions. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.
Individual and contextual determinants of regional variation in prescription drug use: an analysis of administrative data from British Columbia.

PubMed

Morgan, Steven G; Cunningham, Colleen M; Hanley, Gillian E

2010-12-29

Increasing attention is being paid to variations in the use of prescription drugs because their role in health care has grown to the point where their use can be considered a proxy for health system performance. Studies have shown that prescription drug use varies across regions in the US, UK, and Canada by more than would be predicted based on age and health status alone. In this paper, we explore the determinants of variations in the use of prescription drugs, drawing on health services theories of access to care. We conducted a cross-sectional analysis using population-based administrative health care data for British Columbia (BC), Canada. We used logistic and hierarchical regressions to analyze the effects of individual- and area-level determinants of use of prescriptions overall and rates of purchase of prescriptions from five therapeutic categories representing a range of indications: antihypertensives, statins, acid reducing drugs, opioid drugs, and antidepressants. To indicate the relative scale of regional variations and the importance of individual- and area-level variables in explaining them, we computed standardized rates of utilization for 49 local health areas in BC. We found that characteristics of individuals and the areas in which they live affect likelihood of prescription drug purchase. Individual-level factors influenced prescription drug purchases in ways generally consistent with behavioral models of health services use. Contextual variables exerted influences that differed by type of drug studied. Population health, education levels, and ethnic composition of local areas were associated with significant differences in the likelihood of purchasing medications. Relatively modest regional variations remained after both individual-level and area-level determinants were taken into account. The results of this study suggest that individual- and area-level factors should be considered when studying variations in the use of prescription drugs. Some sources of such variations, including individual- and area-level socioeconomic status, warrant further investigation and possible intervention to address inequities.
Individual and Contextual Determinants of Regional Variation in Prescription Drug Use: An Analysis of Administrative Data from British Columbia

PubMed Central

Morgan, Steven G.; Cunningham, Colleen M.; Hanley, Gillian E.

2010-01-01

Background Increasing attention is being paid to variations in the use of prescription drugs because their role in health care has grown to the point where their use can be considered a proxy for health system performance. Studies have shown that prescription drug use varies across regions in the US, UK, and Canada by more than would be predicted based on age and health status alone. In this paper, we explore the determinants of variations in the use of prescription drugs, drawing on health services theories of access to care. Methods We conducted a cross-sectional analysis using population-based administrative health care data for British Columbia (BC), Canada. We used logistic and hierarchical regressions to analyze the effects of individual- and area-level determinants of use of prescriptions overall and rates of purchase of prescriptions from five therapeutic categories representing a range of indications: antihypertensives, statins, acid reducing drugs, opioid drugs, and antidepressants. To indicate the relative scale of regional variations and the importance of individual- and area-level variables in explaining them, we computed standardized rates of utilization for 49 local health areas in BC. Results We found that characteristics of individuals and the areas in which they live affect likelihood of prescription drug purchase. Individual-level factors influenced prescription drug purchases in ways generally consistent with behavioral models of health services use. Contextual variables exerted influences that differed by type of drug studied. Population health, education levels, and ethnic composition of local areas were associated with significant differences in the likelihood of purchasing medications. Relatively modest regional variations remained after both individual-level and area-level determinants were taken into account. Conclusions The results of this study suggest that individual- and area-level factors should be considered when studying variations in the use of prescription drugs. Some sources of such variations, including individual- and area-level socioeconomic status, warrant further investigation and possible intervention to address inequities. PMID:21209960
Hair-based rapid analyses for multiple drugs in forensics and doping: application of dynamic multiple reaction monitoring with LC-MS/MS.

PubMed

Shah, Iltaf; Petroczi, Andrea; Uvacsek, Martina; Ránky, Márta; Naughton, Declan P

2014-01-01

Considerable efforts are being extended to develop more effective methods to detect drugs in forensic science for applications such as preventing doping in sport. The aim of this study was to develop a sensitive and accurate method for analytes of forensic and toxicological nature in human hair at sub-pg levels. The hair test covers a range of different classes of drugs and metabolites of forensic and toxicological nature including selected anabolic steroids, cocaine, amphetamines, cannabinoids, opiates, bronchodilators, phencyclidine and ketamine. For extraction purposes, the hair samples were decontaminated using dichloromethane, ground and treated with 1 M sodium hydroxide and neutralised with hydrochloric acid and phosphate buffer and the homogenate was later extracted with hexane using liquid-liquid extraction (LLE). Following extraction from hair samples, drug-screening employed liquid chromatography coupled to tandem mass spectrometric (LC-MS/MS) analysis using dynamic multiple reaction monitoring (DYN-MRM) method using proprietary software. The screening method (for > 200 drugs/metabolites) was calibrated with a tailored drug mixture and was validated for 20 selected drugs for this study. Using standard additions to hair sample extracts, validation was in line with FDA guidance. A Zorbax Eclipse plus C18 (2.1 mm internal diameter × 100 mm length × 1.8 μm particle size) column was used for analysis. Total instrument run time was 8 minutes with no noted matrix interferences. The LOD of compounds ranged between 0.05-0.5 pg/mg of hair. 233 human hair samples were screened using this new method and samples were confirmed positive for 20 different drugs, mainly steroids and drugs of abuse. This is the first report of the application of this proprietary system to investigate the presence of drugs in human hair samples. The method is selective, sensitive and robust for the screening and confirmation of multiple drugs in a single analysis and has potential as a very useful tool for the analysis of large array of controlled substances and drugs of abuse.
An experimental investigation of masking in the US FDA adverse event reporting system database.

PubMed

Wang, Hsin-wei; Hochberg, Alan M; Pearson, Ronald K; Hauben, Manfred

2010-12-01

A phenomenon of 'masking' or 'cloaking' in pharmacovigilance data mining has been described, which can potentially cause signals of disproportionate reporting (SDRs) to be missed, particularly in pharmaceutical company databases. Masking has been predicted theoretically, observed anecdotally or studied to a limited extent in both pharmaceutical company and health authority databases, but no previous publication systematically assesses its occurrence in a large health authority database. To explore the nature, extent and possible consequences of masking in the US FDA Adverse Event Reporting System (AERS) database by applying various experimental unmasking protocols to a set of drugs and events representing realistic pharmacovigilance analysis conditions. This study employed AERS data from 2001 through 2005. For a set of 63 Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms (PTs), disproportionality analysis was carried out with respect to all drugs included in the AERS database, using a previously described urn-model-based algorithm. We specifically sought masking in which drug removal induced an increase in the statistical representation of a drug-event combination (DEC) that resulted in the emergence of a new SDR. We performed a series of unmasking experiments selecting drugs for removal using rational statistical decision rules based on the requirement of a reporting ratio (RR) >1, top-ranked statistical unexpectedness (SU) and relatedness as reflected in the WHO Anatomical Therapeutic Chemical level 4 (ATC4) grouping. In order to assess the possible extent of residual masking we performed two supplemental purely empirical analyses on a limited subset of data. This entailed testing every drug and drug group to determine which was most influential in uncovering masked SDRs. We assessed the strength of external evidence for a causal association for a small number of masked SDRs involving a subset of 29 drugs for which level of evidence adjudication was available from a previous study. The original disproportionality analysis identified 8719 SDRs for the 63 PTs. The SU-based unmasking protocols generated variable numbers of masked SDRs ranging from 38 to 156, representing a 0.43-1.8% increase over the number of baseline SDRs. A significant number of baseline SDRs were also lost in the course of our experiments. The trend in the number of gained SDRs per report removed was inversely related to the number of lost SDRs per protocol. Both the number and nature of the reports removed influenced the number of gained SDRs observed. The purely empirical protocols unmasked up to ten times as many SDRs. None of the masked SDRs had strong external evidence supporting a causal association. Most involved associations for which there was no external supporting evidence or were in the original product label. For two masked SDRs, there was external evidence of a possible causal association. We documented masking in the FDA AERS database. Attempts at unmasking SDRs using practically implementable protocols produced only small changes in the output of SDRs in our analysis. This is undoubtedly related to the large size and diversity of the database, but the complex interdependencies between drugs and events in authentic spontaneous reporting system (SRS) databases, and the impact of measures of statistical variability that are typically used in real-world disproportionality analysis, may be additional factors that constrain the discovery of masked SDRs and which may also operate in pharmaceutical company databases. Empirical determination of the most influential drugs may uncover significantly more SDRs than protocols based on predetermined statistical selection rules but are impractical except possibly for evaluating specific events. Routine global exercises to elicit masking, especially in large health authority databases are not justified based on results available to date. Exercises to elicit unmasking should be driven by prior knowledge or obvious data imbalances.
Effectiveness of Gross Model-Based Emotion Regulation Strategies Training on Anger Reduction in Drug-Dependent Individuals and its Sustainability in Follow-up

PubMed Central

Massah, Omid; Sohrabi, Faramarz; A’azami, Yousef; Doostian, Younes; Farhoudian, Ali; Daneshmand, Reza

2016-01-01

Background Emotion plays an important role in adapting to life changes and stressful events. Difficulty regulating emotions is one of the problems drug abusers often face, and teaching these individuals to express and manage their emotions can be effective on improving their difficult circumstances. Objectives The present study aimed to determine the effectiveness of the Gross model-based emotion regulation strategies training on anger reduction in drug-dependent individuals. Patients and Methods The present study had a quasi-experimental design wherein pretest-posttest evaluations were applied using a control group. The population under study included addicts attending Marivan’s methadone maintenance therapy centers in 2012 - 2013. Convenience sampling was used to select 30 substance-dependent individuals undergoing maintenance treatment who were then randomly assigned to the experiment and control groups. The experiment group received its training in eight two-hour sessions. Data were analyzed using analysis of co-variance and paired t-test. Results There was significant reduction in anger symptoms of drug-dependent individuals after gross model based emotion regulation training (ERT) (P < 0.001). Moreover, the effectiveness of the training on anger was persistent in the follow-up period. Conclusions Symptoms of anger in drug-dependent individuals of this study were reduced by gross model-based emotion regulation strategies training. Based on the results of this study, we may conclude that the gross model based emotion regulation strategies training can be applied alongside other therapies to treat drug abusers undergoing rehabilitation. PMID:27162759
Can and should value-based pricing be applied to molecular diagnostics?

PubMed

Garau, Martina; Towse, Adrian; Garrison, Louis; Housman, Laura; Ossa, Diego

2013-01-01

Current pricing and reimbursement systems for diagnostics are not efficient. Prices for diagnostics are often driven by administrative practices and expected production cost. The purpose of the paper is to discuss how a value-based pricing framework being used to ensure efficient use and price of medicines could also be applied to diagnostics. Diagnostics not only facilitates health gain and cost savings, but also information to guide patients' decisions on interventions and their future 'behaviors'. For value assessment processes we recommend a two-part approach. Companion diagnostics introduced at the launch of the drug should be assessed through new drug assessment processes considering a broad range of value elements and a balanced analysis of diagnostic impacts. A separate diagnostic-dedicated committee using value-based pricing principles should review other diagnostics lying outside the companion diagnostics-and-drug 'at-launch' situation.
A Population-Based Assessment of the Drug Interaction Between Levothyroxine and Warfarin

PubMed Central

Pincus, D; Gomes, T; Hellings, C; Zheng, H; Paterson, JM; Mamdani, MM; Juurlink, DN

2013-01-01

Most drug interaction resources suggest that levothyroxine can dramatically potentiate the effect of warfarin. However, the mechanistic basis of the interaction is speculative, and little evidence supports a meaningful drug interaction. We conducted a population-based nested case–control study to examine the risk of hospitalization for hemorrhage following the initiation of levothyroxine in a cohort of 260,076 older patients receiving warfarin. In this group, we identified 10,532 case subjects hospitalized for hemorrhage and 40,595 controls. In the primary analysis, we found no association between hospitalization for hemorrhage during warfarin therapy and initiation of levothyroxine in the preceding 30 days (adjusted odds ratio 1.11, 95% confidence interval 0.67–1.86). Secondary analyses using more remote initiation of levothyroxine also found no association. These findings suggest that concerns about a clinically meaningful levothyroxine–warfarin drug interaction are not justified. Drug interaction resources that presently characterize this interaction as important should reevaluate this classification. PMID:23093318
A Conceptual Framework for Pharmacodynamic Genome-wide Association Studies in Pharmacogenomics

PubMed Central

Wu, Rongling; Tong, Chunfa; Wang, Zhong; Mauger, David; Tantisira, Kelan; Szefler, Stanley J.; Chinchilli, Vernon M.; Israel, Elliot

2013-01-01

Summary Genome-wide association studies (GWAS) have emerged as a powerful tool to identify loci that affect drug response or susceptibility to adverse drug reactions. However, current GWAS based on a simple analysis of associations between genotype and phenotype ignores the biochemical reactions of drug response, thus limiting the scope of inference about its genetic architecture. To facilitate the inference of GWAS in pharmacogenomics, we sought to undertake the mathematical integration of the pharmacodynamic process of drug reactions through computational models. By estimating and testing the genetic control of pharmacodynamic and pharmacokinetic parameters, this mechanistic approach does not only enhance the biological and clinical relevance of significant genetic associations, but also improve the statistical power and robustness of gene detection. This report discusses the general principle and development of pharmacodynamics-based GWAS, highlights the practical use of this approach in addressing various pharmacogenomic problems, and suggests that this approach will be an important method to study the genetic architecture of drug responses or reactions. PMID:21920452
Network-Based Approaches in Drug Discovery and Early Development

PubMed Central

Harrold, JM; Ramanathan, M; Mager, DE

2015-01-01

Identification of novel targets is a critical first step in the drug discovery and development process. Most diseases such as cancer, metabolic disorders, and neurological disorders are complex, and their pathogenesis involves multiple genetic and environmental factors. Finding a viable drug target–drug combination with high potential for yielding clinical success within the efficacy–toxicity spectrum is extremely challenging. Many examples are now available in which network-based approaches show potential for the identification of novel targets and for the repositioning of established targets. The objective of this article is to highlight network approaches for identifying novel targets with greater chances of gaining approved drugs with maximal efficacy and minimal side effects. Further enhancement of these approaches may emerge from effectively integrating computational systems biology with pharmacodynamic systems analysis. Coupling genomics, proteomics, and metabolomics databases with systems pharmacology modeling may aid in the development of disease-specific networks that can be further used to build confidence in target identification. PMID:24025802
Budget impact analysis of darbepoetin alfa every 3 weeks versus epoetin alfa every week for the treatment of chemotherapy-induced anaemia from a US payer's perspective.

PubMed

Rubin, Robert J; Glaspy, John A; Adams, John L; Mafilios, Michael S; Wang, Sharon M; Viswanathan, Hema N; Kallich, Joel D

2008-01-01

This analysis was conducted to compare the direct medical costs of treatment with darbepoetin alfa every 3 weeks (Q3W) and epoetin alfa every week (QW) in patients with chemotherapy-induced anaemia (CIA) from the payer's perspective. An analysis was conducted from a US health plan perspective to compare the annual budget impact for CIA with darbepoetin alfa Q3W and epoetin alfa QW over a 16-week treatment period. Dosing regimens were obtained from registration clinical trials. Mean doses, including dose adjustments, were 375.6 microg Q3W for darbepoetin alfa and 43,187 U QW for epoetin alfa. Costs of medical resources included drug acquisition and administration costs. The base case analysis resulted in a per-patient budget impact of $8,544 and $8,667 for darbepoetin alfa and epoetin alfa, respectively. Per member per month cost was $0.90 for darbepoetin alfa and $0.91 for epoetin alfa, based on an estimate of 2,735 CIA patients in a health plan population of 2.17 million. The analysis was most sensitive to drug dose, treatment period and drug price. Results suggest that per-patient direct medical costs of CIA treatment, when initiated at labelled starting doses, are comparable for darbepoetin alfa Q3W and epoetin alfa QW.
A comparison of generic drug prices in seven European countries: a methodological analysis.

PubMed

Wouters, Olivier J; Kanavos, Panos G

2017-03-31

Policymakers and researchers frequently compare the prices of medicines between countries. Such comparisons often serve as barometers of how pricing and reimbursement policies are performing. The aim of this study was to examine methodological challenges to comparing generic drug prices. We calculated all commonly used price indices based on 2013 IMS Health data on sales of 3156 generic drugs in seven European countries. There were large differences in generic drug prices between countries. However, the results varied depending on the choice of index, base country, unit of volume, method of currency conversion, and therapeutic category. The results also differed depending on whether one looked at the prices charged by manufacturers or those charged by pharmacists. Price indices are a useful statistical approach for comparing drug prices across countries, but researchers and policymakers should interpret price indices with caution given their limitations. Price-index results are highly sensitive to the choice of method and sample. More research is needed to determine the drivers of price differences between countries. The data suggest that some governments should aim to reduce distribution costs for generic drugs.
The Drug Discovery and Development Industry in India—Two Decades of Proprietary Small‐Molecule R&D

PubMed Central

2017-01-01

Abstract This review provides a comprehensive survey of proprietary drug discovery and development efforts performed by Indian companies between 1994 and mid‐2016. It is based on the identification and detailed analysis of pharmaceutical, biotechnology, and contract research companies active in proprietary new chemical entity (NCE) research and development (R&D) in India. Information on preclinical and clinical development compounds was collected by company, therapeutic indication, mode of action, target class, and development status. The analysis focuses on the overall pipeline and its evolution over two decades, contributions by type of company, therapeutic focus, attrition rates, and contribution to Western pharmaceutical pipelines through licensing agreements. This comprehensive analysis is the first of its kind, and, in our view, represents a significant contribution to the understanding of the current state of the drug discovery and development industry in India. PMID:28464443
[The temporal dimension of drugs: a sociological analysis based on a category key to the study of health-disease-care processes].

PubMed

Sánchez Antelo, Victoria

2016-03-01

The temporal dimensions that shape the senses and practices of men and women who are poly-consumers of psychoactive substances, 18-35 years of age, and living in the metropolitan area of Buenos Aires were analyzed. Using a qualitative approach, 29 individual in-depth interviews were carried out and then analyzed through a constant comparative analysis process between the categories generated from the data obtained and the theoretical concepts. From the analysis, practices and meanings emerge that regulate the diverse temporalities that underlie drug consumption: feelings related to body rhythms, periods between consumptions, the timing of phases of the life cycle, or unspecific temporalities that become an adequate "moment" for consumption. These practices require that particular attention be paid to time, as this enables the flexibility to consume without being a consumer, to use drugs without being addicted to them.
The Drug Discovery and Development Industry in India-Two Decades of Proprietary Small-Molecule R&D.

PubMed

Differding, Edmond

2017-06-07

This review provides a comprehensive survey of proprietary drug discovery and development efforts performed by Indian companies between 1994 and mid-2016. It is based on the identification and detailed analysis of pharmaceutical, biotechnology, and contract research companies active in proprietary new chemical entity (NCE) research and development (R&D) in India. Information on preclinical and clinical development compounds was collected by company, therapeutic indication, mode of action, target class, and development status. The analysis focuses on the overall pipeline and its evolution over two decades, contributions by type of company, therapeutic focus, attrition rates, and contribution to Western pharmaceutical pipelines through licensing agreements. This comprehensive analysis is the first of its kind, and, in our view, represents a significant contribution to the understanding of the current state of the drug discovery and development industry in India. © 2017 The Author. Published by Wiley-VCH Verlag GmbH & Co. KGaA.
Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

PubMed

Mor, Marco; Rivara, Silvia; Lodola, Alessio; Lorenzi, Simone; Bordi, Fabrizio; Plazzi, Pier Vincenzo; Spadoni, Gilberto; Bedini, Annalida; Duranti, Andrea; Tontini, Andrea; Tarzia, Giorgio

2005-11-01

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.
Chapter 17: Bioimage Informatics for Systems Pharmacology

PubMed Central

Li, Fuhai; Yin, Zheng; Jin, Guangxu; Zhao, Hong; Wong, Stephen T. C.

2013-01-01

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies. PMID:23633943

Did We Get Our Money’s Worth? Bridging Economic and Behavioral Measures of Program Success in Adolescent Drug Prevention

PubMed Central

Griffith, Kevin N.; Scheier, Lawrence M.

2013-01-01

The recent U.S. Congressional mandate for creating drug-free learning environments in elementary and secondary schools stipulates that education reform rely on accountability, parental and community involvement, local decision making, and use of evidence-based drug prevention programs. By necessity, this charge has been paralleled by increased interest in demonstrating that drug prevention programs net tangible benefits to society. One pressing concern is precisely how to integrate traditional scientific methods of program evaluation with economic measures of “cost efficiency”. The languages and methods of each respective discipline don’t necessarily converge on how to establish the true benefits of drug prevention. This article serves as a primer for conducting economic analyses of school-based drug prevention programs. The article provides the reader with a foundation in the relevant principles, methodologies, and benefits related to conducting economic analysis. Discussion revolves around how economists value the potential costs and benefits, both financial and personal, from implementing school-based drug prevention programs targeting youth. Application of heterogeneous costing methods coupled with widely divergent program evaluation findings influences the feasibility of these techniques and may hinder utilization of these practices. Determination of cost-efficiency should undoubtedly become one of several markers of program success and contribute to the ongoing debate over health policy. PMID:24217178
High-Cost Users of Prescription Drugs: A Population-Based Analysis from British Columbia, Canada.

PubMed

Weymann, Deirdre; Smolina, Kate; Gladstone, Emilie J; Morgan, Steven G

2017-04-01

To examine variation in pharmaceutical spending and patient characteristics across prescription drug user groups. British Columbia's population-based linked administrative health and sociodemographic databases (N = 3,460,763). We classified individuals into empirically derived prescription drug user groups based on pharmaceutical spending patterns outside hospitals from 2007 to 2011. We examined variation in patient characteristics, mortality, and health services usage and applied hierarchical clustering to determine patterns of concurrent drug use identifying high-cost patients. Approximately 1 in 20 British Columbians had persistently high prescription costs for 5 consecutive years, accounting for 42 percent of 2011 province-wide pharmaceutical spending. Less than 1 percent of the population experienced discrete episodes of high prescription costs; an additional 2.8 percent transitioned to or from high-cost episodes of unknown duration. Persistent high-cost users were more likely to concurrently use multiple chronic medications; episodic and transitory users spent more on specialized medicines, including outpatient cancer drugs. Cluster analyses revealed heterogeneity in concurrent medicine use within high-cost groups. Whether low, moderate, or high, costs of prescription drugs for most individuals are persistent over time. Policies controlling high-cost use should focus on reducing polypharmacy and encouraging price competition in drug classes used by ordinary and high-cost users alike. © 2016 The Authors. Health Services Research published by Wiley Periodicals, Inc. on behalf of Health Research and Educational Trust.
The application of novel nano-thermal and imaging techniques for monitoring drug microstructure and distribution within PLGA microspheres.

PubMed

Yang, Fan; Chen, De; Guo, Zhe-Fei; Zhang, Yong-Ming; Liu, Yi; Askin, Sean; Craig, Duncan Q M; Zhao, Min

2017-04-30

Poly (d,l-lactic-co-glycolic) acid (PLGA) based microspheres have been extensively used as controlled drug release systems. However, the burst effect has been a persistent issue associated with such systems, especially for those prepared by the double emulsion technique. An effective approach to preventing the burst effect and achieving a more ideal drug release profile is to improve the drug distribution within the polymeric matrix. Therefore, it is of great importance to establish a rapid and robust tool for screening and optimizing the drug distribution during pre-formulation. Transition Temperature Microscopy (TTM), a novel nano-thermal and imaging technique, is an extension of nano-thermal analysis (nano-TA) whereby a transition temperature is detected at a localized region of a sample and then designated a color based on a particular temperature/color palette, finally resulting in a coded map based on transition temperatures detected by carrying out a series of nanoTA measurements across the surface of the sample. In this study, we investigate the feasibility of applying the aforementioned technique combined with other thermal, imaging and structural techniques for monitoring the drug microstructure and spatial distribution within bovine serum albumin (BSA) loaded and nimodipine loaded PLGA microspheres, with a view to better predicting the in vitro drug release performance. Copyright © 2017 Elsevier B.V. All rights reserved.
Production of pure indinavir free base nanoparticles by a supercritical anti-solvent (SAS) method.

PubMed

Imperiale, Julieta C; Bevilacqua, Gabriela; Rosa, Paulo de Tarso Vieira E; Sosnik, Alejandro

2014-12-01

This work investigated the production of pure indinavir free base nanoparticles by a supercritical anti-solvent method to improve the drug dissolution in intestine-like medium. To increase the dissolution of the drug by means of a supercritical fluid processing method. Acetone was used as solvent and supercritical CO2 as antisolvent. Products were characterized by dynamic light scattering (size, size distribution), scanning electron microscopy (morphology), differential scanning calorimetry (thermal behaviour) and X-rays diffraction (crystallinity). Processed indinavir resulted in particles of significantly smaller size than the original drug. Particles showed at least one dimension at the nanometer scale with needle or rod-like morphology. Results of X-rays powder diffraction suggested the formation of a mixture of polymorphs. Differential scanning calorimetry analysis showed a main melting endotherm at 152 °C. Less prominent transitions due to the presence of small amounts of bound water (in the raw drug) or an unstable polymorph (in processed IDV) were also visible. Finally, drug particle size reduction significantly increased the dissolution rate with respect to the raw drug. Conversely, the slight increase of the intrinsic solubility of the nanoparticles was not significant. A supercritical anti-solvent method enabled the nanonization of indinavir free base in one single step with high yield. The processing led to faster dissolution that would improve the oral bioavailability of the drug.
Barriers to community-based drug dependence treatment: implications for police roles, collaborations and performance indicators

PubMed Central

Ma, Yi; Du, Chunhua; Cai, Thomas; Han, Qingfeng; Yuan, Huanhuan; Luo, Tingyan; Ren, Guoliang; Mburu, Gitau; Wang, Bangyuan; Golichenko, Olga; Zhang, Chaoxiong

2016-01-01

Introduction Worldwide, people who use drugs (PWUD) are among the populations at highest risk for HIV infection. In China, PWUD are primarily sentenced to compulsory detainment centres, in which access to healthcare, including HIV treatment and prevention services, is limited or non-existent. In 2008, China's 2008 Anti-Drug Law encouraged the development and use of community-based drug dependence rehabilitation, yet there is limited evidence evaluating the efficacy and challenges of this model in China. In this study, we explore these challenges and describe how cooperation between law enforcement and health departments can meet the needs of PWUD. Methods In 2015, we conducted semi-structured, in-depth interviews with all four staff members and 16 clients of the Ping An Centre No. 1 for community-based drug treatment, three local police officers and three officials from the local Centre for Disease Control. Interviews explored obstacles in implementing community-based drug dependence treatment and efforts to resolve these difficulties. Transcripts were coded and analyzed with qualitative data analysis software (MAXQDA 11). Results We identified three challenges to community-based drug treatment at the Ping An Centre No. 1: (1) suboptimal coordination among parties involved, (2) a divergence in attitudes towards PWUD and harm reduction between law enforcement and health officials and (3) conflicting performance targets for police and health officials that undermine the shared goal of treatment. We also identified the take-home methadone maintenance treatment model at the Ping An Centre No. 1 as an example of an early successful collaboration between the police, the health department and PWUD. Conclusions To overcome barriers to effective community-based drug treatment, we recommend aligning the goals of law enforcement and public health agencies towards health-based performance indicators. Furthermore, tensions between PWUD and police need to be addressed and trust between them fostered, using community-based treatment centres as mediators. The preliminary success of the take-home methadone maintenance treatment pilot can serve as an example of how collaboration with the police and other government agencies can meet the needs of PWUD and contribute to the success of community-based treatment. PMID:27435714
Barriers to community-based drug dependence treatment: implications for police roles, collaborations and performance indicators.

PubMed

Ma, Yi; Du, Chunhua; Cai, Thomas; Han, Qingfeng; Yuan, Huanhuan; Luo, Tingyan; Ren, Guoliang; Mburu, Gitau; Wang, Bangyuan; Golichenko, Olga; Zhang, Chaoxiong

2016-01-01

Worldwide, people who use drugs (PWUD) are among the populations at highest risk for HIV infection. In China, PWUD are primarily sentenced to compulsory detainment centres, in which access to healthcare, including HIV treatment and prevention services, is limited or non-existent. In 2008, China's 2008 Anti-Drug Law encouraged the development and use of community-based drug dependence rehabilitation, yet there is limited evidence evaluating the efficacy and challenges of this model in China. In this study, we explore these challenges and describe how cooperation between law enforcement and health departments can meet the needs of PWUD. In 2015, we conducted semi-structured, in-depth interviews with all four staff members and 16 clients of the Ping An Centre No. 1 for community-based drug treatment, three local police officers and three officials from the local Centre for Disease Control. Interviews explored obstacles in implementing community-based drug dependence treatment and efforts to resolve these difficulties. Transcripts were coded and analyzed with qualitative data analysis software (MAXQDA 11). We identified three challenges to community-based drug treatment at the Ping An Centre No. 1: (1) suboptimal coordination among parties involved, (2) a divergence in attitudes towards PWUD and harm reduction between law enforcement and health officials and (3) conflicting performance targets for police and health officials that undermine the shared goal of treatment. We also identified the take-home methadone maintenance treatment model at the Ping An Centre No. 1 as an example of an early successful collaboration between the police, the health department and PWUD. To overcome barriers to effective community-based drug treatment, we recommend aligning the goals of law enforcement and public health agencies towards health-based performance indicators. Furthermore, tensions between PWUD and police need to be addressed and trust between them fostered, using community-based treatment centres as mediators. The preliminary success of the take-home methadone maintenance treatment pilot can serve as an example of how collaboration with the police and other government agencies can meet the needs of PWUD and contribute to the success of community-based treatment.
Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.

PubMed

Chen, Ming-Huang; Yang, Wu-Lung R; Lin, Kuan-Ting; Liu, Chia-Hung; Liu, Yu-Wen; Huang, Kai-Wen; Chang, Peter Mu-Hsin; Lai, Jin-Mei; Hsu, Chun-Nan; Chao, Kun-Mao; Kao, Cheng-Yan; Huang, Chi-Ying F

2011-01-01

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.
Plasma vs heart tissue concentration in humans - literature data analysis of drugs distribution.

PubMed

Tylutki, Zofia; Polak, Sebastian

2015-03-12

Little is known about the uptake of drugs into the human heart, although it is of great importance nowadays, when science desires to predict tissue level behavior rather than to measure it. Although the drug concentration in cardiac tissue seems a better predictor for physiological and electrophysiological changes than its level in plasma, knowledge of this value is very limited. Tissue to plasma partition coefficients (Kp) come to rescue since they characterize the distribution of a drug among tissues as being one of the input parameters in physiologically based pharmacokinetic (PBPK) models. The article reviews cardiac surgery and forensic medical studies to provide a reference for drug concentrations in human cardiac tissue. Firstly, the focus is on whether a drug penetrates into heart tissue at a therapeutic level; the provided values refer to antibiotics, antifungals and anticancer drugs. Drugs that directly affect cardiomyocyte electrophysiology are another group of interest. Measured levels of amiodarone, digoxin, perhexiline and verapamil in different sites in human cardiac tissue where the compounds might meet ion channels, gives an insight into how these more lipophilic drugs penetrate the heart. Much data are derived from postmortem studies and they provide insight to the cardiac distribution of more than 200 drugs. The analysis depicts potential problems in defining the active concentration location, what may indirectly suggest multiple mechanisms involved in the drug distribution within the heart. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
Gender Differences in Drug Resistance Skills of Youth in Guanajuato, Mexico

PubMed Central

Marsiglia, Flavio F.; Ayers, Stephanie L.; Calderón-Tena, Carlos O.; Nuño-Gutiérrez, Bertha L.

2011-01-01

Research is limited or absent on Mexican adolescents’ exposure to substance offers, ways of dealing with these offers, and possible gender differences in responses to offers. Extending U.S.-based research, this study examines how youth living in the Mexican state of Guanajuato employ the four drug resistance strategies—refuse, explain, avoid, and leave—that are part of the Keepin’ It REAL evidence-based drug prevention intervention. The analysis uses cross-sectional survey data from 702 students enrolled in eight alternative secondary education sites in 2007. Participants reported the drug resistance behaviors they used to deal with offers of alcohol, cigarettes, and marijuana. Using multivariate regression, findings indicate most youth had developed repertoires of drug resistance strategies that involved multiple REAL strategies and some other strategy as well. For those receiving offers, the most common strategy was to refuse the offer with a simple ‘‘no.’’ However, males used all the strategies significantly more often than females for situations involving cigarettes and marijuana as well as when using refuse and non-REAL strategies for alcohol. Possible reasons for the gender difference in use of strategies are discussed. The findings can help inform effective prevention programs based on teaching culturally appropriate drug resistance and communication skills. PMID:21424398
A Study on Pharmacokinetics of Bosentan with Systems Modeling, Part 1: Translating Systemic Plasma Concentration to Liver Exposure in Healthy Subjects.

PubMed

Li, Rui; Niosi, Mark; Johnson, Nathaniel; Tess, David A; Kimoto, Emi; Lin, Jian; Yang, Xin; Riccardi, Keith A; Ryu, Sangwoo; El-Kattan, Ayman F; Maurer, Tristan S; Tremaine, Larry M; Di, Li

2018-04-01

Understanding liver exposure of hepatic transporter substrates in clinical studies is often critical, as it typically governs pharmacodynamics, drug-drug interactions, and toxicity for certain drugs. However, this is a challenging task since there is currently no easy method to directly measure drug concentration in the human liver. Using bosentan as an example, we demonstrate a new approach to estimate liver exposure based on observed systemic pharmacokinetics from clinical studies using physiologically based pharmacokinetic modeling. The prediction was verified to be both accurate and precise using sensitivity analysis. For bosentan, the predicted pseudo steady-state unbound liver-to-unbound systemic plasma concentration ratio was 34.9 (95% confidence interval: 4.2, 50). Drug-drug interaction (i.e., CYP3A and CYP2B6 induction) and inhibition of hepatic transporters (i.e., bile salt export pump, multidrug resistance-associated proteins, and sodium-taurocholate cotransporting polypeptide) were predicted based on the estimated unbound liver tissue or plasma concentrations. With further validation and refinement, we conclude that this approach may serve to predict human liver exposure and complement other methods involving tissue biopsy and imaging. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.
The impact of genetics on future drug discovery in schizophrenia.

PubMed

Matsumoto, Mitsuyuki; Walton, Noah M; Yamada, Hiroshi; Kondo, Yuji; Marek, Gerard J; Tajinda, Katsunori

2017-07-01

Failures of investigational new drugs (INDs) for schizophrenia have left huge unmet medical needs for patients. Given the recent lackluster results, it is imperative that new drug discovery approaches (and resultant drug candidates) target pathophysiological alterations that are shared in specific, stratified patient populations that are selected based on pre-identified biological signatures. One path to implementing this paradigm is achievable by leveraging recent advances in genetic information and technologies. Genome-wide exome sequencing and meta-analysis of single nucleotide polymorphism (SNP)-based association studies have already revealed rare deleterious variants and SNPs in patient populations. Areas covered: Herein, the authors review the impact that genetics have on the future of schizophrenia drug discovery. The high polygenicity of schizophrenia strongly indicates that this disease is biologically heterogeneous so the identification of unique subgroups (by patient stratification) is becoming increasingly necessary for future investigational new drugs. Expert opinion: The authors propose a pathophysiology-based stratification of genetically-defined subgroups that share deficits in particular biological pathways. Existing tools, including lower-cost genomic sequencing and advanced gene-editing technology render this strategy ever more feasible. Genetically complex psychiatric disorders such as schizophrenia may also benefit from synergistic research with simpler monogenic disorders that share perturbations in similar biological pathways.
Transcriptome inference and systems approaches to polypharmacology and drug discovery in herbal medicine.

PubMed

Li, Peng; Chen, Jianxin; Zhang, Wuxia; Fu, Bangze; Wang, Wei

2017-01-04

Herbal medicine is a concoction of numerous chemical ingredients, and it exhibits polypharmacological effects to act on multiple pharmacological targets, regulating different biological mechanisms and treating a variety of diseases. Thus, this complexity is impossible to deconvolute by the reductionist method of extracting one active ingredient acting on one biological target. To dissect the polypharmacological effects of herbal medicines and their underling pharmacological targets as well as their corresponding active ingredients. We propose a system-biology strategy that combines omics and bioinformatical methodologies for exploring the polypharmacology of herbal mixtures. The myocardial ischemia model was induced by Ameroid constriction of the left anterior descending coronary in Ba-Ma miniature pigs. RNA-seq analysis was utilized to find the differential genes induced by myocardial ischemia in pigs treated with formula QSKL. A transcriptome-based inference method was used to find the landmark drugs with similar mechanisms to QSKL. Gene-level analysis of RNA-seq data in QSKL-treated cases versus control animals yields 279 differential genes. Transcriptome-based inference methods identified 80 landmark drugs that covered nearly all drug classes. Then, based on the landmark drugs, 155 potential pharmacological targets and 57 indications were identified for QSKL. Our results demonstrate the power of a combined approach for exploring the pharmacological target and chemical space of herbal medicines. We hope that our method could enhance our understanding of the molecular mechanisms of herbal systems and further accelerate the exploration of the value of traditional herbal medicine systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.
Intrinsic disruption of white matter microarchitecture in first-episode, drug-naive major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging.

PubMed

Chen, Guangxiang; Guo, Yi; Zhu, Hongyan; Kuang, Weihong; Bi, Feng; Ai, Hua; Gu, Zhongwei; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2017-06-02

Previous studies have demonstrated the influences of episodes and antidepressant drugs on white matter (WM) in patients with major depressive disorder (MDD). However, most diffusion tensor imaging (DTI) studies included highly heterogeneous individuals with different numbers of depressive episodes or medication status. To exclude the confounding effects of multiple episodes or medication, we conducted a quantitative voxel-based meta-analysis of fractional anisotropy (FA) in patients with first-episode, drug-naive MDD to identify the intrinsic WM alterations involved in the pathogenesis of MDD. The pooled meta-analysis revealed significant FA reductions in the body of the corpus callosum (CC), bilateral anterior limb of the internal capsule (ALIC), right inferior temporal gyrus (ITG) and right superior frontal gyrus (SFG) in MDD patients relative to healthy controls. Meta-regression analyses revealed that FA reduction in the right ALIC and right SFG was negatively correlated with symptom severity and duration of depression, respectively. Our findings provide robust evidence that the WM impairments in the interhemispheric connections and frontal-subcortical neuronal circuits may play an important role in MDD pathogenesis. Copyright © 2017. Published by Elsevier Inc.
P1-Substituted Symmetry-Based Human Immunodeficiency Virus Protease Inhibitors with Potent Antiviral Activity against Drug-Resistant Viruses

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeGoey, David A.; Grampovnik, David J.; Chen, Hui-Ju

2013-03-07

Because there is currently no cure for HIV infection, patients must remain on long-term drug therapy, leading to concerns over potential drug side effects and the emergence of drug resistance. For this reason, new and safe antiretroviral agents with improved potency against drug-resistant strains of HIV are needed. A series of HIV protease inhibitors (PIs) with potent activity against both wild-type (WT) virus and drug-resistant strains of HIV was designed and synthesized. The incorporation of substituents with hydrogen bond donor and acceptor groups at the P1 position of our symmetry-based inhibitor series resulted in significant potency improvements against the resistantmore » mutants. By this approach, several compounds, such as 13, 24, and 29, were identified that demonstrated similar or improved potencies compared to 1 against highly mutated strains of HIV derived from patients who previously failed HIV PI therapy. Overall, compound 13 demonstrated the best balance of potency against drug resistant strains of HIV and oral bioavailability in pharmacokinetic studies. X-ray analysis of an HIV PI with an improved resistance profile bound to WT HIV protease is also reported.« less
Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169
Anticancer drugs in Portuguese surface waters - Estimation of concentrations and identification of potentially priority drugs.

PubMed

Santos, Mónica S F; Franquet-Griell, Helena; Lacorte, Silvia; Madeira, Luis M; Alves, Arminda

2017-10-01

Anticancer drugs, used in chemotherapy, have emerged as new water contaminants due to their increasing consumption trends and poor elimination efficiency in conventional water treatment processes. As a result, anticancer drugs have been reported in surface and even drinking waters, posing the environment and human health at risk. However, the occurrence and distribution of anticancer drugs depend on the area studied and the hydrological dynamics, which determine the risk towards the environment. The main objective of the present study was to evaluate the risk of anticancer drugs in Portugal. This work includes an extensive analysis of the consumption trends of 171 anticancer drugs, sold or dispensed in Portugal between 2007 and 2015. The consumption data was processed aiming at the estimation of predicted environmental loads of anticancer drugs and 11 compounds were identified as potentially priority drugs based on an exposure-based approach (PEC b > 10 ng L -1 and/or PEC c > 1 ng L -1 ). In a national perspective, mycophenolic acid and mycophenolate mofetil are suspected to pose high risk to aquatic biota. Moderate and low risk was also associated to cyclophosphamide and bicalutamide exposition, respectively. Although no evidences of risk exist yet for the other anticancer drugs, concerns may be associated with long term effects. Copyright © 2017 Elsevier Ltd. All rights reserved.
Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661
Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.
Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis

PubMed Central

2011-01-01

Background The computer-aided identification of specific gait patterns is an important issue in the assessment of Parkinson's disease (PD). In this study, a computer vision-based gait analysis approach is developed to assist the clinical assessments of PD with kernel-based principal component analysis (KPCA). Method Twelve PD patients and twelve healthy adults with no neurological history or motor disorders within the past six months were recruited and separated according to their "Non-PD", "Drug-On", and "Drug-Off" states. The participants were asked to wear light-colored clothing and perform three walking trials through a corridor decorated with a navy curtain at their natural pace. The participants' gait performance during the steady-state walking period was captured by a digital camera for gait analysis. The collected walking image frames were then transformed into binary silhouettes for noise reduction and compression. Using the developed KPCA-based method, the features within the binary silhouettes can be extracted to quantitatively determine the gait cycle time, stride length, walking velocity, and cadence. Results and Discussion The KPCA-based method uses a feature-extraction approach, which was verified to be more effective than traditional image area and principal component analysis (PCA) approaches in classifying "Non-PD" controls and "Drug-Off/On" PD patients. Encouragingly, this method has a high accuracy rate, 80.51%, for recognizing different gaits. Quantitative gait parameters are obtained, and the power spectrums of the patients' gaits are analyzed. We show that that the slow and irregular actions of PD patients during walking tend to transfer some of the power from the main lobe frequency to a lower frequency band. Our results indicate the feasibility of using gait performance to evaluate the motor function of patients with PD. Conclusion This KPCA-based method requires only a digital camera and a decorated corridor setup. The ease of use and installation of the current method provides clinicians and researchers a low cost solution to monitor the progression of and the treatment to PD. In summary, the proposed method provides an alternative to perform gait analysis for patients with PD. PMID:22074315

Pregnancy-induced changes in pharmacokinetics: a mechanistic-based approach.

PubMed

Anderson, Gail D

2005-01-01

Observational studies have documented that women take a variety of medications during pregnancy. It is well known that pregnancy can induce changes in the plasma concentrations of some drugs. The use of mechanistic-based approaches to drug interactions has significantly increased our ability to predict clinically significant drug interactions and improve clinical care. This same method can also be used to improve our understanding regarding the effect of pregnancy on pharmacokinetics of drugs. Limited studies suggest bioavailability of drugs is not altered during pregnancy. Increased plasma volume and protein binding changes can alter the apparent volume of distribution (Vd) of drugs. Through changes in Vd and clearance, pregnancy can cause increases or decreases in the terminal elimination half-life of drugs. Depending on whether a drug is excreted unchanged by the kidneys or which metabolic isoenzyme is involved in the metabolism of a drug can determine whether or not a change in dosage is needed during pregnancy. The renal excretion of unchanged drugs is increased during pregnancy. The metabolism of drugs catalysed by select cytochrome P450 (CYP) isoenzymes (i.e. CYP3A4, CYP2D6 and CYP2C9) and uridine diphosphate glucuronosyltransferase (UGT) isoenzymes (i.e. UGT1A4 and UGT2B7) are increased during pregnancy. Dosages of drugs predominantly metabolised by these isoenzymes or excreted by the kidneys unchanged may need to be increased during pregnancy in order to avoid loss of efficacy. In contrast, CYP1A2 and CYP2C19 activity is decreased during pregnancy, suggesting that dosage reductions may be needed to minimise potential toxicity of their substrates. There are limitations to the available data. This analysis is based primarily on observational studies, many including small numbers of women. For some isoenzymes, the effect of pregnancy on only one drug has been evaluated. The full-time course of pharmacokinetic changes during pregnancy is often not studied. The effect of pregnancy on transport proteins is unknown. Drugs eliminated by non-CYP or non-UGT pathways or multiple pathways will need to be evaluated individually. In conclusion, by evaluating the pharmacokinetic data of a variety of drugs during pregnancy and using a mechanistic-based approach, we can start to predict the effect of pregnancy for a large number of clinically used drugs. However, because of the limitations, more clinical, evidence-based studies are needed to fully elucidate the effects of pregnancy on the pharmacokinetics of drugs.
Nanocarriers for delivery of platinum anticancer drugs☆

PubMed Central

Oberoi, Hardeep S.; Nukolova, Natalia V.; Kabanov, Alexander V.; Bronich, Tatiana K.

2014-01-01

Platinum based anticancer drugs have revolutionized cancer chemotherapy, and continue to be in widespread clinical use especially for management of tumors of the ovary, testes, and the head and neck. However, several dose limiting toxicities associated with platinum drug use, partial anti-tumor response in most patients, development of drug resistance, tumor relapse, and many other challenges have severely limited the patient quality of life. These limitations have motivated an extensive research effort towards development of new strategies for improving platinum therapy. Nanocarrier-based delivery of platinum compounds is one such area of intense research effort beginning to provide encouraging preclinical and clinical results and may allow the development of the next generation of platinum chemotherapy. This review highlights current understanding on the pharmacology and limitations of platinum compounds in clinical use, and provides a comprehensive analysis of various platinum–polymer complexes, micelles, dendrimers, liposomes and other nanoparticles currently under investigation for delivery of platinum drugs. PMID:24113520
[Investigation on pattern of quality control for Chinese materia medica based on famous-region drug and bioassay--the work reference].

PubMed

Yan, Dan; Xiao, Xiaohe

2011-05-01

Selection and standardization of the work reference are the technical issues to be faced with in the bioassay of Chinese materia medica. Taking the bioassay of Coptis chinensis. as an example, the manufacture process of the famous-region drugs extraction was explained from the aspects of original identification, routine examination, component analysis and bioassay. The common technologies were extracted, and the selection and standardization procedures of the work reference for the bioassay of Chinese materia medica were drawn up, so as to provide technical support for constructing a new mode and method of the quality control of Chinese materia medica based on the famous-region drugs and bioassay.
The Federal Response to Drug Abuse: 1976-1980

PubMed Central

Brown, Lawrence S.; Stuart, Janet C.

1980-01-01

Drug use remains a prominent aspect of the American environment. Consequently, this analysis was undertaken to examine the current as well as the projected role of the federal government in drug abuse. Based on an examination of federal expenditures between the years of 1976 and 1980, the intelligence, corrections, interdictions, federal prosecutions, and compliance categories have increased their proportions of the budget, but not enough to compensate for inflation. Based on the foregoing, there is a continuing desire for states to increase their operational responsibilities; however, a well-structured mechanism for evaluation in law enforcement efforts is lacking. Even so, it appears that the level of concern accorded by the federal government to psychoactive substance use is progressively decreasing. PMID:7401184
Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.
AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, Yingssu; Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080; McPhillips, Scott E.

New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data,more » performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully demonstrated. This workflow was run once on the same 96 samples that the group had examined manually and the workflow cycled successfully through all of the samples, collected data from the same samples that were selected manually and located the same peaks of unmodeled density in the resulting difference Fourier maps.« less
A novel data-mining approach leveraging social media to monitor consumer opinion of sitagliptin.

PubMed

Akay, Altug; Dragomir, Andrei; Erlandsson, Björn-Erik

2015-01-01

A novel data mining method was developed to gauge the experience of the drug Sitagliptin (trade name Januvia) by patients with diabetes mellitus type 2. To this goal, we devised a two-step analysis framework. Initial exploratory analysis using self-organizing maps was performed to determine structures based on user opinions among the forum posts. The results were a compilation of user's clusters and their correlated (positive or negative) opinion of the drug. Subsequent modeling using network analysis methods was used to determine influential users among the forum members. These findings can open new avenues of research into rapid data collection, feedback, and analysis that can enable improved outcomes and solutions for public health and important feedback for the manufacturer.
Benefit-Risk Analysis for Decision-Making: An Approach.

PubMed

Raju, G K; Gurumurthi, K; Domike, R

2016-12-01

The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.
Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

PubMed

Bender, Andreas; Scheiber, Josef; Glick, Meir; Davies, John W; Azzaoui, Kamal; Hamon, Jacques; Urban, Laszlo; Whitebread, Steven; Jenkins, Jeremy L

2007-06-01

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions. Firstly, in silico (computational) Bayesian models for 70 PSP-related targets were built, which are able to detect 93% of the ligands binding at IC(50) < or = 10 microM at an overall correct classification rate of about 94%. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side-effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90% of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92%. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back-projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid mu and the muscarinic M2 receptors, as well as for cyclooxygenase-1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.
Quality Testing of Artemisinin-Based Antimalarial Drugs in Myanmar.

PubMed

Guo, Suqin; Kyaw, Myat Phone; He, Lishan; Min, Myo; Ning, Xiangxue; Zhang, Wei; Wang, Baomin; Cui, Liwang

2017-10-01

Artemisinin-based combination therapies are the frontline treatment of Plasmodium falciparum malaria. The circulation of falsified and substandard artemisinin-based antimalarials in Southeast Asia has been a major predicament for the malaria elimination campaign. To provide an update of this situation, we purchased 153 artemisinin-containing antimalarials, as convenience samples, in private drug stores from different regions of Myanmar. The quality of these drugs in terms of their artemisinin derivative content was tested using specific dipsticks for these artemisinin derivatives, as point-of-care devices. A subset of these samples was further tested by high-performance liquid chromatography (HPLC). This survey identified that > 35% of the collected drugs were oral artesunate and artemether monotherapies. When tested with the dipsticks, all but one sample passed the assays, indicating that the detected artemisinin derivative content corresponded approximately to the labeled contents. However, one artesunate injection sample was found to contain no active ingredient at all by the dipstick assay and subsequent HPLC analysis. The continued circulation of oral monotherapies and the description, for the first time, of falsified parenteral artesunate provides a worrisome picture of the antimalarial drug quality in Myanmar during the malaria elimination phase, a situation that deserves more oversight from regulatory authorities.
Computer aided drug design

NASA Astrophysics Data System (ADS)

Jain, A.

2017-08-01

Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.
Designing Dietary Recommendations Using System Level Interactomics Analysis and Network-Based Inference

PubMed Central

Zheng, Tingting; Ni, Yueqiong; Li, Jun; Chow, Billy K. C.; Panagiotou, Gianni

2017-01-01

Background: A range of computational methods that rely on the analysis of genome-wide expression datasets have been developed and successfully used for drug repositioning. The success of these methods is based on the hypothesis that introducing a factor (in this case, a drug molecule) that could reverse the disease gene expression signature will lead to a therapeutic effect. However, it has also been shown that globally reversing the disease expression signature is not a prerequisite for drug activity. On the other hand, the basic idea of significant anti-correlation in expression profiles could have great value for establishing diet-disease associations and could provide new insights into the role of dietary interventions in disease. Methods: We performed an integrated analysis of publicly available gene expression profiles for foods, diseases and drugs, by calculating pairwise similarity scores for diet and disease gene expression signatures and characterizing their topological features in protein-protein interaction networks. Results: We identified 485 diet-disease pairs where diet could positively influence disease development and 472 pairs where specific diets should be avoided in a disease state. Multiple evidence suggests that orange, whey and coconut fat could be beneficial for psoriasis, lung adenocarcinoma and macular degeneration, respectively. On the other hand, fructose-rich diet should be restricted in patients with chronic intermittent hypoxia and ovarian cancer. Since humans normally do not consume foods in isolation, we also applied different algorithms to predict synergism; as a result, 58 food pairs were predicted. Interestingly, the diets identified as anti-correlated with diseases showed a topological proximity to the disease proteins similar to that of the corresponding drugs. Conclusions: In conclusion, we provide a computational framework for establishing diet-disease associations and additional information on the role of diet in disease development. Due to the complexity of analyzing the food composition and eating patterns of individuals our in silico analysis, using large-scale gene expression datasets and network-based topological features, may serve as a proof-of-concept in nutritional systems biology for identifying diet-disease relationships and subsequently designing dietary recommendations. PMID:29033850
Developments for Personalized Medicine of Lung Cancer Subtypes: Mass Spectrometry-Based Clinical Proteogenomic Analysis of Oncogenic Mutations.

PubMed

Nishimura, Toshihide; Nakamura, Haruhiko

2016-01-01

Molecular therapies targeting lung cancers with mutated epidermal growth factor receptor (EGFR) by EGFR-tyrosin kinase inhibitors (EGFR-TKIs), gefitinib and erlotinib, changed the treatment system of lung cancer. It was revealed that drug efficacy differs by race (e.g., Caucasians vs. Asians) due to oncogenic driver mutations specific to each race, exemplified by gefitinib / erlotinib. The molecular target drugs for lung cancer with anaplastic lymphoma kinase (ALK) gene translocation (the fusion gene, EML4-ALK) was approved, and those targeting lung cancers addicted ROS1, RET, and HER2 have been under development. Both identification and quantification of gatekeeper mutations need to be performed using lung cancer tissue specimens obtained from patients to improve the treatment for lung cancer patients: (1) identification and quantitation data of targeted mutated proteins, including investigation of mutation heterogeneity within a tissue; (2) exploratory mass spectrometry (MS)-based clinical proteogenomic analysis of mutated proteins; and also importantly (3) analysis of dynamic protein-protein interaction (PPI) networks of proteins significantly related to a subgroup of patients with lung cancer not only with good efficacy but also with acquired resistance. MS-based proteogenomics is a promising approach to directly capture mutated and fusion proteins expressed in a clinical sample. Technological developments are further expected, which will provide a powerful solution for the stratification of patients and drug discovery (Precision Medicine).
[Irrational use of drugs as a source of drug - induced diseases].

PubMed

Woroń, Jarosław; Porebski, Grzegorz; Kostka-Trabka, Elzbieta; Goszcz, Aleksandra

2007-01-01

The irrational use of medication, by which we understand the administration of drugs for indications where their effectiveness has not been confirmed, the disregard of restrictions and warnings against their use, and the use of drug combinations which do not increase the therapeutic effect but to the contrary increase the risk of adverse drug reactions, is a serious problem encountered in paediatric pharmacotherapy. Each year the centres for monitoring of adverse drug reactions receive many reports, the analysis of which show that the reasons of occurrence of adverse drug reactions after drug administration, are specifically due to irrational use of medications. In order to prevent in an active way the occurrence, of adverse drug reactions following drug administration it is worthwhile to bring to attention the reasons for their occurrence which not infrequently bring about pathological effects. Our work which is based on reports received by the Regional Centre for Adverse Drug Reactions Monitoring in Krakow concerning the occurrence of adverse drug reactions in an attempt to bring to attention in our view important problems in current pharmacotherapy.
A new in vitro lipid digestion - in vivo absorption model to evaluate the mechanisms of drug absorption from lipid-based formulations.

PubMed

Crum, Matthew F; Trevaskis, Natalie L; Williams, Hywel D; Pouton, Colin W; Porter, Christopher J H

2016-04-01

In vitro lipid digestion models are commonly used to screen lipid-based formulations (LBF), but in vitro-in vivo correlations are in some cases unsuccessful. Here we enhance the scope of the lipid digestion test by incorporating an absorption 'sink' into the experimental model. An in vitro model of lipid digestion was coupled directly to a single pass in situ intestinal perfusion experiment in an anaesthetised rat. The model allowed simultaneous real-time analysis of the digestion and absorption of LBFs of fenofibrate and was employed to evaluate the influence of formulation digestion, supersaturation and precipitation on drug absorption. Formulations containing higher quantities of co-solvent and surfactant resulted in higher supersaturation and more rapid drug precipitation in vitro when compared to those containing higher quantities of lipid. In contrast, when the same formulations were examined using the coupled in vitro lipid digestion - in vivo absorption model, drug flux into the mesenteric vein was similar regardless of in vitro formulation performance. For some drugs, simple in vitro lipid digestion models may underestimate the potential for absorption from LBFs. Consistent with recent in vivo studies, drug absorption for rapidly absorbed drugs such as fenofibrate may occur even when drug precipitation is apparent during in vitro digestion.
Polyox and carrageenan based composite film dressing containing anti-microbial and anti-inflammatory drugs for effective wound healing.

PubMed

Boateng, Joshua S; Pawar, Harshavardhan V; Tetteh, John

2013-01-30

Polyethylene oxide (Polyox) and carrageenan based solvent cast films have been formulated as dressings for drug delivery to wounds. Films plasticised with glycerol were loaded with streptomycin (30%, w/w) and diclofenac (10%, w/w) for enhanced healing effects in chronic wounds. Blank and drug loaded films were characterised by texture analysis (for mechanical and mucoadhesive properties), scanning electron microscopy, differential scanning calorimetry, X-ray diffraction and Fourier transform infrared spectroscopy. In addition, swelling, in vitro drug release and antibacterial studies were conducted to further characterise the films. Both blank and drug loaded films showed a smooth, homogeneous surface morphology, excellent transparency, high elasticity and acceptable tensile (mechanical) properties. The drug loaded films showed a high capacity to absorb simulated wound fluid and significant mucoadhesion force which is expected to allow effective adherence to and protection of the wound. The films showed controlled release of both streptomycin and diclofenac for 72 h. These drug loaded films produced higher zones of inhibition against Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli compared to the individual drugs zones of inhibition. Incorporation of streptomycin can prevent and treat chronic wound infections whereas diclofenac can target the inflammatory phase of wound healing to relieve pain and swelling. Copyright © 2012 Elsevier B.V. All rights reserved.
Return to drug use and overdose after release from prison: a qualitative study of risk and protective factors.

PubMed

Binswanger, Ingrid A; Nowels, Carolyn; Corsi, Karen F; Glanz, Jason; Long, Jeremy; Booth, Robert E; Steiner, John F

2012-01-01

Former inmates are at high risk for death from drug overdose, especially in the immediate post-release period. The purpose of the study is to understand the drug use experiences, perceptions of overdose risk, and experiences with overdose among former prisoners. This qualitative study included former prison inmates (N=29) who were recruited within two months after their release. Interviewers conducted in-person, semi-structured interviews which explored participants' experiences and perceptions. Transcripts were analyzed utilizing a team-based method of inductive analysis. The following themes emerged: 1) Relapse to drugs and alcohol occurred in a context of poor social support, medical co-morbidity and inadequate economic resources; 2) former inmates experienced ubiquitous exposure to drugs in their living environments; 3) intentional overdose was considered "a way out" given situational stressors, and accidental overdose was perceived as related to decreased tolerance; and 4) protective factors included structured drug treatment programs, spirituality/religion, community-based resources (including self-help groups), and family. Former inmates return to environments that strongly trigger relapse to drug use and put them at risk for overdose. Interventions to prevent overdose after release from prison may benefit from including structured treatment with gradual transition to the community, enhanced protective factors, and reductions of environmental triggers to use drugs.
C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms

PubMed Central

Alam, Zaid; Peddinti, Gopal

2017-01-01

Abstract The advent of polypharmacology paradigm in drug discovery calls for novel chemoinformatic tools for analyzing compounds’ multi-targeting activities. Such tools should provide an intuitive representation of the chemical space through capturing and visualizing underlying patterns of compound similarities linked to their polypharmacological effects. Most of the existing compound-centric chemoinformatics tools lack interactive options and user interfaces that are critical for the real-time needs of chemical biologists carrying out compound screening experiments. Toward that end, we introduce C-SPADE, an open-source exploratory web-tool for interactive analysis and visualization of drug profiling assays (biochemical, cell-based or cell-free) using compound-centric similarity clustering. C-SPADE allows the users to visually map the chemical diversity of a screening panel, explore investigational compounds in terms of their similarity to the screening panel, perform polypharmacological analyses and guide drug-target interaction predictions. C-SPADE requires only the raw drug profiling data as input, and it automatically retrieves the structural information and constructs the compound clusters in real-time, thereby reducing the time required for manual analysis in drug development or repurposing applications. The web-tool provides a customizable visual workspace that can either be downloaded as figure or Newick tree file or shared as a hyperlink with other users. C-SPADE is freely available at http://cspade.fimm.fi/. PMID:28472495
Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.
The educational value of consumer-targeted prescription drug print advertising.

PubMed

Bell, R A; Wilkes, M S; Kravitz, R L

2000-12-01

The case for direct-to-consumer (DTC) prescription drug advertising has often been based on the argument that such promotions can educate the public about medical conditions and associated treatments. Our content analysis of DTC advertising assessed the extent to which such educational efforts have been attempted. We collected advertisements appearing in 18 popular magazines from 1989 through 1998. Two coders independently evaluated 320 advertisements encompassing 101 drug brands to determine if information appeared about specific aspects of the medical conditions for which the drug was promoted and about the treatment (mean kappa reliability=0.91). We employed basic descriptive statistics using the advertisement as the unit of analysis and cross-tabulations using the brand as the unit of analysis. Virtually all the advertisements gave the name of the condition treated by the promoted drug, and a majority provided information about the symptoms of that condition. However, few reported details about the condition's precursors or its prevalence; attempts to clarify misconceptions about the condition were also rare. The advertisements seldom provided information about the drug's mechanism of action, its success rate, treatment duration, alternative treatments, and behavioral changes that could enhance the health of affected patients. Informative advertisements were identified, but most of the promotions provided only a minimal amount of information. Strategies for improving the educational value of DTC advertisements are considered.

Cognition-Enhancing Drugs and Their Appropriateness for Aviation and Ground Troops: A Meta-Analysis

DTIC Science & Technology

2010-12-01

individuals is not approved by the Food and Drug Administration (FDA). Current indications include narcolepsy, obstructive sleep apnea/hypopnea syndrome, and...to caffeine and perceived effects of caffeine in moderate and high regular caffeine consumers . Psychopharmacology. 190: 469-477...J. 2004. The effect of caffeinated tube food on cognitive performance during fatigue/circadian desynchronosis. Brooks City-Base, TX
qPCR-High resolution melt analysis for drug susceptibility testing of Mycobacterium leprae directly from clinical specimens of leprosy patients.

PubMed

Araujo, Sergio; Goulart, Luiz Ricardo; Truman, Richard W; Goulart, Isabela Maria B; Vissa, Varalakshmi; Li, Wei; Matsuoka, Masanori; Suffys, Philip; Fontes, Amanda B; Rosa, Patricia S; Scollard, David M; Williams, Diana L

2017-06-01

Real-Time PCR-High Resolution Melting (qPCR-HRM) analysis has been recently described for rapid drug susceptibility testing (DST) of Mycobacterium leprae. The purpose of the current study was to further evaluate the validity, reliability, and accuracy of this assay for M. leprae DST in clinical specimens. The specificity and sensitivity for determining the presence and susceptibility of M. leprae to dapsone based on the folP1 drug resistance determining region (DRDR), rifampin (rpoB DRDR) and ofloxacin (gyrA DRDR) was evaluated using 211 clinical specimens from leprosy patients, including 156 multibacillary (MB) and 55 paucibacillary (PB) cases. When comparing the results of qPCR-HRM DST and PCR/direct DNA sequencing, 100% concordance was obtained. The effects of in-house phenol/chloroform extraction versus column-based DNA purification protocols, and that of storage and fixation protocols of specimens for qPCR-HRM DST, were also evaluated. qPCR-HRM results for all DRDR gene assays (folP1, rpoB, and gyrA) were obtained from both MB (154/156; 98.7%) and PB (35/55; 63.3%) patients. All PCR negative specimens were from patients with low numbers of bacilli enumerated by an M. leprae-specific qPCR. We observed that frozen and formalin-fixed paraffin embedded (FFPE) tissues or archival Fite's stained slides were suitable for HRM analysis. Among 20 mycobacterial and other skin bacterial species tested, only M. lepromatosis, highly related to M. leprae, generated amplicons in the qPCR-HRM DST assay for folP1 and rpoB DRDR targets. Both DNA purification protocols tested were efficient in recovering DNA suitable for HRM analysis. However, 3% of clinical specimens purified using the phenol/chloroform DNA purification protocol gave false drug resistant data. DNA obtained from freshly frozen (n = 172), formalin-fixed paraffin embedded (FFPE) tissues (n = 36) or archival Fite's stained slides (n = 3) were suitable for qPCR-HRM DST analysis. The HRM-based assay was also able to identify mixed infections of susceptible and resistant M. leprae. However, to avoid false positives we recommend that clinical specimens be tested for the presence of the M. leprae using the qPCR-RLEP assay prior to being tested in the qPCR-HRM DST and that all specimens demonstrating drug resistant profiles in this assay be subjected to DNA sequencing. Taken together these results further demonstrate the utility of qPCR-HRM DST as an inexpensive screening tool for large-scale drug resistance surveillance in leprosy.
Increased in synthetic cannabinoids-related harms: results from a longitudinal web-based content analysis

PubMed Central

Lamy, Francois R.; Daniulaityte, Raminta; Nahhas, Ramzi W.; Barratt, Monica J.; Smith, Alan G.; Sheth, Amit; Martins, Silvia S.; Boyer, Edward W.; Carlson, Robert G.

2017-01-01

Background Synthetic Cannabinoid Receptor Agonists (SCRA), also known as “K2” or “Spice,” have drawn considerable attention due to their potential of abuse and harmful consequences. More research is needed to understand user experiences of SCRA-related effects. We use semiautomated information processing techniques through eDrugTrends platform to examine SCRA-related effects and their variations through a longitudinal content analysis of web-forum data. Method English language posts from three drug-focused web-forums were extracted and analyzed between January 1st 2008 and September 30th 2015. Search terms are based on the Drug Abuse Ontology (DAO) created for this study (189 SCRA-related and 501 effect-related terms). EDrugTrends NLP-based text processing tools were used to extract posts mentioning SCRA and their effects. Generalized linear regression was used to fit restricted cubic spline functions of time to test whether the proportion of drug-related posts that mention SCRA (and no other drug) and the proportion of these “SCRA-only” posts that mention SCRA effects have changed over time, with an adjustment for multiple testing. Results 19,052 SCRA-related posts (Bluelight (n=2,782), Forum A (n=3,882), and Forum B (n=12,388)) posted by 2,543 international users were extracted. The most frequently mentioned effects were “getting high” (44.0%), “hallucinations” (10.8%), and “anxiety” (10.2%). The frequency of SCRA-only posts declined steadily over the study period. The proportions of SCRA-only posts mentioning positive effects (e.g., “High” and “Euphoria”) steadily decreased, while the proportions of SCRA-only posts mentioning negative effects (e.g., “Anxiety,” “Nausea,” “Overdose”) increased over the same period. Conclusion This study's findings indicate that the proportion of negative effects mentioned in web forum posts and linked to SCRA has increased over time, suggesting that recent generations of SCRA generate more harms. This is also one of the first studies to conduct automated content analysis of web forum data related to illicit drug use. PMID:28578250
Technology-based interventions for tobacco and other drug use in university and college students: a systematic review and meta-analysis.

PubMed

Gulliver, Amelia; Farrer, Louise; Chan, Jade K Y; Tait, Robert J; Bennett, Kylie; Calear, Alison L; Griffiths, Kathleen M

2015-02-24

University students have high levels of tobacco and other drug use, yet they are unlikely to seek traditional care. Technology-based interventions are highly relevant to this population. This paper comprises a systematic review and meta-analysis of published randomized trials of technology-based interventions evaluated in a tertiary (university/college) setting for tobacco and other drug use (excluding alcohol). It extends previous reviews by using a broad definition of technology. PubMed, PsycInfo, and the Cochrane databases were searched using keywords, phrases, and MeSH terms. Retrieved abstracts (n = 627) were double screened and coded. Included studies met the following criteria: (1) the study was a randomized trial or a randomized controlled trial (RCT); (2) the sample was composed of students attending a tertiary (e.g., university, college) institution; (3) the intervention was either delivered by or accessed using a technological device or process (e.g., computer/internet, telephone, mobile short message services [SMS]); (4) the age range or mean of the sample was between 18 and 25 years; and (5) the intervention was designed to alter a drug use outcome relating to tobacco or other drugs (excluding alcohol). A total of 12 papers met inclusion criteria for the current review. The majority of included papers examined tobacco use (n = 9; 75%), two studies targeted marijuana use (17%); and one targeted stress, marijuana, alcohol, and tobacco use. A quantitative meta-analysis was conducted on the tobacco use studies using an abstinence outcome measure (n = 6), demonstrating that the interventions increased the rate of abstinence by 1.5 times that of controls (Risk Ratio [RR] = 1.54; 95% Confidence Interval [CI] = 1.20-1.98). Across all 12 studies, a total of 20 technology-based interventions were reviewed. A range of technology was employed in the interventions, including stand-alone computer programs (n = 10), internet (n = 5), telephone (n = 3), and mobile SMS (n = 2). Although technological interventions have the potential to reduce drug use in tertiary students, very few trials have been conducted, particularly for substances other than tobacco. However, the improvement shown in abstinence from tobacco use has the potential to impact substantially on morbidity and mortality.
The development of a value based pricing index for new drugs in metastatic colorectal cancer.

PubMed

Dranitsaris, George; Truter, Ilse; Lubbe, Martie S

2011-06-01

Worldwide, prices for cancer drugs have been under downward pressure where several governments have mandated price cuts of branded products. A better alternative to government mandated price cuts would be to estimate a final price based on drug performance, cost effectiveness and a country's ability to pay. We developed a global pricing index for new cancer drugs in patients with metastatic colorectal cancer (mCRC) that encompasses all of these attributes. A pharmacoeconomic model was developed to simulate mCRC patients receiving chemotherapy plus a 'new drug' that improves survival by 1.4, 3 and 6months, respectively. Cost and utility data were obtained from cancer centres and oncology nurses (n=112) in Canada, Spain, India, South Africa and Malaysia. Multivariable analysis was then used to develop the pricing index, which considers survival benefit, per capita GDP and income dispersion (as measured by the Gini coefficient) as predictor variables. Higher survival benefits were associated with elevated drug prices, especially in higher income countries such as Canada. For Argentina with a per capita GDP of $15,000 and a Gini coefficient of 51, the index estimated that for a drug which provides a 4month survival benefit in mCRC, the value based price would be $US 630 per dose. In contrast, the same drug in a wealthier country like Norway (per capita GDP=$50,000) could command a price of $US 2,775 per dose. The application of this index to estimate a price based on cost effectiveness and the wealth of a nation would be important for opening dialogue between the key stakeholders and a better alternative to government mandated price cuts. Copyright © 2011 Elsevier Ltd. All rights reserved.
Drug repositioning for enzyme modulator based on human metabolite-likeness.

PubMed

Lee, Yoon Hyeok; Choi, Hojae; Park, Seongyong; Lee, Boah; Yi, Gwan-Su

2017-05-31

Recently, the metabolite-likeness of the drug space has emerged and has opened a new possibility for exploring human metabolite-like candidates in drug discovery. However, the applicability of metabolite-likeness in drug discovery has been largely unexplored. Moreover, there are no reports on its applications for the repositioning of drugs to possible enzyme modulators, although enzyme-drug relations could be directly inferred from the similarity relationships between enzyme's metabolites and drugs. We constructed a drug-metabolite structural similarity matrix, which contains 1,861 FDA-approved drugs and 1,110 human intermediary metabolites scored with the Tanimoto similarity. To verify the metabolite-likeness measure for drug repositioning, we analyzed 17 known antimetabolite drugs that resemble the innate metabolites of their eleven target enzymes as the gold standard positives. Highly scored drugs were selected as possible modulators of enzymes for their corresponding metabolites. Then, we assessed the performance of metabolite-likeness with a receiver operating characteristic analysis and compared it with other drug-target prediction methods. We set the similarity threshold for drug repositioning candidates of new enzyme modulators based on maximization of the Youden's index. We also carried out literature surveys for supporting the drug repositioning results based on the metabolite-likeness. In this paper, we applied metabolite-likeness to repurpose FDA-approved drugs to disease-associated enzyme modulators that resemble human innate metabolites. All antimetabolite drugs were mapped with their known 11 target enzymes with statistically significant similarity values to the corresponding metabolites. The comparison with other drug-target prediction methods showed the higher performance of metabolite-likeness for predicting enzyme modulators. After that, the drugs scored higher than similarity score of 0.654 were selected as possible modulators of enzymes for their corresponding metabolites. In addition, we showed that drug repositioning results of 10 enzymes were concordant with the literature evidence. This study introduced a method to predict the repositioning of known drugs to possible modulators of disease associated enzymes using human metabolite-likeness. We demonstrated that this approach works correctly with known antimetabolite drugs and showed that the proposed method has better performance compared to other drug target prediction methods in terms of enzyme modulators prediction. This study as a proof-of-concept showed how to apply metabolite-likeness to drug repositioning as well as potential in further expansion as we acquire more disease associated metabolite-target protein relations.
Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key.

PubMed

Haupt, V Joachim; Daminelli, Simone; Schroeder, Michael

2013-01-01

Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) - a drug's ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.
Application of Pharmacokinetic and Pharmacodynamic Analysis to the Development of Liposomal Formulations for Oncology

PubMed Central

Ait-Oudhia, Sihem; Mager, Donald E.; Straubinger, Robert M.

2014-01-01

Liposomal formulations of anticancer agents have been developed to prolong drug circulating lifetime, enhance anti-tumor efficacy by increasing tumor drug deposition, and reduce drug toxicity by avoiding critical normal tissues. Despite the clinical approval of numerous liposome-based chemotherapeutics, challenges remain in the development and clinical deployment of micro- and nano-particulate formulations, as well as combining these novel agents with conventional drugs and standard-of-care therapies. Factors requiring optimization include control of drug biodistribution, release rates of the encapsulated drug, and uptake by target cells. Quantitative mathematical modeling of formulation performance can provide an important tool for understanding drug transport, uptake, and disposition processes, as well as their role in therapeutic outcomes. This review identifies several relevant pharmacokinetic/pharmacodynamic models that incorporate key physical, biochemical, and physiological processes involved in delivery of oncology drugs by liposomal formulations. They capture observed data, lend insight into factors determining overall antitumor response, and in some cases, predict conditions for optimizing chemotherapy combinations that include nanoparticulate drug carriers. PMID:24647104
Effectiveness of a high-throughput genetic analysis in the identification of responders/non-responders to CYP2D6-metabolized drugs.

PubMed

Savino, Maria; Seripa, Davide; Gallo, Antonietta P; Garrubba, Maria; D'Onofrio, Grazia; Bizzarro, Alessandra; Paroni, Giulia; Paris, Francesco; Mecocci, Patrizia; Masullo, Carlo; Pilotto, Alberto; Santini, Stefano A

2011-01-01

Recent studies investigating the single cytochrome P450 (CYP) 2D6 allele *2A reported an association with the response to drug treatments. More genetic data can be obtained, however, by high-throughput based-technologies. Aim of this study is the high-throughput analysis of the CYP2D6 polymorphisms to evaluate its effectiveness in the identification of patient responders/non-responders to CYP2D6-metabolized drugs. An attempt to compare our results with those previously obtained with the standard analysis of CYP2D6 allele *2A was also made. Sixty blood samples from patients treated with CYP2D6-metabolized drugs previously genotyped for the allele CYP2D6*2A, were analyzed for the CYP2D6 polymorphisms with the AutoGenomics INFINITI CYP4502D6-I assay on the AutoGenomics INFINITI analyzer. A higher frequency of mutated alleles in responder than in non-responder patients (75.38 % vs 43.48 %; p = 0.015) was observed. Thus, the presence of a mutated allele of CYP2D6 was associated with a response to CYP2D6-metabolized drugs (OR = 4.044 (1.348 - 12.154). No difference was observed in the distribution of allele *2A (p = 0.320). The high-throughput genetic analysis of the CYP2D6 polymorphisms better discriminate responders/non-responders with respect to the standard analysis of the CYP2D6 allele *2A. A high-throughput genetic assay of the CYP2D6 may be useful to identify patients with different clinical responses to CYP2D6-metabolized drugs.
[Optimization of cluster analysis based on drug resistance profiles of MRSA isolates].

PubMed

Tani, Hiroya; Kishi, Takahiko; Gotoh, Minehiro; Yamagishi, Yuka; Mikamo, Hiroshige

2015-12-01

We examined 402 methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from clinical specimens in our hospital between November 19, 2010 and December 27, 2011 to evaluate the similarity between cluster analysis of drug susceptibility tests and pulsed-field gel electrophoresis (PFGE). The results showed that the 402 strains tested were classified into 27 PFGE patterns (151 subtypes of patterns). Cluster analyses of drug susceptibility tests with the cut-off distance yielding a similar classification capability showed favorable results--when the MIC method was used, and minimum inhibitory concentration (MIC) values were used directly in the method, the level of agreement with PFGE was 74.2% when 15 drugs were tested. The Unweighted Pair Group Method with Arithmetic mean (UPGMA) method was effective when the cut-off distance was 16. Using the SIR method in which susceptible (S), intermediate (I), and resistant (R) were coded as 0, 2, and 3, respectively, according to the Clinical and Laboratory Standards Institute (CLSI) criteria, the level of agreement with PFGE was 75.9% when the number of drugs tested was 17, the method used for clustering was the UPGMA, and the cut-off distance was 3.6. In addition, to assess the reproducibility of the results, 10 strains were randomly sampled from the overall test and subjected to cluster analysis. This was repeated 100 times under the same conditions. The results indicated good reproducibility of the results, with the level of agreement with PFGE showing a mean of 82.0%, standard deviation of 12.1%, and mode of 90.0% for the MIC method and a mean of 80.0%, standard deviation of 13.4%, and mode of 90.0% for the SIR method. In summary, cluster analysis for drug susceptibility tests is useful for the epidemiological analysis of MRSA.
A multichannel nanosensor for instantaneous readout of cancer drug mechanisms

NASA Astrophysics Data System (ADS)

Rana, Subinoy; Le, Ngoc D. B.; Mout, Rubul; Saha, Krishnendu; Tonga, Gulen Yesilbag; Bain, Robert E. S.; Miranda, Oscar R.; Rotello, Caren M.; Rotello, Vincent M.

2015-01-01

Screening methods that use traditional genomic, transcriptional, proteomic and metabonomic signatures to characterize drug mechanisms are known. However, they are time consuming and require specialized equipment. Here, we present a high-throughput multichannel sensor platform that can profile the mechanisms of various chemotherapeutic drugs in minutes. The sensor consists of a gold nanoparticle complexed with three different fluorescent proteins that can sense drug-induced physicochemical changes on cell surfaces. In the presence of cells, fluorescent proteins are rapidly displaced from the gold nanoparticle surface and fluorescence is restored. Fluorescence ‘turn on’ of the fluorescent proteins depends on the drug-induced cell surface changes, generating patterns that identify specific mechanisms of cell death induced by drugs. The nanosensor is generalizable to different cell types and does not require processing steps before analysis, offering an effective way to expedite research in drug discovery, toxicology and cell-based sensing.
How effective is drug abuse resistance education? A meta-analysis of Project DARE outcome evaluations.

PubMed Central

Ennett, S T; Tobler, N S; Ringwalt, C L; Flewelling, R L

1994-01-01

OBJECTIVES. Project DARE (Drug Abuse Resistance Education) is the most widely used school-based drug use prevention program in the United States, but the findings of rigorous evaluations of its effectiveness have not been considered collectively. METHODS. We used meta-analytic techniques to review eight methodologically rigorous DARE evaluations. Weighted effect size means for several short-term outcomes also were compared with means reported for other drug use prevention programs. RESULTS. The DARE effect size for drug use behavior ranged from .00 to .11 across the eight studies; the weighted mean for drug use across studies was .06. For all outcomes considered, the DARE effect size means were substantially smaller than those of programs emphasizing social and general competencies and using interactive teaching strategies. CONCLUSIONS. DARE's short-term effectiveness for reducing or preventing drug use behavior is small and is less than for interactive prevention programs. PMID:8092361
Nanocarriers for the Effective Treatment of Cervical Cancer: Research Advancements and Patent Analysis.

PubMed

Akhtar, Nida; Pathak, Kamla

2018-04-02

Cervical cancer being the cancer of cervix is caused by the aberrant cell growth that acquires an ability to spread/ invade to other body parts as well. It has been reported to be the second most commonest cause of death and cancer as well among women. Based on the severity of the disease, treatment aspect needs to be explored more in order to overcome the limitations acquired by conventional treatment. Recently, nanocarriers based drug delivery systems including liposomes, nanofibres, metallic NPs, polymeric NPs, dendrimers, polymeric micelles, antibody-drug conjugates etc. have been explored to target and treat cervical cancer. This review highlights numerous recent research and patent reports as well on nanocarriers based systems. Patents viz US, EP and WIPO have been retrieved using sites www.uspto.gov/patft and www.freepatentsonline.com to collect literature on nanocarriers. Various research reports and patents revealed nanocarriers to be effective in treating cervical cancer and these carriers are observed to be safer than the conventional treatment. Nanocarriers results in transforming drug distribution that can overpower drug resistance. Further, nanocarriers based drug delivery systems can particularly target drugs to cellular, subcellular and tissue sites. By enhancing the drug's bioavailability at the desired site, these systems result in therapeutic benefits like enhanced safety and efficacy. Also, in combination with other treatment approaches like radiation, photothermal and gene therapy, nanocarriers are reported to be quite effective and can define novel strategies to combat cervical cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Blood alcohol analysis alone versus comprehensive toxicological analysis - Systematic investigation of missed co-ingested other drugs in suspected alcohol-impaired drivers.

PubMed

Steuer, Andrea E; Eisenbeiss, Lisa; Kraemer, Thomas

2016-10-01

Driving under the influence of alcohol and/or drugs (DUID) is a safety issue of increasing public concern. When a police officer has reasonable grounds to classify a driver as impaired, he may arrange for a blood sample to be taken. In many countries, alcohol analysis only is ordered if impairment is suspected to be exclusively due to alcohol while comprehensive toxicological screening will be performed if additional suspicion for other illegal drugs of abuse (DoA) or medicinal drugs is on hand. The aim of the present study was firstly to evaluate whether signs of impairment can be differentiated to be caused by alcohol alone or a combination of alcohol and other driving-impairing drugs and secondly to which extent additional drugs are missed in suspected alcohol-impaired drivers. A total of 293 DUID cases (negative n=41; alcohol positive only, n=131; alcohol+active drug positive, n=121) analyzed in 2015 in the Canton of Zurich were evaluated for their documented impairment symptoms by translating these into a severity score and comparing them applying principle component analysis (PCA). Additional 500 cases suspected for alcohol-impaired driving only were reanalyzed using comprehensive LC-MS/MS screening methods covering about 1500 compounds. Drugs detected were classified for severity of driving impairment using the classification system established in the DRUID study of the European Commission. As partly expected from the pharmacological and toxicological point of view, PCA analysis revealed no differences between signs of impairment caused by alcohol alone and those caused by alcohol plus at least one active drug. Breaking it down to different blood alcohol concentration ranges, only between 0.3 and 0.5g/kg trends could be observed in terms of more severe impairment for combined alcohol and drug intake. In the 500 blood samples retrospectively analyzed in this study, a total of 330 additional drugs could be detected; in some cases up to 9 co-ingested ones. In total, 37% of all cases were positive for additional drugs, thereby 15% of classic DoAs and further 9% of prescription drugs with a severe risk to cause driving impairment based on the DRUID classification system. A decision whether signs of impairment are related to alcohol alone or to the combination of alcohol and other drugs is impossible. Taking into consideration the high rate of missed drugs in DUI cases, police should think about increasing the number of DUID cases in countries were sanctioning differs between alcohol and alcohol plus drug impaired driving. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Design, implementation, and first-year outcomes of a value-based drug formulary.

PubMed

Sullivan, Sean D; Yeung, Kai; Vogeler, Carol; Ramsey, Scott D; Wong, Edward; Murphy, Chad O; Danielson, Dan; Veenstra, David L; Garrison, Louis P; Burke, Wylie; Watkins, John B

2015-04-01

Value-based insurance design attempts to align drug copayment tier with value rather than cost. Previous implementations of value-based insurance design have lowered copayments for drugs indicated for select "high value" conditions and have found modest improvements in medication adherence. However, these implementations have generally not resulted in cost savings to the health plan, suggesting a need for increased copayments for "low value" drugs. Further, previous implementations have assigned equal copayment reductions to all drugs within a therapeutic area without assessing the value of individual drugs. Aligning the individual drug's copayment to its specific value may yield greater clinical and economic benefits. In 2010, Premera Blue Cross, a large not-for-profit health plan in the Pacific Northwest, implemented a value-based drug formulary (VBF) that explicitly uses cost-effectiveness analyses after safety and efficacy reviews to estimate the value of each individual drug. Concurrently, Premera increased copayments for existing tiers. To describe and evaluate the design, implementation, and first-year outcomes of the VBF. We compared observed pharmacy cost per member per month in the year following the VBF implementation with 2 comparator groups: (1) observed pharmacy costs in the year prior to implementation, and (2) expected costs if no changes were made to the pharmacy benefits. Expected costs were generated by applying autoregressive integrated moving averages to pharmacy costs over the previous 36 months. We used an interrupted time series analysis to assess drug use and adherence among individuals with diabetes, hypertension, or dyslipidemia compared with a group of members in plans that did not implement a VBF. Pharmacy costs decreased by 3% compared with the 12 months prior and 11% compared with expected costs. There was no significant decline in medication use or adherence to treatments for patients with diabetes, hypertension, or dyslipidemia. The VBF and copayment changes enabled pharmacy plan cost savings without negatively affecting utilization in key disease states.
Current trends in Finnish drug abuse: Wastewater based epidemiology combined with other national indicators.

PubMed

Kankaanpää, Aino; Ariniemi, Kari; Heinonen, Mari; Kuoppasalmi, Kimmo; Gunnar, Teemu

2016-10-15

No single measure is able to provide a complete picture of population- or community-level drug abuse and its current trends. Therefore, a multi-indicator approach is needed. The aim of this study was to combine wastewater-based epidemiology (WBE) with data from other national indicators, namely driving under the influence of drugs (DUID) statistics, drug seizures, and drug use surveys. Furthermore, drug market size estimates and a comparison of confiscated drugs to drugs actually consumed by users were performed using the WBE approach. Samples for wastewater analysis were collected during one-week sampling periods in 2012, 2014 and 2015, with a maximum of 14 cities participating. The samples were analysed with a validated ultra-high-performance liquid chromatography-mass spectrometric (UHPLC-MS/MS) methodology for various common drugs of abuse. The results were then compared with data from other national indicators available. Joint interpretation of the data shows that the use of amphetamine and MDMA has increased in Finland from 2012 to 2014. A similar trend was also observed for cocaine, although its use remains at a very low level compared to many other European countries. Heroin was practically absent from the Finnish drug market during the study period. The retail market for the most common stimulant drugs were estimated to have been worth EUR 70 million for amphetamine and around EUR 10 million for both methamphetamine and cocaine, in 2014 in Finland. Copyright © 2016 Elsevier B.V. All rights reserved.
Evaluation of rational drug use based on World Health Organization core drug use indicators in selected public hospitals of eastern Ethiopia: a cross sectional study.

PubMed

Sisay, Mekonnen; Mengistu, Getnet; Molla, Bereket; Amare, Firehiwot; Gabriel, Tesfaye

2017-02-23

Despite the complexity of drug use, a number of indicators have been developed, standardized and evaluated by the World Health Organization (WHO). These indicators are grouped in to three categories namely: prescribing indicators, patient care indicators and facility indicators. The study was aimed to evaluate rational drug use based on WHO-core drug use indicators in Dilchora referral hospital, Dire Dawa; Hiwot Fana specialized university hospital, Harar and Karamara general hospital, Jigjiga, eastern Ethiopia. Hospital based quantitative cross sectional study design was employed to evaluate rational drug use based on WHO core drug use indicators in selected hospitals. Systematic random sampling for prescribing indicators and convenient sampling for patient care indicators was employed. Taking WHO recommendations in to account, a total of 1,500 prescription papers (500 from each hospitals) were investigated. In each hospital, 200 outpatient attendants and 30 key essential drugs were also selected using the WHO recommendation. Data were collected using retrospective and prospective structured observational check list. Data were entered to EPI Data Version 3.1, exported and analyzed using SPSS version 16.0. Besides, the data were evaluated as per the WHO guidelines. Statistical significance was determined by one way analysis of variance (ANOVA) for some variables. P-value of less than 0.05 was considered statistically significant. Finally, tabular presentation was used to present the data. Mean, 2.34 (±1.08) drugs were prescribed in the selected hospitals. Prescriptions containing antibiotics and that of injectables were 57.87 and 10.9% respectively. The average consultation and dispensing time were 276.5 s and 61.12 s respectively. Besides, 75.77% of the prescribed drugs were actually dispensed. Only 3.3% of prescriptions were adequately labeled and 75.7% patients know about the dosage of the prescription. Not more than, 20(66.7%) key drugs were available in stock while only 19(63.3%) of key drugs had adequate labeling. On average, selected key drugs were out of stock for 30 days per year. All of the hospitals included in the study used the national drug list, formulary and standard treatment guidelines but none of them had their own drug list or guideline. Majority of WHO stated core drug use indicators were not met by the three hospitals included in the study.
Costs of providing infusion therapy for patients with inflammatory bowel disease in a hospital-based infusion center setting.

PubMed

Afzali, Anita; Ogden, Kristine; Friedman, Michael L; Chao, Jingdong; Wang, Anthony

2017-04-01

Inflammatory bowel disease (IBD) (e.g. ulcerative colitis [UC] and Crohn's disease [CD]) severely impacts patient quality-of-life. Moderate-to-severe disease is often treated with biologics requiring infusion therapy, adding incremental costs beyond drug costs. This study evaluates US hospital-based infusion services costs for treatment of UC or CD patients receiving infliximab or vedolizumab therapy. A model was developed, estimating annual costs of providing monitored infusions using an activity-based costing framework approach. Multiple sources (published literature, treatment product inserts) informed base-case model input estimates. The total modeled per patient infusion therapy costs in Year 1 with infliximab and vedolizumab was $38,782 and $41,320, respectively, and Year 2+, $49,897 and $36,197, respectively. Drug acquisition cost was the largest total costs driver (90-93%), followed by costs associated with hospital-based infusion provision: labor (53-56%, non-drug costs), allocated overhead (23%, non-drug costs), non-labor (23%, non-drug costs), and laboratory (7-10%, non-drug costs). Limitations included reliance on published estimates, base-case cost estimates infusion drug, and supplies, not accounting for volume pricing, assumption of a small hospital infusion center, and that, given the model adopts the hospital perspective, costs to the patient were not included in infusion administration cost base-case estimates. This model is an early step towards a framework to fully analyze infusion therapies' associated costs. Given the lack of published data, it would be beneficial for hospital administrators to assess total costs and trade-offs with alternative means of providing biologic therapies. This analysis highlights the value to hospital administrators of assessing cost associated with infusion patient mix to make more informed resource allocation decisions. As the landscape for reimbursement changes, tools for evaluating the costs of infusion therapy may help hospital administrators make informed choices and weigh trade-offs associated with providing infusion services for IBD patients.
A dose-dependent relationship between exposure to a street-based drug scene and health-related harms among people who use injection drugs.

PubMed

Debeck, Kora; Wood, Evan; Zhang, Ruth; Buxton, Jane; Montaner, Julio; Kerr, Thomas

2011-08-01

While the community impacts of drug-related street disorder have been well described, lesser attention has been given to the potential health and social implications of drug scene exposure on street-involved people who use illicit drugs. Therefore, we sought to assess the impacts of exposure to a street-based drug scene among injection drug users (IDU) in a Canadian setting. Data were derived from a prospective cohort study known as the Vancouver Injection Drug Users Study. Four categories of drug scene exposure were defined based on the numbers of hours spent on the street each day. Three generalized estimating equation (GEE) logistic regression models were constructed to identify factors associated with varying levels of drug scene exposure (2-6, 6-15, over 15 hours) during the period of December 2005 to March 2009. Among our sample of 1,486 IDU, at baseline, a total of 314 (21%) fit the criteria for high drug scene exposure (>15 hours per day). In multivariate GEE analysis, factors significantly and independently associated with high exposure included: unstable housing (adjusted odds ratio [AOR] = 9.50; 95% confidence interval [CI], 6.36-14.20); daily crack use (AOR = 2.70; 95% CI, 2.07-3.52); encounters with police (AOR = 2.11; 95% CI, 1.62-2.75); and being a victim of violence (AOR = 1.49; 95 % CI, 1.14-1.95). Regular employment (AOR = 0.50; 95% CI, 0.38-0.65), and engagement with addiction treatment (AOR = 0.58; 95% CI, 0.45-0.75) were negatively associated with high exposure. Our findings indicate that drug scene exposure is associated with markers of vulnerability and higher intensity addiction. Intensity of drug scene exposure was associated with indicators of vulnerability to harm in a dose-dependent fashion. These findings highlight opportunities for policy interventions to address exposure to street disorder in the areas of employment, housing, and addiction treatment.
Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)

PubMed Central

2013-01-01

Background The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ‘ad hoc’ gene expression data-sets. Results By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. PMID:24088245

Effect of intravenous drug administration mode on drug distribution in a tumor slab: a finite Fourier transform analysis.

PubMed

Subramaniam, B; Claudius, J S

1990-03-08

Cancer therapy using chemotherapeutic drugs frequently involves injection of the drug into the body through some intravenous mode of administration, viz, continuous (drip) infusion or single/multiple bolus injection(s). An understanding of the effect of the various modes of administration upon tumor penetration of drug is essential to rational design of drug therapy. This paper investigates drug penetration into a model tumor of slab geometry (between two capillaries) in which the overall transport rate of drug is limited by intra-tumor transport characterized by an effective diffusion coefficient. Employing the method of Finite Fourier Transforms (FFT), analytical solutions have been obtained for transient drug distribution in both the plasma and the tumor following three modes of administration, viz, continuous infusion, single bolus injection and equally-spaced equal-dose multiple bolus injections, of a given amount of drug. The qualitative trends exhibited by the plasma drug distribution profiles are consistent with reported experimental studies. Two concepts, viz, the dimensionless decay constant and the plasma/tumor drug concentration trajectories, are found to be particularly useful in the rational design of drug therapy. The dimensionless decay constant provides a measure of the rate of drug decay in the plasma relative to the rate of drug diffusion into the tumor and is thus characteristic of the tumor/drug system. The magnitude of this parameter dictates the choice of drug administration mode for minimizing drug decay in the plasma while simultaneously maximizing drug transport into the tumor. The concentration trajectories provide a measure of the plasma drug concentration relative to the tumor drug concentration at various times following injection. When the tumor drug concentration exceeds the plasma drug concentration, the drug will begin to diffuse out of the tumor. Knowledge of the time at which this diffusion reversal occurs is especially useful for optimum scheduling of subsequent bolus injections in a multiple bolus dosing regimen. There are no reported applications of the FFT method to solve repeated input functions in either the chemical engineering or pharmaceutical science literature. Thus, the application of FFT method to solve multiple bolus injections is a unique one. Use of this FFT based analysis as a predictor tool can limit the number of costly experiments which are being done now to achieve this purpose. Even though the model in its present form is simplified, the analysis thereof has nevertheless led to a better understanding of the various factors that must be taken into account for rational design of drug therapy.
Cross-Site Reliability of Human Induced Pluripotent Stem-Cell Derived Cardiomyocyte Based Safety Assays using Microelectrode Arrays: Results from a Blinded CiPA Pilot Study.

PubMed

Millard, Daniel; Dang, Qianyu; Shi, Hong; Zhang, Xiaou; Strock, Chris; Kraushaar, Udo; Zeng, Haoyu; Levesque, Paul; Lu, Hua-Rong; Guillon, Jean-Michel; Wu, Joseph C; Li, Yingxin; Luerman, Greg; Anson, Blake; Guo, Liang; Clements, Mike; Abassi, Yama A; Ross, James; Pierson, Jennifer; Gintant, Gary

2018-04-27

Recent in vitro cardiac safety studies demonstrate the ability of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) to detect electrophysiologic effects of drugs. However, variability contributed by unique approaches, procedures, cell lines and reagents across laboratories makes comparisons of results difficult, leading to uncertainty about the role of hiPSC-CMs in defining proarrhythmic risk in drug discovery and regulatory submissions. A blinded pilot study was conducted to evaluate the electrophysiologic effects of eight well-characterized drugs on four cardiomyocyte lines using a standardized protocol across three microelectrode array (MEA) platforms (18 individual studies). Drugs were selected to define assay sensitivity of prominent repolarizing currents (E-4031 for IKr, JNJ303 for IKs) and depolarizing currents (nifedipine for ICaL, mexiletine for INa) as well as drugs affecting multi-channel block (flecainide, moxifloxacin, quinidine, and ranolazine). Inclusion criteria for final analysis was based on demonstrated sensitivity to IKr block (20% prolongation with E-4031) and L-type calcium current block (20% shortening with nifedipine). Despite differences in baseline characteristics across cardiomyocyte lines, multiple sites and instrument platforms, 10 of 18 studies demonstrated adequate sensitivity to IKr block with E-4031 and ICaL block with nifedipine for inclusion in the final analysis. Concentration-dependent effects on repolarization were observed with this qualified dataset consistent with known ionic mechanisms of single and multi-channel blocking drugs. hiPSC-CMs can detect repolarization effects elicited by single and multi-channel blocking drugs after defining pharmacologic sensitivity to IKr and ICaL block, supporting further validation efforts using hiPSC-CMs for cardiac safety studies.
Elegant pH-Responsive Nanovehicle for Drug Delivery Based on Triazine Dendrimer Modified Magnetic Nanoparticles.

PubMed

Landarani-Isfahani, Amir; Moghadam, Majid; Mohammadi, Shima; Royvaran, Maryam; Moshtael-Arani, Naimeh; Rezaei, Saghar; Tangestaninejad, Shahram; Mirkhani, Valiollah; Mohammadpoor-Baltork, Iraj

2017-08-29

Owing to properties of magnetic nanoparticles and elegant three-dimensional macromolecule architectural features, dendrimeric structures have been investigated as nanoscale drug delivery systems. In this work, a novel magnetic nanocarrier, generation two (G2) triazine dendrimer modified Fe 3 O 4 @SiO 2 magnetic nanoparticles (MNP-G2), was designed, fabricated, and characterized by Fourier transform infrared (FT-IR), thermal gravimetric analysis (TGA), vibrating sample magnetometer (VSM), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and dynamic light scattering (DLS). The prepared MNP-G2 nanosystem offers a new formulation that combines the unique properties of MNPs and triazine dendrimer as a biocompatible material for biomedical applications. To demonstrate the potential of MNP-G2, the nanoparticles were loaded with methotrexate (MTX), a proven chemotherapy drug. The MTX-loaded MNP-G2 (MNP-G2/MTX) exhibited a high drug-loading capacity of MTX and the excellent ability for controlled drug release. The cytotoxicity of MNP-G2/MTX using an 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide based assay and MCF-7, HeLa, and Caov-4 cell lines revealed that MNP-G2/MTX was more active against the tumor cells than the free drug in a mildly acidic environment. The results of hemolysis, hemagglutination, and coagulation assays confirmed the good blood safety of MNP-G2/MTX. Moreover, the cell uptake and intracellular distribution of MNP-G2/MTX were studied by flow cytometry analysis and confocal laser scanning microscopy (CLSM). This research suggests that MNP-G2/MTX with good biocompatibility and degradability can be selected as an ideal and effective drug carrier in targeted biomedicine studies especially anticancer applications.
Variation in choice of study design: findings from the Epidemiology Design Decision Inventory and Evaluation (EDDIE) survey.

PubMed

Stang, Paul E; Ryan, Patrick B; Overhage, J Marc; Schuemie, Martijn J; Hartzema, Abraham G; Welebob, Emily

2013-10-01

Researchers using observational data to understand drug effects must make a number of analytic design choices that suit the characteristics of the data and the subject of the study. Review of the published literature suggests that there is a lack of consistency even when addressing the same research question in the same database. To characterize the degree of similarity or difference in the method and analysis choices made by observational database research experts when presented with research study scenarios. On-line survey using research scenarios on drug-effect studies to capture method selection and analysis choices that follow a dependency branching based on response to key questions. Voluntary participants experienced in epidemiological study design solicited for participation through registration on the Observational Medical Outcomes Partnership website, membership in particular professional organizations, or links in relevant newsletters. Description (proportion) of respondents selecting particular methods and making specific analysis choices based on individual drug-outcome scenario pairs. The number of questions/decisions differed based on stem questions of study design, time-at-risk, outcome definition, and comparator. There is little consistency across scenarios, by drug or by outcome of interest, in the decisions made for design and analyses in scenarios using large healthcare databases. The most consistent choice was the cohort study design but variability in the other critical decisions was common. There is great variation among epidemiologists in the design and analytical choices that they make when implementing analyses in observational healthcare databases. These findings confirm that it will be important to generate empiric evidence to inform these decisions and to promote a better understanding of the impact of standardization on research implementation.
Image-based compound profiling reveals a dual inhibitor of tyrosine kinase and microtubule polymerization.

PubMed

Tanabe, Kenji

2016-04-27

Small-molecule compounds are widely used as biological research tools and therapeutic drugs. Therefore, uncovering novel targets of these compounds should provide insights that are valuable in both basic and clinical studies. I developed a method for image-based compound profiling by quantitating the effects of compounds on signal transduction and vesicle trafficking of epidermal growth factor receptor (EGFR). Using six signal transduction molecules and two markers of vesicle trafficking, 570 image features were obtained and subjected to multivariate analysis. Fourteen compounds that affected EGFR or its pathways were classified into four clusters, based on their phenotypic features. Surprisingly, one EGFR inhibitor (CAS 879127-07-8) was classified into the same cluster as nocodazole, a microtubule depolymerizer. In fact, this compound directly depolymerized microtubules. These results indicate that CAS 879127-07-8 could be used as a chemical probe to investigate both the EGFR pathway and microtubule dynamics. The image-based multivariate analysis developed herein has potential as a powerful tool for discovering unexpected drug properties.
Microfluidic chip integrated with flexible PDMS-based electrochemical cytosensor for dynamic analysis of drug-induced apoptosis on HeLa cells.

PubMed

Cao, Jun-Tao; Zhu, Ying-Di; Rana, Rohit Kumar; Zhu, Jun-Jie

2014-01-15

A novel microfluidic platform integrated with a flexible PDMS-based electrochemical cytosensor was developed for real-time monitoring of the proliferation and apoptosis of HeLa cells. The PDMS-gold film, which had a conductive smooth surface and was semi-transparent, facilitated electrochemical measurements and optical microscope observations. We observed distinct increases and decreases in peak current intensity, corresponding to cell proliferation in culture medium and apoptosis in the presence of an anticancer drug, respectively. This electrochemical analysis method permitted real-time, label-free monitoring of cell behavior, and the electrochemical results were confirmed with optical microscopy. The flexible microfluidic electrochemical platform presented here is suitable for on-site monitoring of cell behavior in microenvironments. © 2013 Elsevier B.V. All rights reserved.
Synthesis and structural characterization of some trisulfide analoges of thiouracil-based antithyroid drugs

NASA Astrophysics Data System (ADS)

Bhabak, Krishna P.; Bhowmick, Debasish

2012-08-01

Thiourea-based antithyroid drugs are effectively used for the treatment of hyperthyroidism. In this paper, we describe the synthesis of new trisulfides (11-12) from the commonly used thiourea-based antithyroid drugs such as 6-n-propyl-2-thiouracil (PTU) and 6-methyl-2-thiouracil (MTU) in the reaction with I2/KI system. Structural analysis by single crystal X-ray diffraction studies revealed the stabilization of trisulfides by a lactam-lactim tautomerism facilitating effective intramolecular as well as intermolecular non-covalent interactions. Although the structures of both trisulfides were found to be quite similar, a notable difference in the intermolecular interactions was observed between compounds 11 and 12 leading to different structural patterns. Structural stabilization of these trisulfides by tautomerism followed by intramolecular as well as intermolecular H-bonds makes these molecules as perfect examples in molecular recognition with self-complementary donor and acceptor units within a single molecule.
Quantitative Analysis of Complex Drug-Drug Interactions Between Repaglinide and Cyclosporin A/Gemfibrozil Using Physiologically Based Pharmacokinetic Models With In Vitro Transporter/Enzyme Inhibition Data.

PubMed

Kim, Soo-Jin; Toshimoto, Kota; Yao, Yoshiaki; Yoshikado, Takashi; Sugiyama, Yuichi

2017-09-01

Quantitative analysis of transporter- and enzyme-mediated complex drug-drug interactions (DDIs) is challenging. Repaglinide (RPG) is transported into the liver by OATP1B1 and then is metabolized by CYP2C8 and CYP3A4. The purpose of this study was to describe the complex DDIs of RPG quantitatively based on unified physiologically based pharmacokinetic (PBPK) models using in vitro K i values for OATP1B1, CYP3A4, and CYP2C8. Cyclosporin A (CsA) or gemfibrozil (GEM) increased the blood concentrations of RPG. The time profiles of RPG and the inhibitors were analyzed by PBPK models, considering the inhibition of OATP1B1 and CYP3A4 by CsA or OATP1B1 inhibition by GEM and its glucuronide and the mechanism-based inhibition of CYP2C8 by GEM glucuronide. RPG-CsA interaction was closely predicted using a reported in vitro K i,OATP1B1 value in the presence of CsA preincubation. RPG-GEM interaction was underestimated compared with observed data, but the simulation was improved with the increase of f m,CYP2C8 . These results based on in vitro K i values for transport and metabolism suggest the possibility of a bottom-up approach with in vitro inhibition data for the prediction of complex DDIs using unified PBPK models and in vitro f m value of a substrate for multiple enzymes should be considered carefully for the prediction. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Microsponges based novel drug delivery system for augmented arthritis therapy

PubMed Central

Osmani, Riyaz Ali M.; Aloorkar, Nagesh H.; Ingale, Dipti J.; Kulkarni, Parthasarathi K.; Hani, Umme; Bhosale, Rohit R.; Jayachandra Dev, Dandasi

2015-01-01

The motive behind present work was to formulate and evaluate gel containing microsponges of diclofenac diethylamine to provide prolonged release for proficient arthritis therapy. Quasi-emulsion solvent diffusion method was implied using Eudragit RS-100 and microsponges with varied drug–polymer ratios were prepared. For the sake of optimization, diverse factors affecting microparticles physical properties were too investigated. Microsponges were characterized by SEM, DSC, FT-IR, XRPD and particle size analysis, and evaluated for morphology, drug loading, in vitro drug release and ex vivo diffusion as well. There were no chemical interactions between drug and polymers used as revealed by compatibility studies outcomes. The drug polymer ratio reflected notable effect on drug content, encapsulation efficiency and particle size. SEM results revealed spherical microsponges with porous surface, and had 7.21 μm mean particle size. The microsponges were then incorporated in gel; which exhibited viscous modulus along with pseudoplastic behavior. In vitro drug release results depicted that microsponges with 1:2 drug–polymer ratio were more efficient to give extended drug release of 75.88% at the end of 8 h; while conventional formulation get exhausted incredibly earlier by releasing 81.11% drug at the end of 4 h only. Thus the formulated microsponge-based gel of diclofenac diethylamine would be a promising alternative to conventional therapy for safer and efficient treatment of arthritis and musculoskeletal disorders. PMID:26594124
Distinguishing characteristics of patients who seek more information or request a prescription in response to direct-to-consumer advertisements.

PubMed

Schommer, Jon C; Singh, Reshmi L; Hansen, Richard A

2005-06-01

The objective of this study was to examine demographic and psychographic profiles of individuals who sought additional information or requested a prescription drug based on a direct-to-consumer advertisement. A cross-sectional descriptive survey was used for collecting data from a random sample of 200 Minnesotans during Fall 2002. Chi-square and Mann-Whitney U tests were used as nonparametric tests for assessing differences in distributions between our categories of study subjects. Out of 177 deliverable surveys, 81 (46%) were returned. Of these, 80 surveys were usable for analysis. The results showed that the distinguishing characteristics of individuals who sought additional information based on an advertisement were associated with demographic variables such as number of drugs taken daily and monthly out-of-pocket expenditures for prescription drugs. In contrast, distinguishing characteristics of individuals who requested prescription drugs (in addition to seeking information) based on an advertisement were psychographic in nature such as (1) viewing themselves as having greater influence on their physician, (2) having a stronger relationship with their physician, (3) expressing greater satisfaction with their current therapy, (4) viewing prescriptions as less of a burden, and (5) having higher outcome expectations for prescription drugs compared to the respondents who did not ask for a prescription drug based on a direct-to-consumer advertisement. Distinguishing characteristics of information seekers were demographic in nature, whereas those characteristics of prescription requesters were psychographic in nature.
[Uniform analyzes of drugs in urine needed for rule of law].

PubMed

Hansson, Therese; Helander, Anders; Beck, Olof; Elmgren, Anders; Kugelberg, Fredrik; Kronstrand, Robert

2015-09-22

Drugs of abuse testing is used in various areas of society for detection and follow-up of drug use. In routine laboratory drug testing, immunoassays are employed for initial screening of specimens to indicate the presence of drugs. To confirm a positive screening test, a secondary analysis by mass spectrometry is performed. The "cut-off" is the pre-defined concentration threshold of a drug or drug metabolite above which the sample is considered positive. A reading below this level implies a negative test result. Swedish drug testing laboratories currently employ varying cut-offs to distinguish between a positive and a negative test result. Because a positive drug test may have serious legal consequences to the individual, it is of importance that testing is performed and judged equally, regardless of where it is performed. A national harmonization of cut-offs is therefore warranted. Based on data from four major Swedish drug testing laboratories, and considering the recommendations in international guidelines, a proposal for national harmonization of urine cut-offs for the most common set of drugs of abuse is presented.
Motivations for Non-Medical Prescription Drug Use: A Mixed Methods Analysis

PubMed Central

Rigg, Khary K.; Ibañez, Gladys E.

2010-01-01

Despite a dramatic increase in the non-medical use of prescription drugs among illicit drug users, their motives for abusing prescription drugs are still largely unknown. The objective of this study was to 1) determine the motivations for engaging in the non-medical use of prescription opioids and sedatives among street-based illicit drug users, methadone maintenance patients, and residential drug treatment clients, 2) examine associations between prescription drug abuse motivations and gender, age, race/ethnicity, and user group, and 3) examine associations between specific motivations and prescription drug abuse patterns. Quantitative surveys (n = 684) and in-depth interviews (n = 45) were conducted with a diverse sample of prescription drug abusers in South Florida between March 2008 and November 2009. The three most common motivations reported were “to get high”, “to sleep”, and “for anxiety/stress”. There were age, race/ethnicity, and gender differences by motives. Prescription drug abuse patterns were also found to be associated with specific motivations. While additional research is needed, these findings serve to inform appropriate prevention and treatment initiatives for prescription drug abusers. PMID:20667680
Use of Natural Products as Chemical Library for Drug Discovery and Network Pharmacology

PubMed Central

Gu, Jiangyong; Gui, Yuanshen; Chen, Lirong; Yuan, Gu; Lu, Hui-Zhe; Xu, Xiaojie

2013-01-01

Background Natural products have been an important source of lead compounds for drug discovery. How to find and evaluate bioactive natural products is critical to the achievement of drug/lead discovery from natural products. Methodology We collected 19,7201 natural products structures, reported biological activities and virtual screening results. Principal component analysis was employed to explore the chemical space, and we found that there was a large portion of overlap between natural products and FDA-approved drugs in the chemical space, which indicated that natural products had large quantity of potential lead compounds. We also explored the network properties of natural product-target networks and found that polypharmacology was greatly enriched to those compounds with large degree and high betweenness centrality. In order to make up for a lack of experimental data, high throughput virtual screening was employed. All natural products were docked to 332 target proteins of FDA-approved drugs. The most potential natural products for drug discovery and their indications were predicted based on a docking score-weighted prediction model. Conclusions Analysis of molecular descriptors, distribution in chemical space and biological activities of natural products was conducted in this article. Natural products have vast chemical diversity, good drug-like properties and can interact with multiple cellular target proteins. PMID:23638153
Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis

PubMed Central

Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul

2011-01-01

Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238
Are drug-coated balloons cost effective for femoropopliteal occlusive disease? A comparison of bare metal stents and uncoated balloons.

PubMed

Poder, Thomas G; Fisette, Jean-François

2016-07-01

To perform a cost-effectiveness analysis to help hospital decision-makers with regard to the use of drug-coated balloons compared with bare metal stents and uncoated balloons for femoropopliteal occlusive disease. Clinical outcomes were extracted from the results of meta-analyses already published, and cost units are those used in the Quebec healthcare network. The literature review was limited to the last four years to obtain the most recent data. The cost-effectiveness analysis was based on a 2-year perspective, and risk factors of reintervention were considered. The cost-effectiveness analysis indicated that drug-coated balloons were generally more efficient than bare metal stents, particularly for patients with higher risk of reintervention (up to CAD$1686 per patient TASC II C or D). Compared with uncoated balloons, results indicated that drug-coated balloons were more efficient if the reintervention rate associated with uncoated balloons is very high and for patients with higher risk of reintervention (up to CAD$3301 per patient). The higher a patient's risk of reintervention, the higher the savings associated with the use of a drug-coated balloon will be. For patients at lower risk, the uncoated balloon strategy is still recommended as a first choice for endovascular intervention.
Adverse and Advantageous Selection in the Medicare Supplemental Market: A Bayesian Analysis of Prescription drug Expenditure.

PubMed

Li, Qian; Trivedi, Pravin K

2016-02-01

This paper develops an extended specification of the two-part model, which controls for unobservable self-selection and heterogeneity of health insurance, and analyzes the impact of Medicare supplemental plans on the prescription drug expenditure of the elderly, using a linked data set based on the Medicare Current Beneficiary Survey data for 2003-2004. The econometric analysis is conducted using a Bayesian econometric framework. We estimate the treatment effects for different counterfactuals and find significant evidence of endogeneity in plan choice and the presence of both adverse and advantageous selections in the supplemental insurance market. The average incentive effect is estimated to be $757 (2004 value) or 41% increase per person per year for the elderly enrolled in supplemental plans with drug coverage against the Medicare fee-for-service counterfactual and is $350 or 21% against the supplemental plans without drug coverage counterfactual. The incentive effect varies by different sources of drug coverage: highest for employer-sponsored insurance plans, followed by Medigap and managed medicare plans. Copyright © 2014 John Wiley & Sons, Ltd.
Effectiveness of multi-drug regimen chemotherapy treatment in osteosarcoma patients: a network meta-analysis of randomized controlled trials.

PubMed

Wang, Xiaojie; Zheng, Hong; Shou, Tao; Tang, Chunming; Miao, Kun; Wang, Ping

2017-03-29

Osteosarcoma is the most common malignant bone tumour. Due to the high metastasis rate and drug resistance of this disease, multi-drug regimens are necessary to control tumour cells at various stages of the cell cycle, eliminate local or distant micrometastases, and reduce the emergence of drug-resistant cells. Many adjuvant chemotherapy protocols have shown different efficacies and controversial results. Therefore, we classified the types of drugs used for adjuvant chemotherapy and evaluated the differences between single- and multi-drug chemotherapy regimens using network meta-analysis. We searched electronic databases, including PubMed (MEDLINE), EmBase, and the Cochrane Library, through November 2016 using the keywords "osteosarcoma", "osteogenic sarcoma", "chemotherapy", and "random*" without language restrictions. The major outcome in the present analysis was progression-free survival (PFS), and the secondary outcome was overall survival (OS). We used a random effect network meta-analysis for mixed multiple treatment comparisons. We included 23 articles assessing a total of 5742 patients in the present systematic review. The analysis of PFS indicated that the T12 protocol (including adriamycin, bleomycin, cyclophosphamide, dactinomycin, methotrexate, cisplatin) plays a more critical role in osteosarcoma treatment (surface under the cumulative ranking (SUCRA) probability 76.9%), with a better effect on prolonging the PFS of patients when combined with ifosfamide (94.1%) or vincristine (81.9%). For the analysis of OS, we separated the regimens to two groups, reflecting the disconnection. The T12 protocol plus vincristine (94.7%) or the removal of cisplatinum (89.4%) is most likely the best regimen. We concluded that multi-drug regimens have a better effect on prolonging the PFS and OS of osteosarcoma patients, and the T12 protocol has a better effect on prolonging the PFS of osteosarcoma patients, particularly in combination with ifosfamide or vincristine. The OS analysis showed that the T12 protocol plus vincristine or the T12 protocol with the removal of cisplatinum might be a better regimen for improving the OS of patients. However, well-designed randomized controlled trials of chemotherapeutic protocols are still necessary.
Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: placing back-calculations in a formal statistical framework.

PubMed

Jones, Hayley E; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J; Baker, David R; Ades, A E

2014-07-15

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these 'back-calculations', the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. Copyright © 2014. Published by Elsevier B.V.
Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: Placing back-calculations in a formal statistical framework

PubMed Central

Jones, Hayley E.; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J.; Baker, David R.; Ades, A.E.

2014-01-01

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these ‘back-calculations’, the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. PMID:24636801
INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.

PubMed

Verkhivker, Gennady M

2016-01-01

The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling complex relationships between robustness of targeted kinase genes and binding specificity of targeted kinase drugs. We discuss how these approaches can exploit advances in chemical biology and network science to develop novel strategies for rationally tailored and robust personalized drug therapies.

Designed Synthesis of Nanostructured Magnetic Hydroxyapatite Based Drug Nanocarrier for Anti-Cancer Drug Delivery toward the Treatment of Human Epidermoid Carcinoma

PubMed Central

Govindan, Bharath; Swarna Latha, Beeseti; Nagamony, Ponpandian; Ahmed, Faheem; Saifi, Muheet Alam; Harrath, Abdel Halim; Alwasel, Saleh; Mansour, Lamjed; Alsharaeh, Edreese H.

2017-01-01

Superparamagnetic Fe3O4 nanoparticles on hydroxyapatite nanorod based nanostructures (Fe3O4/HAp) were synthesized using hydrothermal techniques at 180 °C for 12 h and were used as drug delivery nanocarriers for cancer cell therapeutic applications. The synthesized Fe3O4/HAp nanocomposites were characterized by X-ray diffraction analysis (XRD), Field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET)-analysis, and vibrating sample magnetometry (VSM). The morphologies of the Fe3O4/HAp nanocomposites show 15 nm Fe3O4 nanoparticles dispersed in the form of rods. The BET result shows that the synthesized samples have a high specific surface area of 80 m2 g−1 with mesoporous structures. Magnetic measurements revealed that the sample has high saturation magnetization of 18 emu/g with low coercivity. The Fe3O4/HAp nanocomposites had a large specific surface area (SSA), high mesoporous volume, and good magnetic property, which made it a suitable nanocarrier for targeted drug delivery systems. The chemotherapeutic agent, andrographolide, was used to investigate the drug delivery behavior of the Fe3O4/HAp nanocomposites. The human epidermoid skin cancer cells (A431) were used as the model targeting cell lines by treating with andrographolide loaded Fe3O4/HAp nanosystems and were further evaluated for their antiproliferative activities and the induction of apoptosis. Also, the present nanocomposite shows better biocompatibility, therefore it can be used as suitable drug vehicle for cancer therapy applications. PMID:28587317
[New drugs in oncology--features of clinical trials for market authorisation and arguments for the rapid implementation of independent clinical trials following approval].

PubMed

Ludwig, Wolf-Dieter; Schott, Gisela

2013-01-01

The market authorisation or extension of indication for all oncology drugs in Europe is now based on Regulation (EC) No. 726/2004, a centralised procedure of the European Medicines Agency (EMA). Studies in recent years have highlighted deficiencies in pivotal studies. For example, the requirements of the EMA are not always consistently followed and studies are stopped prematurely after only interim analysis that at this time point shows improved efficacy with regard to the comparator arm. Our current analysis of the European Assessment Reports (reporting period: 01/01/2009 to 08/13/2012) on 29 drugs for 39 oncology indications shows that the quality of the trials for market authorisation has improved in several respects. Primary endpoints recommended by the EMA and the Food and Drug Administration (FDA) such as overall survival and progression-free survival are used, and only one study was conducted as a phase II trial with no comparator arm. In contrast, oncology drugs that are approved for the treatment of rare diseases (orphan drugs) are based on small studies which are often carried out without blinding, are not randomised and investigate surrogate endpoints. To answer patient-relevant issues following market authorisation, it is necessary to conduct independent clinical studies. Increased public funding needs to be provided and bureaucratic hurdles have to be reduced. Only this will permit a more efficient use of limited health care resources and allow to improve the quality of care for cancer patients. Copyright © 2013 S. Karger AG, Basel.
Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.

PubMed

Potemkin, Andrey V; Grishina, Maria A; Potemkin, Vladimir A

2017-01-01

In 1979, R.D.Cramer and M.Milne made a first realization of 3D comparison of molecules by aligning them in space and by mapping their molecular fields to a 3D grid. Further, this approach was developed as the DYLOMMS (Dynamic Lattice- Oriented Molecular Modelling System) approach. In 1984, H.Wold and S.Wold proposed the use of partial least squares (PLS) analysis, instead of principal component analysis, to correlate the field values with biological activities. Then, in 1988, the method which was called CoMFA (Comparative Molecular Field Analysis) was introduced and the appropriate software became commercially available. Since 1988, a lot of 3D QSAR methods, algorithms and their modifications are introduced for solving of virtual drug discovery problems (e.g., CoMSIA, CoMMA, HINT, HASL, GOLPE, GRID, PARM, Raptor, BiS, CiS, ConGO,). All the methods can be divided into two groups (classes):1. Methods studying the exterior of molecules; 2) Methods studying the interior of molecules. A series of grid-based computational technologies for Continual Molecular Interior analysis (CoMIn) are invented in the current paper. The grid-based analysis is fulfilled by means of a lattice construction analogously to many other grid-based methods. The further continual elucidation of molecular structure is performed in various ways. (i) In terms of intermolecular interactions potentials. This can be represented as a superposition of Coulomb, Van der Waals interactions and hydrogen bonds. All the potentials are well known continual functions and their values can be determined in all lattice points for a molecule. (ii) In the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum free-orbital approach AlteQ is proposed. All the functions can be calculated using a quantum approach at a sufficient level of theory and their values can be determined in all lattice points for a molecule. Then, the molecules of a dataset can be superimposed in the lattice for the maximal coincidence (or minimal deviations) of the potentials (i) or the quantum functions (ii). The methods and criteria of the superimposition are discussed. After that a functional relationship between biological activity or property and characteristics of potentials (i) or functions (ii) is created. The methods of the quantitative relationship construction are discussed. New approaches for rational virtual drug design based on the intermolecular potentials and quantum functions are invented. All the invented methods are realized at www.chemosophia.com web page. Therefore, a set of 3D QSAR approaches for continual molecular interior study giving a lot of opportunities for virtual drug discovery, virtual screening and ligand-based drug design are invented. The continual elucidation of molecular structure is performed in the terms of intermolecular interactions potentials and in the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum free-orbital approach AlteQ is proposed. The methods of the quantitative relationship construction are discussed. New approaches for rational virtual drug design based on the intermolecular potentials and quantum functions are invented. All the invented methods are realized at www.chemosophia.com web page. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Predicting Drug-Target Interactions With Multi-Information Fusion.

PubMed

Peng, Lihong; Liao, Bo; Zhu, Wen; Li, Zejun; Li, Keqin

2017-03-01

Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most models only consider chemical structures and protein sequences, and other models are oversimplified. Moreover, datasets used for analysis contain only true-positive interactions, and experimentally validated negative samples are unavailable. To overcome these limitations, we developed a semi-supervised based learning framework called NormMulInf through collaborative filtering theory by using labeled and unlabeled interaction information. The proposed method initially determines similarity measures, such as similarities among samples and local correlations among the labels of the samples, by integrating biological information. The similarity information is then integrated into a robust principal component analysis model, which is solved using augmented Lagrange multipliers. Experimental results on four classes of drug-target interaction networks suggest that the proposed approach can accurately classify and predict drug-target interactions. Part of the predicted interactions are reported in public databases. The proposed method can also predict possible targets for new drugs and can be used to determine whether atropine may interact with alpha1B- and beta1- adrenergic receptors. Furthermore, the developed technique identifies potential drugs for new targets and can be used to assess whether olanzapine and propiomazine may target 5HT2B. Finally, the proposed method can potentially address limitations on studies of multitarget drugs and multidrug targets.
Mapping of Drug-like Chemical Universe with Reduced Complexity Molecular Frameworks.

PubMed

Kontijevskis, Aleksejs

2017-04-24

The emergence of the DNA-encoded chemical libraries (DEL) field in the past decade has attracted the attention of the pharmaceutical industry as a powerful mechanism for the discovery of novel drug-like hits for various biological targets. Nuevolution Chemetics technology enables DNA-encoded synthesis of billions of chemically diverse drug-like small molecule compounds, and the efficient screening and optimization of these, facilitating effective identification of drug candidates at an unprecedented speed and scale. Although many approaches have been developed by the cheminformatics community for the analysis and visualization of drug-like chemical space, most of them are restricted to the analysis of a maximum of a few millions of compounds and cannot handle collections of 10 8 -10 12 compounds typical for DELs. To address this big chemical data challenge, we developed the Reduced Complexity Molecular Frameworks (RCMF) methodology as an abstract and very general way of representing chemical structures. By further introducing RCMF descriptors, we constructed a global framework map of drug-like chemical space and demonstrated how chemical space occupied by multi-million-member drug-like Chemetics DNA-encoded libraries and virtual combinatorial libraries with >10 12 members could be analyzed and mapped without a need for library enumeration. We further validate the approach by performing RCMF-based searches in a drug-like chemical universe and mapping Chemetics library selection outputs for LSD1 targets on a global framework chemical space map.
Prediction of phospholipidosis-inducing potential of drugs by in vitro biochemical and physicochemical assays followed by multivariate analysis.

PubMed

Kuroda, Yukihiro; Saito, Madoka

2010-03-01

An in vitro method to predict phospholipidosis-inducing potential of cationic amphiphilic drugs (CADs) was developed using biochemical and physicochemical assays. The following parameters were applied to principal component analysis, as well as physicochemical parameters: pK(a) and clogP; dissociation constant of CADs from phospholipid, inhibition of enzymatic phospholipid degradation, and metabolic stability of CADs. In the score plot, phospholipidosis-inducing drugs (amiodarone, propranolol, imipramine, chloroquine) were plotted locally forming the subspace for positive CADs; while non-inducing drugs (chlorpromazine, chloramphenicol, disopyramide, lidocaine) were placed scattering out of the subspace, allowing a clear discrimination between both classes of CADs. CADs that often produce false results by conventional physicochemical or cell-based assay methods were accurately determined by our method. Basic and lipophilic disopyramide could be accurately predicted as a nonphospholipidogenic drug. Moreover, chlorpromazine, which is often falsely predicted as a phospholipidosis-inducing drug by in vitro methods, could be accurately determined. Because this method uses the pharmacokinetic parameters pK(a), clogP, and metabolic stability, which are usually obtained in the early stages of drug development, the method newly requires only the two parameters, binding to phospholipid, and inhibition of lipid degradation enzyme. Therefore, this method provides a cost-effective approach to predict phospholipidosis-inducing potential of a drug. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
Antibiotic combination efficacy (ACE) networks for a Pseudomonas aeruginosa model

PubMed Central

Barbosa, Camilo; Beardmore, Robert; Jansen, Gunther

2018-01-01

The spread of antibiotic resistance is always a consequence of evolutionary processes. The consideration of evolution is thus key to the development of sustainable therapy. Two main factors were recently proposed to enhance long-term effectiveness of drug combinations: evolved collateral sensitivities between the drugs in a pair and antagonistic drug interactions. We systematically assessed these factors by performing over 1,600 evolution experiments with the opportunistic nosocomial pathogen Pseudomonas aeruginosa in single- and multidrug environments. Based on the growth dynamics during these experiments, we reconstructed antibiotic combination efficacy (ACE) networks as a new tool for characterizing the ability of the tested drug combinations to constrain bacterial survival as well as drug resistance evolution across time. Subsequent statistical analysis of the influence of the factors on ACE network characteristics revealed that (i) synergistic drug interactions increased the likelihood of bacterial population extinction—irrespective of whether combinations were compared at the same level of inhibition or not—while (ii) the potential for evolved collateral sensitivities between 2 drugs accounted for a reduction in bacterial adaptation rates. In sum, our systematic experimental analysis allowed us to pinpoint 2 complementary determinants of combination efficacy and to identify specific drug pairs with high ACE scores. Our findings can guide attempts to further improve the sustainability of antibiotic therapy by simultaneously reducing pathogen load and resistance evolution. PMID:29708964
Effect of sampling and diagnostic effort on the assessment of schistosomiasis and soil-transmitted helminthiasis and drug efficacy: a meta-analysis of six drug efficacy trials and one epidemiological survey.

PubMed

Levecke, Bruno; Brooker, Simon J; Knopp, Stefanie; Steinmann, Peter; Sousa-Figueiredo, Jose Carlos; Stothard, J Russell; Utzinger, Jürg; Vercruysse, Jozef

2014-12-01

It is generally recommended to perform multiple stool examinations in order to improve the diagnostic accuracy when assessing the impact of mass drug administration programmes to control human intestinal worm infections and determining efficacy of the drugs administered. However, the collection and diagnostic work-up of multiple stool samples increases costs and workload. It has been hypothesized that these increased efforts provide more accurate results when infection and drug efficacy are summarized by prevalence (proportion of subjects infected) and cure rate (CR, proportion of infected subjects that become egg-negative after drug administration), respectively, but not when these indicators are expressed in terms of infection intensity and egg reduction rate (ERR). We performed a meta-analysis of six drug efficacy trials and one epidemiological survey. We compared prevalence and intensity of infection, CR and ERR based on collection of one or two stool samples that were processed with single or duplicate Kato-Katz thick smears. We found that the accuracy of prevalence estimates and CR was lowest with the minimal sampling effort, but that this was not the case for estimating infection intensity and ERR. Hence, a single Kato-Katz thick smear is sufficient for reporting infection intensity and ERR following drug treatment.
Design and evaluation of effervescent floating tablets based on hydroxyethyl cellulose and sodium alginate using pentoxifylline as a model drug

PubMed Central

Rahim, Safwan Abdel; Carter, Paul A; Elkordy, Amal Ali

2015-01-01

The aim of this work was to design and evaluate effervescent floating gastro-retentive drug delivery matrix tablets with sustained-release behavior using a binary mixture of hydroxyethyl cellulose and sodium alginate. Pentoxifylline was used as a highly water-soluble, short half-life model drug with a high density. The floating capacity, swelling, and drug release behaviors of drug-loaded matrix tablets were evaluated in 0.1 N HCl (pH 1.2) at 37°C±0.5°C. Release data were analyzed by fitting the power law model of Korsmeyer–Peppas. The effect of different formulation variables was investigated, such as wet granulation, sodium bicarbonate gas-forming agent level, and tablet hardness properties. Statistical analysis was applied by paired sample t-test and one-way analysis of variance depending on the type of data to determine significant effect of different parameters. All prepared tablets through wet granulation showed acceptable physicochemical properties and their drug release profiles followed non-Fickian diffusion. They could float on the surface of dissolution medium and sustain drug release over 24 hours. Tablets prepared with 20% w/w sodium bicarbonate at 50–54 N hardness were promising with respect to their floating lag time, floating duration, swelling ability, and sustained drug release profile. PMID:25848220
Drug-class-specific changes in the volume and cost of antidiabetic medications in Poland between 2012 and 2015.

PubMed

Śliwczyński, Andrzej; Brzozowska, Melania; Jacyna, Andrzej; Iltchev, Petre; Iwańczuk, Tymoteusz; Wierzba, Waldemar; Marczak, Michał; Orlewska, Katarzyna; Szymański, Piotr; Orlewska, Ewa

2017-01-01

to investigate the drug-class-specific changes in the volume and cost of antidiabetic medications in Poland in 2012-2015. This retrospective analysis was conducted based on the National Health Fund database covering an entire Polish population. The volume of antidiabetic medications is reported according to ATC/DDD methodology, costs-in current international dollars, based on purchasing power parity. During a 4-year observational period the number of patients, consumption of antidiabetic drugs and costs increased by 17%, 21% and 20%, respectively. Biguanides are the basic diabetes medication with a 39% market share. The insulin market is still dominated by human insulins, new antidiabetics (incretins, thiazolidinediones) are practically absent. Insulins had the largest share in diabetes medications expenditures (67% in 2015). The increase in antidiabetic medications costs over the analysed period of time was mainly caused by the increased use of insulin analogues. The observed tendencies correspond to the evidence-based HTA recommendations. The reimbursement status, the ratio of cost to clinical outcomes and data on the long-term safety have a deciding impact on how a drug is used.
Market uptake of biologic and small-molecule--targeted oncology drugs in Europe.

PubMed

Obradovic, Marko; Mrhar, Ales; Kos, Mitja

2009-12-01

The aim of this study was to investigate the market uptake of biologic and small-molecule-targeted oncology drugs in Europe. Targeted oncology drugs that were used in one of the selected European countries before the end of 2007 were eligible for inclusion in the analysis. The following European countries were included: Austria, Croatia, France, Germany, Hungary, Italy, Slovenia, and the United Kingdom. Monetary market uptake of targeted oncology drugs was assessed by using sales data (in euros) obtained from 2 large data- bases for the period 1997-2007. Market uptake was assessed in terms of expenditures for specific drugs in euros per capita and in market shares. The monetary market uptake of targeted oncology drugs had an exponential growth from 1997 to 2007 in all comparison countries and reached 40% of the total oncology drug market in 2007. Although the various European countries allocate substantially different amounts of resources per capita for oncology drugs, the share of expenditures attributed to targeted oncology drugs did not differ substantially among the countries. Biologic molecules were used in clinical practice before the small-molecule-targeted oncology drugs. Targeted oncology drugs that were introduced first to clinical practice in most of the comparison countries (ie, rituximab, trastuzumab, imatinib mesylate) maintained the leading positions on the market throughout the period of the analysis. In 2007, approximately 25% of all expenditures for oncology drugs were attributed to biologic oncology drugs, and approximately 15% were spent on small-molecule-targeted oncology drugs. Expenditures on targeted oncology drugs have been increasing exponentially in Europe throughout the past decade and have reached a 40% share of the oncology drug market. As of 2007, the market share of biologic oncology drugs was higher than the market share of small-molecule-targeted oncology drugs. Copyright 2009 Excerpta Medica Inc. All rights reserved.
Conditioned taste aversion, drugs of abuse and palatability

PubMed Central

Lin, Jian-You; Arthurs, Joe; Reilly, Steve

2014-01-01

LIN, J.-Y., J. Arthurs and S. Reilly. Conditioned taste aversion: Palatability and drugs of abuse. NEUROSCI BIOBEHAV REV XX(x) XXX-XXX, 2014. – We consider conditioned taste aversion to involve a learned reduction in the palatability of a taste (and hence in amount consumed) based on the association that develops when a taste experience is followed by gastrointestinal malaise. The present article evaluates the well-established finding that drugs of abuse, at doses that are otherwise considered rewarding and self-administered, cause intake suppression. Our recent work using lick pattern analysis shows that drugs of abuse also cause a palatability downshift and, therefore, support conditioned taste aversion learning. PMID:24813806
Parental perceptions of neighborhood effects in Latino Comunas: the script of "the Delinquent" in understanding drug use, violence, and social disorganization.

PubMed

Horner, Pilar; Sanchez, Ninive; Castillo, Marcela; Delva, Jorge

2012-06-01

To obtain rich information about how adult Latinos living in high-poverty/high-drug use neighborhoods perceive and negotiate their environment. In 2008, 13 adult caregivers in Santiago, Chile, were interviewed with open-ended questions to ascertain beliefs about neighborhood effects and drug use. Inductive analysis was used to develop the codebook/identify trends. Residents externalized their understanding of drug use and misuse by invoking the concept of delinquent youth. A typology of their perceptions is offered. Learning more about residents' circumstances may help focus on needs-based interventions. More research with Latino neighborhoods is needed for culturally competent models of interventions.
A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation.

PubMed

Artemov, Artem; Aliper, Alexander; Korzinkin, Michael; Lezhnina, Ksenia; Jellen, Leslie; Zhukov, Nikolay; Roumiantsev, Sergey; Gaifullin, Nurshat; Zhavoronkov, Alex; Borisov, Nicolas; Buzdin, Anton

2015-10-06

A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearson's correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.
Identifying anti-cancer drug response related genes using an integrative analysis of transcriptomic and genomic variations with cell line-based drug perturbations.

PubMed

Sun, Yi; Zhang, Wei; Chen, Yunqin; Ma, Qin; Wei, Jia; Liu, Qi

2016-02-23

Clinical responses to anti-cancer therapies often only benefit a defined subset of patients. Predicting the best treatment strategy hinges on our ability to effectively translate genomic data into actionable information on drug responses. To achieve this goal, we compiled a comprehensive collection of baseline cancer genome data and drug response information derived from a large panel of cancer cell lines. This data set was applied to identify the signature genes relevant to drug sensitivity and their resistance by integrating CNVs and the gene expression of cell lines with in vitro drug responses. We presented an efficient in-silico pipeline for integrating heterogeneous cell line data sources with the simultaneous modeling of drug response values across all the drugs and cell lines. Potential signature genes correlated with drug response (sensitive or resistant) in different cancer types were identified. Using signature genes, our collaborative filtering-based drug response prediction model outperformed the 44 algorithms submitted to the DREAM competition on breast cancer cells. The functions of the identified drug response related signature genes were carefully analyzed at the pathway level and the synthetic lethality level. Furthermore, we validated these signature genes by applying them to the classification of the different subtypes of the TCGA tumor samples, and further uncovered their in vivo implications using clinical patient data. Our work may have promise in translating genomic data into customized marker genes relevant to the response of specific drugs for a specific cancer type of individual patients.
Analysis of Drug Policy in the Republic of Slovenia and in the EU Context: A Platform for Prevention in Schools

ERIC Educational Resources Information Center

Kvaternik, Ines; Rihter, Liljana

2012-01-01

Aims: This article presents an overview of the strategies and measures used in the context of school-based prevention in Slovenia, both on a declaratory and on a practical level. Methods: A review of the Resolution on the National Programme on Drugs in the Republic of Slovenia [ReNPPD (2004). Resolucija o nacionalnem programu na podrocju drog…
Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones.

PubMed

Martins Alho, Miriam A; Marrero-Ponce, Yovani; Barigye, Stephen J; Meneses-Marcel, Alfredo; Machado Tugores, Yanetsy; Montero-Torres, Alina; Gómez-Barrio, Alicia; Nogal, Juan J; García-Sánchez, Rory N; Vega, María Celeste; Rolón, Miriam; Martínez-Fernández, Antonio R; Escario, José A; Pérez-Giménez, Facundo; Garcia-Domenech, Ramón; Rivera, Norma; Mondragón, Ricardo; Mondragón, Mónica; Ibarra-Velarde, Froylán; Lopez-Arencibia, Atteneri; Martín-Navarro, Carmen; Lorenzo-Morales, Jacob; Cabrera-Serra, Maria Gabriela; Piñero, Jose; Tytgat, Jan; Chicharro, Roberto; Arán, Vicente J

2014-03-01

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In an effort to overcome this problem, the main purpose of this study is to develop a QSARs-based ensemble classifier for antiprotozoan drug-like entities from a heterogeneous compounds collection. Here, we use some of the TOMOCOMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved. Firstly, we construct a wide-spectrum benchmark database comprising of 680 organic chemicals with great structural variability (254 of them antiprotozoan agents and 426 to drugs having other clinical uses). This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. In total, seven discriminant functions were obtained, by using the whole set of atom-based linear indices. All the LDA-based QSAR models show accuracies above 85% in the training set and values of Matthews correlation coefficients (C) vary from 0.70 to 0.86. The external validation set shows rather-good global classifications of around 80% (92.05% for best equation). Later, we developed a multi-agent QSAR classification system, in which the individual QSAR outputs are the inputs of the aforementioned fusion approach. Finally, the fusion model was used for the identification of a novel generation of lead-like antiprotozoan compounds by using ligand-based virtual screening of 'available' small molecules (with synthetic feasibility) in our 'in-house' library. A new molecular subsystem (quinoxalinones) was then theoretically selected as a promising lead series, and its derivatives subsequently synthesized, structurally characterized, and experimentally assayed by using in vitro screening that took into consideration a battery of five parasite-based assays. The chemicals 11(12) and 16 are the most active (hits) against apicomplexa (sporozoa) and mastigophora (flagellata) subphylum parasites, respectively. Both compounds depicted good activity in every protozoan in vitro panel and they did not show unspecific cytotoxicity on the host cells. The described technical framework seems to be a promising QSAR-classifier tool for the molecular discovery and development of novel classes of broad-antiprotozoan-spectrum drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of protozoan illnesses. Copyright © 2014 Elsevier Ltd. All rights reserved.
Safety analysis of occupational exposure of healthcare workers to residual contaminations of cytotoxic drugs using FMECA security approach.

PubMed

Le, Laetitia Minh Mai; Reitter, Delphine; He, Sophie; Bonle, Franck Té; Launois, Amélie; Martinez, Diane; Prognon, Patrice; Caudron, Eric

2017-12-01

Handling cytotoxic drugs is associated with chemical contamination of workplace surfaces. The potential mutagenic, teratogenic and oncogenic properties of those drugs create a risk of occupational exposure for healthcare workers, from reception of starting materials to the preparation and administration of cytotoxic therapies. The Security Failure Mode Effects and Criticality Analysis (FMECA) was used as a proactive method to assess the risks involved in the chemotherapy compounding process. FMECA was carried out by a multidisciplinary team from 2011 to 2016. Potential failure modes of the process were identified based on the Risk Priority Number (RPN) that prioritizes corrective actions. Twenty-five potential failure modes were identified. Based on RPN results, the corrective actions plan was revised annually to reduce the risk of exposure and improve practices. Since 2011, 16 specific measures were implemented successively. In six years, a cumulative RPN reduction of 626 was observed, with a decrease from 912 to 286 (-69%) despite an increase of cytotoxic compounding activity of around 23.2%. In order to anticipate and prevent occupational exposure, FMECA is a valuable tool to identify, prioritize and eliminate potential failure modes for operators involved in the cytotoxic drug preparation process before the failures occur. Copyright © 2017 Elsevier B.V. All rights reserved.
Spectrofluorimetric methods of stability-indicating assay of certain drugs affecting the cardiovascular system

NASA Astrophysics Data System (ADS)

Moussa, B. A.; Mohamed, M. F.; Youssef, N. F.

2011-01-01

Two stability-indicating spectrofluorimetric methods have been developed for the determination of ezetimibe and olmesartan medoxomil, drugs affecting the cardiovascular system, and validated in the presence of their degradation products. The first method, for ezetimibe, is based on an oxidative coupling reaction of ezetimibe with 3-methylbenzothiazolin-2-one hydrazone hydrochloride in the presence of cerium (IV) ammonium sulfate in an acidic medium. The quenching effect of ezetimibe on the fluorescence of excess cerous ions is measured at the emission wavelength, λem, of 345 nm with the excitation wavelength, λex, of 296 nm. Factors affecting the reaction were carefully studied and optimized. The second method, for olmesartan medoxomil, is based on measuring the native fluorescence intensity of olmesartan medoxomil in methanol at λem = 360 nm with λex = 286 nm. Regression plots revealed good linear relationships in the assay limits of 10-120 and 8-112 g/ml for ezetimibe and olmesartan medoxomil, respectively. The validity of the methods was assessed according to the United States Pharmacopeya guidelines. Statistical analysis of the results exposed good Student's t-test and F-ratio values. The introduced methods were successfully applied to the analysis of ezetimibe and olmesartan medoxomil in drug substances and drug products as well as in the presence of their degradation products.
Exploration of approaches to adjusting brand-name drug prices in Mainland of China: based on comparison and analysis of some brand-name drug prices of Mainland and Taiwan, China.

PubMed

Weng, Geng; Han, Sheng; Pu, Run; Pan, Wynn H T; Shi, Luwen

2014-01-01

Under the circumstance of the New Medical Reform in Mainland of China, lowering drug prices has become an approach to relieving increase of medical expenses, and lowering brand-name medication price is a key strategy. This study, by comparing and analyzing brand-name medication prices between Mainland of China and Taiwan, explores how to adjust brand-name medication prices in Mainland of China in the consideration of the drug administrative strategies in Taiwan. By selecting brand-name drug with generic name and dose types matched in Mainland and Taiwan, calculate the average unit price and standard deviation and test it with the paired t-test. In the mean time, drug administrative strategies between Mainland and Taiwan are also compared systematically. Among the 70 brand-name medications with generic names and matched dose types, 54 are at higher prices in Mainland of China than Taiwan, which is statistically significant in t-test. Also, among the 47 medications with all of matched generic names, dose types, and manufacturing enterprises, 38 are at higher prices in Mainland than Taiwan, and the gap is also statistically significant in t-test. In Mainland of China, brand-name medication took cost-plus pricing and price-based price adjustment, while in Taiwan, brand-name medication took internal and external reference pricing and market-based price adjustment. Brand-name drug prices were higher in Mainland of China than in Taiwan. The adjustment strategies of drug prices are scientific in Taiwan and are worth reference by Mainland of China.

The Cost Effectiveness of Psychological and Pharmacological Interventions for Social Anxiety Disorder: A Model-Based Economic Analysis.

PubMed

Mavranezouli, Ifigeneia; Mayo-Wilson, Evan; Dias, Sofia; Kew, Kayleigh; Clark, David M; Ades, A E; Pilling, Stephen

2015-01-01

Social anxiety disorder is one of the most persistent and common anxiety disorders. Individually delivered psychological therapies are the most effective treatment options for adults with social anxiety disorder, but they are associated with high intervention costs. Therefore, the objective of this study was to assess the relative cost effectiveness of a variety of psychological and pharmacological interventions for adults with social anxiety disorder. A decision-analytic model was constructed to compare costs and quality adjusted life years (QALYs) of 28 interventions for social anxiety disorder from the perspective of the British National Health Service and personal social services. Efficacy data were derived from a systematic review and network meta-analysis. Other model input parameters were based on published literature and national sources, supplemented by expert opinion. Individual cognitive therapy was the most cost-effective intervention for adults with social anxiety disorder, followed by generic individual cognitive behavioural therapy (CBT), phenelzine and book-based self-help without support. Other drugs, group-based psychological interventions and other individually delivered psychological interventions were less cost-effective. Results were influenced by limited evidence suggesting superiority of psychological interventions over drugs in retaining long-term effects. The analysis did not take into account side effects of drugs. Various forms of individually delivered CBT appear to be the most cost-effective options for the treatment of adults with social anxiety disorder. Consideration of side effects of drugs would only strengthen this conclusion, as it would improve even further the cost effectiveness of individually delivered CBT relative to phenelzine, which was the next most cost-effective option, due to the serious side effects associated with phenelzine. Further research needs to determine more accurately the long-term comparative benefits and harms of psychological and pharmacological interventions for social anxiety disorder and establish their relative cost effectiveness with greater certainty.
The Cost Effectiveness of Psychological and Pharmacological Interventions for Social Anxiety Disorder: A Model-Based Economic Analysis

PubMed Central

Mavranezouli, Ifigeneia; Mayo-Wilson, Evan; Dias, Sofia; Kew, Kayleigh; Clark, David M.; Ades, A. E.; Pilling, Stephen

2015-01-01

Background Social anxiety disorder is one of the most persistent and common anxiety disorders. Individually delivered psychological therapies are the most effective treatment options for adults with social anxiety disorder, but they are associated with high intervention costs. Therefore, the objective of this study was to assess the relative cost effectiveness of a variety of psychological and pharmacological interventions for adults with social anxiety disorder. Methods A decision-analytic model was constructed to compare costs and quality adjusted life years (QALYs) of 28 interventions for social anxiety disorder from the perspective of the British National Health Service and personal social services. Efficacy data were derived from a systematic review and network meta-analysis. Other model input parameters were based on published literature and national sources, supplemented by expert opinion. Results Individual cognitive therapy was the most cost-effective intervention for adults with social anxiety disorder, followed by generic individual cognitive behavioural therapy (CBT), phenelzine and book-based self-help without support. Other drugs, group-based psychological interventions and other individually delivered psychological interventions were less cost-effective. Results were influenced by limited evidence suggesting superiority of psychological interventions over drugs in retaining long-term effects. The analysis did not take into account side effects of drugs. Conclusion Various forms of individually delivered CBT appear to be the most cost-effective options for the treatment of adults with social anxiety disorder. Consideration of side effects of drugs would only strengthen this conclusion, as it would improve even further the cost effectiveness of individually delivered CBT relative to phenelzine, which was the next most cost-effective option, due to the serious side effects associated with phenelzine. Further research needs to determine more accurately the long-term comparative benefits and harms of psychological and pharmacological interventions for social anxiety disorder and establish their relative cost effectiveness with greater certainty. PMID:26506554
Significant differences in pediatric psychotropic side effects: Implications for school performance.

PubMed

Kubiszyn, Thomas; Mire, Sarah; Dutt, Sonia; Papathopoulos, Katina; Burridge, Andrea Backsheider

2012-03-01

Some side effects (SEs) of increasingly prescribed psychotropic medications can impact student performance in school. SE risk varies, even among drugs from the same class (e.g., antidepressants). Knowing which SEs occur significantly more often than others may enable school psychologists to enhance collaborative risk-benefit analysis, medication monitoring, data-based decision-making, and inform mitigation efforts. SE data from Full Prescribing Information (PI) on the FDA website for ADHD drugs, atypical antipsychotics, and antidepressants with pediatric indications were analyzed. Risk ratios (RR) are reported for each drug within a category compared with placebo. RR tables and graphs inform the reader about SE incidence differences for each drug and provide clear evidence of the wide variability in SE incidence in the FDA data. Breslow-Day and Cochran Mantel-Haenszel methods were used to test for drug-placebo SE differences and to test for significance across drugs within each category based on odds ratios (ORs). Significant drug-placebo differences were found for each drug compared with placebo, when odds were pooled across all drugs in a category compared with placebo, and between some drugs within categories. Unexpectedly, many large RR differences did not reach significance. Potential explanations are offered, including limitations of the FDA data sets and statistical and methodological issues. Future research directions are offered. The potential impact of certain SEs on school performance, mitigation strategies, and the potential role of the school psychologist is discussed, with consideration for ethical and legal limitations. (c) 2012 APA, all rights reserved.
An overview of forensic drug testing methods and their suitability for harm reduction point-of-care services.

PubMed

Harper, Lane; Powell, Jeff; Pijl, Em M

2017-07-31

Given the current opioid crisis around the world, harm reduction agencies are seeking to help people who use drugs to do so more safely. Many harm reduction agencies are exploring techniques to test illicit drugs to identify and, where possible, quantify their constituents allowing their users to make informed decisions. While these technologies have been used for years in Europe (Nightlife Empowerment & Well-being Implementation Project, Drug Checking Service: Good Practice Standards; Trans European Drugs Information (TEDI) Workgroup, Factsheet on Drug Checking in Europe, 2011; European Monitoring Centre for Drugs and Drug Addiction, An Inventory of On-site Pill-Testing Interventions in the EU: Fact Files, 2001), they are only now starting to be utilized in this context in North America. The goal of this paper is to describe the most common methods for testing illicit substances and then, based on this broad, encompassing review, recommend the most appropriate methods for testing at point of care.Based on our review, the best methods for point-of-care drug testing are handheld infrared spectroscopy, Raman spectroscopy, and ion mobility spectrometry; mass spectrometry is the current gold standard in forensic drug analysis. It would be prudent for agencies or clinics that can obtain the funding to contact the companies who produce these devices to discuss possible usage in a harm reduction setting. Lower tech options, such as spot/color tests and immunoassays, are limited in their use but affordable and easy to use.
Analysis of stimulant drugs in the wastewater of five Nordic capitals.

PubMed

Löve, Arndís Sue Ching; Baz-Lomba, Jose Antonio; Reid, Malcolm J; Kankaanpää, Aino; Gunnar, Teemu; Dam, Maria; Ólafsdóttir, Kristín; Thomas, Kevin V

2018-06-15

Wastewater-based epidemiology is an efficient way to assess illicit drug use, complementing currently used methods retrieved from different data sources. The aim of this study is to compare stimulant drug use in five Nordic capital cities that include for the first time wastewater samples from Torshavn in the Faroe Islands. Currently there are no published reports that compare stimulant drug use in these Nordic capitals. All wastewater samples were analyzed using solid phase extraction and ultra-high performance liquid chromatography coupled to tandem mass spectrometry. The results were compared with data published by the European Monitoring Centre for Drugs and Drug Addiction based on illicit drugs in wastewater from over 50 European cities. Confirming previous reports, the results showed high amphetamine loads compared with other European countries. Very little apparent abuse of stimulant drugs was detected in Torshavn. Methamphetamine loads were the highest from Helsinki of the Nordic countries, indicating substantial fluctuations in the availability of the drug compared with previous studies. Methamphetamine loads from Oslo confirmed that the use continues to be high. Estimated cocaine use was found to be in the lower range compared with other cities in the southern and western part of Europe. Ecstasy and cocaine showed clear variations between weekdays and weekends, indicating recreational use. This study further demonstrates geographical trends in the stimulant drug market in five Nordic capitals, which enables a better comparison with other areas of the continent. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Surface-Modification of Carbonate Apatite Nanoparticles Enhances Delivery and Cytotoxicity of Gemcitabine and Anastrozole in Breast Cancer Cells

PubMed Central

Mozar, Fitya Syarifa; Chowdhury, Ezharul Hoque

2017-01-01

pH sensitive nanoparticles of carbonate apatite (CA) have been proven to be effective delivery vehicles for DNA, siRNAs and proteins. More recently, conventional anti-cancer drugs, such as doxorubicin, methotrexate and cyclophosphamide have been successfully incorporated into CA for intracellular delivery to breast cancer cells. However, physical and chemical properties of drug molecules appeared to affect their interactions with CA, with hydrophillic drug so far exhibiting better binding affinity and cellular uptakes compared to hydrophobic drugs. In this study, anastrozole, a non-steroidal aromatase inhibitor which is largely hydrophobic, and gemcitabine, a hydrophilic nucleoside inhibitor were used as solubility models of chemotherapy drug. Aggregation tendency of poorly soluble drugs resulting in larger particle-drug complex size might be the main factor hindering their delivery effectiveness. For the first time, surface modification of CA with poly(ethylene glycol) (PEG) has shown promising result to drastically reduce anastrozole- loaded CA particle size, from approximately 1000 to 500 nm based on zeta sizer analysis. Besides PEG, a cell specific ligand, in this case fibronectin, was attached to the particles in order to facilitate receptor mediated endocytosis based on fibronectin–integrin interaction. High-performance liquid chromatography (HPLC) was performed to measure uptake of the drugs by breast cancer cells, revealing that surface modification increased the drug uptake, especially for the hydrophobic drug, compared to the uncoated particles and the free drug. In vitro chemosensitivity assay and in vivo tumor regression study also showed that coated apatite/drug nanoparticle complexes presented higher cytotoxicity and tumor regression effects than uncoated apatite/drug nanoparticles and free drugs, indicating that surface modification successfully created optimum particles size with the consequence of more effective uptake along with favorable pharmacokinetics of the particles. PMID:28590445
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

PubMed Central

Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J.M.; London, Gábor; Nussinov, Ruth

2013-01-01

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The “central hit strategy” selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The “network influence strategy” works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach. PMID:23384594
Social and Structural Challenges to Drug Cessation Among Couples in Northern Mexico: Implications for Drug Treatment in Underserved Communities

PubMed Central

Bazzi, Angela Robertson; Syvertsen, Jennifer L.; Rolón, María Luisa; Martinez, Gustavo; Rangel, Gudelia; Vera, Alicia; Amaro, Hortensia; Ulibarri, Monica D.; Hernandez, Daniel O.; Strathdee, Steffanie A.

2015-01-01

Background Available drug treatment modalities may inadequately address social and structural contexts surrounding recovery efforts. Methods This mixed methods analysis drew on (1) surveys with female sex workers and their intimate male partners and (2) semi-structured interviews with a subsample of 41 couples (n = 82 individuals, 123 total interviews) in Northern Mexico. Descriptive and content analyses examined drug cessation and treatment experiences. Results Perceived need for drug treatment was high, yet only 35% had ever accessed services. Financial and institutional barriers (childcare needs, sex-segregated facilities) prevented partners from enrolling in residential programs together or simultaneously, leading to self-treatment attempts. Outpatient methadone was experienced more positively, yet financial constraints limited access and treatment duration. Relapse was common, particularly when one partner enrolled alone while the other continued using drugs. Conclusions Affordable, accessible, evidence-based drug treatment and recovery services that acknowledge social and structural contexts surrounding recovery are urgently needed for drug-involved couples. PMID:26470596
An informatics approach to assess pediatric pharmacotherapy: design and implementation of a hospital drug utilization system.

PubMed

Zuppa, Athena; Vijayakumar, Sundararajan; Jayaraman, Bhuvana; Patel, Dimple; Narayan, Mahesh; Vijayakumar, Kalpana; Mondick, John T; Barrett, Jeffrey S

2007-09-01

Drug utilization in the inpatient setting can provide a mechanism to assess drug prescribing trends, efficiency, and cost-effectiveness of hospital formularies and examine subpopulations for which prescribing habits may be different. Such data can be used to correlate trends with time-dependent or seasonal changes in clinical event rates or the introduction of new pharmaceuticals. It is now possible to provide a robust, dynamic analysis of drug utilization in a large pediatric inpatient setting through the creation of a Web-based hospital drug utilization system that retrieves source data from our accounting database. The production implementation provides a dynamic and historical account of drug utilization at the authors' institution. The existing application can easily be extended to accommodate a multi-institution environment. The creation of a national or even global drug utilization network would facilitate the examination of geographical and/or socioeconomic influences in drug utilization and prescribing practices in general.
Drugs & the Brain: Case-based Instruction for an Undergraduate Neuropharmacology Course.

PubMed

Nagel, Anastasia; Nicholas, Andrea

2017-01-01

In order to transform a traditional large non-majors general education (GE) neurobiology lecture (Drugs & the Brain) into an active learning course, we developed a series of directed mini-cases targeting major drug classes. Humorous and captivating case-based situations were used to better engage and motivate students to solve problems related to neuropharmacology and physiology. Here we provide directed cases, questions and learning outcomes for our opiates mini-cases. In addition, we describe how case studies were incorporated into our course and assessed using peer review and online quizzing. An in-depth analysis of the overall course transformation on student exam performance, opinions and instructor evaluations can be found in the JUNE article Don't Believe the Gripe! Increasing Course Structure in a Large Non-majors Neuroscience Course.
Estimation of the size of drug-like chemical space based on GDB-17 data.

PubMed

Polishchuk, P G; Madzhidov, T I; Varnek, A

2013-08-01

The goal of this paper is to estimate the number of realistic drug-like molecules which could ever be synthesized. Unlike previous studies based on exhaustive enumeration of molecular graphs or on combinatorial enumeration preselected fragments, we used results of constrained graphs enumeration by Reymond to establish a correlation between the number of generated structures (M) and the number of heavy atoms (N): logM = 0.584 × N × logN + 0.356. The number of atoms limiting drug-like chemical space of molecules which follow Lipinsky's rules (N = 36) has been obtained from the analysis of the PubChem database. This results in M ≈ 10³³ which is in between the numbers estimated by Ertl (10²³) and by Bohacek (10⁶⁰).
Management of irritable bowel syndrome in primary care: feasibility randomised controlled trial of mebeverine, methylcellulose, placebo and a patient self-management cognitive behavioural therapy website. (MIBS trial).

PubMed

Everitt, Hazel A; Moss-Morris, Rona E; Sibelli, Alice; Tapp, Laura; Coleman, Nicholas S; Yardley, Lucy; Smith, Peter W; Little, Paul S

2010-11-18

IBS affects 10-22% of the UK population. Abdominal pain, bloating and altered bowel habit affect quality of life, social functioning and time off work. Current GP treatment relies on a positive diagnosis, reassurance, lifestyle advice and drug therapies, but many suffer ongoing symptoms.A recent Cochrane review highlighted the lack of research evidence for IBS drugs. Neither GPs, nor patients have good evidence to inform prescribing decisions. However, IBS drugs are widely used: In 2005 the NHS costs were nearly £10 million for mebeverine and over £8 million for fibre-based bulking agents. CBT and self-management can be helpful, but poor availability in the NHS restricts their use. We have developed a web-based CBT self-management programme, Regul8, based on an existing evidence based self-management manual and in partnership with patients. This could increase access with minimal increased costs. The aim is to undertake a feasibility factorial RCT to assess the effectiveness of the commonly prescribed medications in UK general practice for IBS: mebeverine (anti-spasmodic) and methylcellulose (bulking-agent) and Regul8, the CBT based self-management website.135 patients aged 16 to 60 years with IBS symptoms fulfilling Rome III criteria, recruited via GP practices, will be randomised to 1 of 3 levels of the drug condition: mebeverine, methylcellulose or placebo for 6 weeks and to 1 of 3 levels of the website condition, Regul8 with a nurse telephone session and email support, Regul8 with minimal email support, or no website, thus creating 9 groups. Irritable bowel symptom severity scale and IBS-QOL will be measured at baseline, 6 and 12 weeks as the primary outcomes. An intention to treat analysis will be undertaken by ANCOVA for a factorial trial. This pilot will provide valuable information for a larger trial. Determining the effectiveness of commonly used drug treatments will help patients and doctors make informed treatment decisions regarding drug management of IBS symptoms, enabling better targeting of treatment. A web-based self-management CBT programme for IBS developed in partnership with patients has the potential to benefit large numbers of patients with low cost to the NHS. Assessment of the amount of email or therapist support required for the website will enable economic analysis to be undertaken.
Success, Failure, and Transparency in Biomarker-Based Drug Development: A Case Study of Cholesteryl Ester Transfer Protein Inhibitors.

PubMed

Hey, Spencer Phillips; Franklin, Jessica M; Avorn, Jerry; Kesselheim, Aaron S

2017-06-01

Although biomarkers are used as surrogate measures for drug targeting and approval and are generally based on plausible biological hypotheses, some are found to not correlate well with clinical outcomes. Over-reliance on inadequately validated biomarkers in drug development can lead to harm to trial subjects and patients and to research waste. To shed greater light on the process and ethics of biomarker-based drug development, we conducted a systematic portfolio analysis of cholesterol ester transfer protein inhibitors, a drug class designed to improve lipid profiles and prevent cardiovascular events. Despite years of development, no cholesterol ester transfer protein inhibitor has yet been approved for clinical use. We searched PubMed and Clinicaltrials.gov for clinical studies of 5 known cholesterol ester transfer protein inhibitors: anacetrapib, dalcetrapib, evacetrapib, TA-8995, and torcetrapib. Published reports and registration records were extracted for patient demographic characteristics and study authors' recommendations of clinical usage or further testing. We used Accumulating Evidence and Research Organization graphing to depict the portfolio of research activities and a Poisson model to examine trends. We identified 100 studies for analysis that involved 96 944 human subjects. The data from only 41 201 (42%) of the human subjects had been presented in a published report. For the 3 discontinued cholesterol ester transfer protein inhibitors, we found a pattern of consistently positive results on lipid-modification end points followed by negative results using clinical end points. Inefficiencies and harms can arise if a biomarker hypothesis continues to drive trials despite successive failures. Regulators, research funding bodies, and public policy makers may need to play a greater role in evaluating and coordinating biomarker-driven research programs. © 2017 American Heart Association, Inc.
Problem drinking and the dimension of involvement with drugs: a Guttman scalogram analysis of adolescent drug use.

PubMed Central

Donovan, J E; Jessor, R

1983-01-01

Analyses of data from two nationwide surveys of high school students, one carried out in 1974 and the other in 1978, suggest that problem drinking may be seen as yet another step along an underlying dimension of involvement with both licit and illicit drugs. The dimension of involvement with drugs consists of the following levels: nonuse of alcohol or illicit drugs; nonproblem use of alcohol; marijuana use; problem drinking; use of pills (amphetamines, barbiturates, hallucinogenic drugs); and the use of "hard drugs" such as cocaine or heroin. The dimension possesses excellent Guttman-scale properties in both national samples as well as in subsamples differing in gender and ethnic background. The ordering of the levels of involvement was confirmed by the ordering of the alcohol-drug involvement groups based on their mean scores on measures of psychosocial proneness for involvement in problem behavior. The excessive use of a licit drug, i.e., problem drinking, appears to indicate greater involvement in drug use than does the use of an illicit drug, marijuana. This finding points to the importance of distinguishing between use and problem use of drugs in efforts to understand adolescent drug involvement. PMID:6837819
DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity

PubMed Central

Anchang, Benedict; Davis, Kara L.; Fienberg, Harris G.; Bendall, Sean C.; Karacosta, Loukia G.; Tibshirani, Robert; Nolan, Garry P.; Plevritis, Sylvia K.

2018-01-01

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple (>40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples. PMID:29654148
EPOR-Based Purification and Analysis of Erythropoietin Mimetic Peptides from Human Urine by Cys-Specific Cleavage and LC/MS/MS

NASA Astrophysics Data System (ADS)

Vogel, Matthias; Thomas, Andreas; Schänzer, Wilhelm; Thevis, Mario

2015-09-01

The development of a new class of erythropoietin mimetic agents (EMA) for treating anemic conditions has been initiated with the discovery of oligopeptides capable of dimerizing the erythropoietin (EPO) receptor and thus stimulating erythropoiesis. The most promising amino acid sequences have been mounted on various different polymeric structures or carrier molecules to obtain highly active EPO-like drugs exhibiting beneficial and desirable pharmacokinetic profiles. Concomitant with creating new therapeutic options, erythropoietin mimetic peptide (EMP)-based drug candidates represent means to artificially enhance endurance performance and necessitate coverage by sports drug testing methods. Therefore, the aim of the present study was to develop a strategy for the comprehensive detection of EMPs in doping controls, which can be used complementary to existing protocols. Three model EMPs were used to provide proof-of-concept data. Following EPO receptor-facilitated purification of target analytes from human urine, the common presence of the cysteine-flanked core structure of EMPs was exploited to generate diagnostic peptides with the aid of a nonenzymatic cleavage procedure. Sensitive detection was accomplished by targeted-SIM/data-dependent MS2 analysis. Method characterization was conducted for the EMP-based drug peginesatide concerning specificity, linearity, precision, recovery, stability, ion suppression/enhancement, and limit of detection (LOD, 0.25 ng/mL). Additionally, first data for the identification of the erythropoietin mimetic peptides EMP1 and BB68 were generated, demonstrating the multi-analyte testing capability of the presented approach.
Visualisation and quantitative analysis of the rodent malaria liver stage by real time imaging.

PubMed

Ploemen, Ivo H J; Prudêncio, Miguel; Douradinha, Bruno G; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J F; Hermsen, Cornelus C; Sauerwein, Robert W; Baptista, Fernanda G; Mota, Maria M; Waters, Andrew P; Que, Ivo; Lowik, Clemens W G M; Khan, Shahid M; Janse, Chris J; Franke-Fayard, Blandine M D

2009-11-18

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luc(con), expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1-5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium.
Visualisation and Quantitative Analysis of the Rodent Malaria Liver Stage by Real Time Imaging

PubMed Central

Douradinha, Bruno G.; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J. F.; Hermsen, Cornelus C.; Sauerwein, Robert W.; Baptista, Fernanda G.; Mota, Maria M.; Waters, Andrew P.; Que, Ivo; Lowik, Clemens W. G. M.; Khan, Shahid M.; Janse, Chris J.; Franke-Fayard, Blandine M. D.

2009-01-01

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luccon, expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1–5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium. PMID:19924309
Automated Drug Identification for Urban Hospitals

NASA Technical Reports Server (NTRS)

Shirley, Donna L.

1971-01-01

Many urban hospitals are becoming overloaded with drug abuse cases requiring chemical analysis for identification of drugs. In this paper, the requirements for chemical analysis of body fluids for drugs are determined and a system model for automated drug analysis is selected. The system as modeled, would perform chemical preparation of samples, gas-liquid chromatographic separation of drugs in the chemically prepared samples, infrared spectrophotometric analysis of the drugs, and would utilize automatic data processing and control for drug identification. Requirements of cost, maintainability, reliability, flexibility, and operability are considered.
Economic evaluation of weekends-off antiretroviral therapy for young people in 11 countries.

PubMed

Tierrablanca, Luis Enrique; Ochalek, Jessica; Ford, Deborah; Babiker, Ab; Gibb, Diana; Butler, Karina; Turkova, Anna; Griffin, Susan; Revill, Paul

2018-02-01

To analyze the cost effectiveness of short-cycle therapy (SCT), where patients take antiretroviral (ARV) drugs 5 consecutive days a week and have 2 days off, as an alternative to continuous ARV therapy for young people infected with human immunodeficiency virus (HIV) and taking efavirenz-based first-line ARV drugs. We conduct a hierarchical cost-effectiveness analysis based on data on clinical outcomes and resource use from the BREATHER trial. BREATHER is a randomized trial investigating the effectiveness of SCT and continuous therapy in 199 participants aged 8 to 24 years and taking efavirenz-based first-line ARV drugs in 11 countries worldwide. Alongside nationally representative unit costs/prices, these data were used to estimate costs and quality adjusted life years (QALYs). An incremental cost-effectiveness comparison was performed using a multilevel bivariate regression approach for total costs and QALYs. Further analyses explored cost-effectiveness in low- and middle-income countries with access to low-cost generic ARV drugs and high-income countries purchasing branded ARV drugs, respectively. At 48 weeks, SCT offered significant total cost savings over continuous therapy of US dollar (USD) 41 per patient in countries using generic drugs and USD 4346 per patient in countries using branded ARV drugs, while accruing nonsignificant total health benefits of 0.008 and 0.009 QALYs, respectively. Cost-effectiveness estimates were similar across settings with access to generic ARV drugs but showed significant variation among high-income countries where branded ARV drugs are purchased. SCT is a cost-effective treatment alternative to continuous therapy for young people infected with HIV in countries where viral load monitoring is available.

Industry Perspectives on Market Access of Innovative Drugs: The Relevance for Oncology Drugs.

PubMed

Pauwels, Kim; Huys, Isabelle; Casteels, Minne; Simoens, Steven

2016-01-01

Key Points - Representatives of the pharmaceutical industry call for a broader recognition of value within the assessment and appraisal of innovative drugs- Focus on value within the assessment and appraisal of drugs is jeopardized by financial drives as the side of industry and at the side of the payers- A well-considered value-framework, with attention for patient reported outcomes, societal preferences and dynamic approach on the drug life cycle, needs to be incorporated in assessment and appraisal at national and European level in order to coordinate the views of different stakeholders and allow efficient resource allocation This study presents industry perspectives on the challenges related to market access of innovative drugs in general and oncology drugs in specific. Fifteen interviews were conducted with representatives of pharmaceutical companies and industry associations. Interviewees call for a broader recognition of value within the assessment and appraisal of drugs. According to interviewees, focus on value is jeopardized by the lack of a common value definition across Europe, poor availability and validity of value measures and cost-saving measures such as external reference price setting and cost-effectiveness analysis at the side of the payers. Centralized assessment of relative-effectiveness at European level would provide a common value estimate across member states, independent of financial drivers. Empirical evidence on PRO and societal preferences is however essential in the development of a value definition. Furthermore, value-based pricing would imply a dynamic approach where the price is differentiated across indications and across the lifecycle of the drug, especially in fields such as oncology. Financial drivers however also threat the application of value-based pricing at the side of the industry, making value-based profitability a more appropriate term.
Economic evaluation of weekends-off antiretroviral therapy for young people in 11 countries

PubMed Central

Tierrablanca, Luis Enrique; Ochalek, Jessica; Ford, Deborah; Babiker, Ab; Gibb, Diana; Butler, Karina; Turkova, Anna; Griffin, Susan; Revill, Paul

2018-01-01

Abstract Objectives: To analyze the cost effectiveness of short-cycle therapy (SCT), where patients take antiretroviral (ARV) drugs 5 consecutive days a week and have 2 days off, as an alternative to continuous ARV therapy for young people infected with human immunodeficiency virus (HIV) and taking efavirenz-based first-line ARV drugs. Methods: We conduct a hierarchical cost-effectiveness analysis based on data on clinical outcomes and resource use from the BREATHER trial. BREATHER is a randomized trial investigating the effectiveness of SCT and continuous therapy in 199 participants aged 8 to 24 years and taking efavirenz-based first-line ARV drugs in 11 countries worldwide. Alongside nationally representative unit costs/prices, these data were used to estimate costs and quality adjusted life years (QALYs). An incremental cost-effectiveness comparison was performed using a multilevel bivariate regression approach for total costs and QALYs. Further analyses explored cost-effectiveness in low- and middle-income countries with access to low-cost generic ARV drugs and high-income countries purchasing branded ARV drugs, respectively. Results: At 48 weeks, SCT offered significant total cost savings over continuous therapy of US dollar (USD) 41 per patient in countries using generic drugs and USD 4346 per patient in countries using branded ARV drugs, while accruing nonsignificant total health benefits of 0.008 and 0.009 QALYs, respectively. Cost-effectiveness estimates were similar across settings with access to generic ARV drugs but showed significant variation among high-income countries where branded ARV drugs are purchased. Conclusion: SCT is a cost-effective treatment alternative to continuous therapy for young people infected with HIV in countries where viral load monitoring is available. PMID:29384848
CROI 2018: Advances in Antiretroviral Therapy.

PubMed

Tieu, Hong-Van; Taylor, Barbara S; Jones, Joyce; Wilkin, Timothy J

2018-05-01

The 2018 Conference on Retroviruses and Opportunistic Infections (CROI) showcased exciting data on new investigational agents including MK-8591 and tri-specific antibody targeting 3 highly conserved epitopes on HIV-1 in a single antibody. Clinical trials of initial antiretroviral therapy (ART) and switch studies involving bictegravir/emtricitabine/tenofovir alafenamide were presented. Intensification of initial ART with integrase strand transfer inhibitors did not increase the risk of immune reconstitution inflammatory syndrome. Pharmacokinetic issues were discussed, including the substantial drug-drug interactions between efavirenz-based ART and hormonal contraception delivered via a vaginal ring. Studies on pre-ART drug resistance and emergence of drug resistance after initial and second-line ART in different settings and populations were highlighted. Novel technologies to identify drug resistance included a free, cloud-based web service for HIV genotyping analysis and a promising technology for point-of-care drug resistance mutations testing. New strategies to improve the HIV care continuum included home-based testing with initiation of same-day ART and stratified care with specialized clinics to serve those disengaged in care, but the data on financial incentives were not encouraging. Several studies provided insights into the impact of early ART on decreasing the size of the HIV reservoir in HIV-infected infants. Pertinent conference findings relating to women's health issues included similar clinical outcomes between breastfeeding and formula feeding HIV-infected women, the problem of viral rebound and ART nonadherence in pregnancy and postpartum.
[Approaching the "evidence-practice gap" in pharmaceutical risk management: analysis of healthcare claim data].

PubMed

Nakayama, Takeo

2012-01-01

The concept of evidence-based medicine (EBM) has promulgated among healthcare professionals in recent years, on the other hand, the problem of underuse of useful clinical evidence is coming to be important. This is called as evidence-practice gap. The major concern about evidence-practice gap is insufficient implementation of evidence-based effective treatment, however, the perspective can be extended to measures to improve drug safety and prevention of drug related adverse events. First, this article reviews the characteristics of the database of receipt (healthcare claims) and the usefulness for research purpose of pharmacoepidemiology. Second, as the real example of the study on evidence-practice gap by using the receipt database, the case of ergot-derived anti-Parkinson drugs, of which risk of valvulopathy has been identified, is introduced. The receipt analysis showed that more than 70% of Parkinson's disease patients prescribed with cabergoline or pergolide did not undergo echocardiography despite the revision of the product label recommendation. Afterwards, the issues of pharmaceutical risk management and risk communication will be discussed.
Simulation-based cheminformatic analysis of organelle-targeted molecules: lysosomotropic monobasic amines.

PubMed

Zhang, Xinyuan; Zheng, Nan; Rosania, Gus R

2008-09-01

Cell-based molecular transport simulations are being developed to facilitate exploratory cheminformatic analysis of virtual libraries of small drug-like molecules. For this purpose, mathematical models of single cells are built from equations capturing the transport of small molecules across membranes. In turn, physicochemical properties of small molecules can be used as input to simulate intracellular drug distribution, through time. Here, with mathematical equations and biological parameters adjusted so as to mimic a leukocyte in the blood, simulations were performed to analyze steady state, relative accumulation of small molecules in lysosomes, mitochondria, and cytosol of this target cell, in the presence of a homogenous extracellular drug concentration. Similarly, with equations and parameters set to mimic an intestinal epithelial cell, simulations were also performed to analyze steady state, relative distribution and transcellular permeability in this non-target cell, in the presence of an apical-to-basolateral concentration gradient. With a test set of ninety-nine monobasic amines gathered from the scientific literature, simulation results helped analyze relationships between the chemical diversity of these molecules and their intracellular distributions.
Analysis of Antiretrovirals in Single Hair Strands for Evaluation of Drug Adherence with Infrared-Matrix-Assisted Laser Desorption Electrospray Ionization Mass Spectrometry Imaging.

PubMed

Rosen, Elias P; Thompson, Corbin G; Bokhart, Mark T; Prince, Heather M A; Sykes, Craig; Muddiman, David C; Kashuba, Angela D M

2016-01-19

Adherence to a drug regimen can be a strong predictor of health outcomes, and validated measures of adherence are necessary at all stages of therapy from drug development to prescription. Many of the existing metrics of drug adherence (e.g., self-report, pill counts, blood monitoring) have limitations, and analysis of hair strands has recently emerged as an objective alternative. Traditional methods of hair analysis based on LC-MS/MS (segmenting strands at ≥1 cm length) are not capable of preserving a temporal record of drug intake at higher resolution than approximately 1 month. Here, we evaluated the detectability of HIV antiretrovirals (ARVs) in hair from a range of drug classes using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) with 100 μm resolution. Infrared laser desorption of hair strands was shown to penetrate into the strand cortex, allowing direct measurement by MSI without analyte extraction. Using optimized desorption conditions, a linear correlation between IR-MALDESI ion abundance and LC-MS/MS response was observed for six common ARVs with estimated limits of detection less than or equal to 1.6 ng/mg hair. The distribution of efavirenz (EFV) was then monitored in a series of hair strands collected from HIV infected, virologically suppressed patients. Because of the role hair melanin plays in accumulation of basic drugs (like most ARVs), an MSI method to quantify the melanin biomarker pyrrole-2,3,5-tricarboxylic acid (PTCA) was evaluated as a means of normalizing drug response between patients to develop broadly applicable adherence criteria.
ANALYSIS OF DRUG-PROTEIN BINDING BY ULTRAFAST AFFINITY CHROMATOGRAPHY USING IMMOBILIZED HUMAN SERUM ALBUMIN

PubMed Central

Mallik, Rangan; Yoo, Michelle J.; Briscoe, Chad J.; Hage, David S.

2010-01-01

Human serum albumin (HSA) was explored for use as a stationary phase and ligand in affinity microcolumns for the ultrafast extraction of free drug fractions and the use of this information for the analysis of drug-protein binding. Warfarin, imipramine, and ibuprofen were used as model analytes in this study. It was found that greater than 95% extraction of all these drugs could be achieved in as little as 250 ms on HSA microcolumns. The retained drug fraction was then eluted from the same column under isocratic conditions, giving elution in less than 40 s when working at 4.5 mL/min. The chromatographic behavior of this system gave a good fit with that predicted by computer simulations based on a reversible, saturable model for the binding of an injected drug with immobilized HSA. The free fractions measured by this method were found to be comparable to those determined by ultrafiltration, and equilibrium constants estimated by this approach gave good agreement with literature values. Advantages of this method include its speed and the relatively low cost of microcolumns that contain HSA. The ability of HSA to bind many types of drugs also creates the possibility of using the same affinity microcolumn to study and measure the free fractions for a variety of pharmaceutical agents. These properties make this technique appealing for use in drug binding studies and in the high-throughput screening of new drug candidates. PMID:20227701
Strategic incorporation of fluorine in the drug discovery of new-generation antitubercular agents targeting bacterial cell division protein FtsZ⋆

PubMed Central

Ojima, Iwao; Awasthi, Divya; Wei, Longfei; Haranahalli, Krupanandan

2016-01-01

This article presents an account of our research on the discovery and development of new-generation fluorine-containing antibacterial agents against drug-resistant tuberculosis, targeting FtsZ. FtsZ is an essential protein for bacterial cell division and a highly promising therapeutic target for antibacterial drug discovery. Through design, synthesis and semi-HTP screening of libraries of novel benzimidazoles, followed by SAR studies, we identified highly potent lead compounds. However, these lead compounds were found to lack sufficient metabolic and plasma stabilities. Accordingly, we have performed extensive study on the strategic incorporation of fluorine into lead compounds to improve pharmacological properties. This study has led to the development of highly efficacious fluorine-containing benzimidazoles as potential drug candidates. We have also performed computational docking analysis of these novel FtsZ inhibitors to identify their putative binding site. Based on the structural data and docking analysis, a plausible mode-of-action for this novel class of FtsZ inhibitors is proposed. PMID:28555087
Quality control of the paracetamol drug by chemometrics and imaging spectroscopy in the near infrared region

NASA Astrophysics Data System (ADS)

Baptistao, Mariana; Rocha, Werickson Fortunato de Carvalho; Poppi, Ronei Jesus

2011-09-01

In this work, it was used imaging spectroscopy and chemometric tools for the development and analysis of paracetamol and excipients in pharmaceutical formulations. It was also built concentration maps to study the distribution of the drug in the tablets surface. Multivariate models based on PLS regression were developed for paracetamol and excipients concentrations prediction. For the construction of the models it was used 31 samples in the tablet form containing the active principle in a concentration range of 30.0-90.0% (w/w) and errors below to 5% were obtained for validation samples. Finally, the study of the distribution in the drug was performed through the distribution maps of concentration of active principle and excipients. The analysis of maps showed the complementarity between the active principle and excipients in the tablets. The region with a high concentration of a constituent must have, necessarily, absence or low concentration of the other one. Thus, an alternative method for the paracetamol drug quality monitoring is presented.
Metabolic Clustering Analysis as a Strategy for Compound Selection in the Drug Discovery Pipeline for Leishmaniasis.

PubMed

Armitage, Emily G; Godzien, Joanna; Peña, Imanol; López-Gonzálvez, Ángeles; Angulo, Santiago; Gradillas, Ana; Alonso-Herranz, Vanesa; Martín, Julio; Fiandor, Jose M; Barrett, Michael P; Gabarro, Raquel; Barbas, Coral

2018-05-18

A lack of viable hits, increasing resistance, and limited knowledge on mode of action is hindering drug discovery for many diseases. To optimize prioritization and accelerate the discovery process, a strategy to cluster compounds based on more than chemical structure is required. We show the power of metabolomics in comparing effects on metabolism of 28 different candidate treatments for Leishmaniasis (25 from the GSK Leishmania box, two analogues of Leishmania box series, and amphotericin B as a gold standard treatment), tested in the axenic amastigote form of Leishmania donovani. Capillary electrophoresis-mass spectrometry was applied to identify the metabolic profile of Leishmania donovani, and principal components analysis was used to cluster compounds on potential mode of action, offering a medium throughput screening approach in drug selection/prioritization. The comprehensive and sensitive nature of the data has also made detailed effects of each compound obtainable, providing a resource to assist in further mechanistic studies and prioritization of these compounds for the development of new antileishmanial drugs.
Analysis of street drugs in seized material without primary reference standards.

PubMed

Laks, Suvi; Pelander, Anna; Vuori, Erkki; Ali-Tolppa, Elisa; Sippola, Erkki; Ojanperä, Ilkka

2004-12-15

A novel approach was used to analyze street drugs in seized material without primary reference standards. Identification was performed by liquid chromatography/time-of-flight mass spectrometry (LC/TOFMS), essentially based on accurate mass determination using a target library of 735 exact monoisotopic masses. Quantification was carried out by liquid chromatography/chemiluminescence nitrogen detection (LC/CLND) with a single secondary standard (caffeine), utilizing the detector's equimolar response to nitrogen. Sample preparation comprised dilution, first with methanol and further with the LC mobile phase. Altogether 21 seized drug samples were analyzed blind by the present method, and results were compared to accredited reference methods utilizing identification by gas chromatography/mass spectrometry and quantification by gas chromatography or liquid chromatography. The 31 drug findings by LC/TOFMS comprised 19 different drugs-of-abuse, byproducts, and adulterants, including amphetamine and tryptamine designer drugs, with one unresolved pair of compounds having an identical mass. By the reference methods, 27 findings could be confirmed, and among the four unconfirmed findings, only 1 apparent false positive was found. In the quantitative analysis of 11 amphetamine, heroin, and cocaine findings, mean relative difference between the results of LC/CLND and the reference methods was 11% (range 4.2-21%), without any observable bias. Mean relative standard deviation for three parallel LC/CLND results was 6%. Results suggest that the present combination of LC/TOFMS and LC/CLND offers a simple solution for the analysis of scheduled and designer drugs in seized material, independent of the availability of primary reference standards.
Microfluidic chip based nano liquid chromatography coupled to tandem mass spectrometry for the determination of abused drugs and metabolites in human hair.

PubMed

Zhu, Kevin Y; Leung, K Wing; Ting, Annie K L; Wong, Zack C F; Ng, Winki Y Y; Choi, Roy C Y; Dong, Tina T X; Wang, Tiejie; Lau, David T W; Tsim, Karl W K

2012-03-01

A microfluidic chip based nano-HPLC coupled to tandem mass spectrometry (nano-HPLC-Chip-MS/MS) has been developed for simultaneous measurement of abused drugs and metabolites: cocaine, benzoylecgonine, cocaethylene, norcocaine, morphine, codeine, 6-acetylmorphine, phencyclidine, amphetamine, methamphetamine, MDMA, MDA, MDEA, and methadone in the hair of drug abusers. The microfluidic chip was fabricated by laminating polyimide films and it integrated an enrichment column, an analytical column and a nanospray tip. Drugs were extracted from hairs by sonication, and the chromatographic separation was achieved in 15 min. The drug identification and quantification criteria were fulfilled by the triple quardropule tandem mass spectrometry. The linear regression analysis was calibrated by deuterated internal standards with all of the R(2) at least over 0.993. The limit of detection (LOD) and the limit of quantification (LOQ) were from 0.1 to 0.75 and 0.2 to 1.25 pg/mg, respectively. The validation parameters including selectivity, accuracy, precision, stability, and matrix effect were also evaluated here. In conclusion, the developed sample preparation method coupled with the nano-HPLC-Chip-MS/MS method was able to reveal the presence of drugs in hairs from the drug abusers, with the enhanced sensitivity, compared with the conventional HPLC-MS/MS.
Kinetic and theoretical studies of novel biodegradable thermo-sensitive xerogels based on PEG/PVP/silica for sustained release of enrofloxacin

NASA Astrophysics Data System (ADS)

Ebadi, Azra; Rafati, Amir Abbas; Bavafa, Sadeghali; Mohammadi, Masoumah

2017-12-01

This study involves the synthesis of a new silica-based colloidal hybrid system. In this new hybrid system, poly (ethylene glycol) (PEG) and thermo-sensitive amphiphilic biocompatible poly (vinyl pyrrolidone) (PVP) were used to create suitable storage for hydrophobic drugs. The possibility of using variable PVP/PEG molar ratios to modulate drug release rate from silica nanoparticles was a primary goal of the current research. In addition, an investigation of the drug release kinetic was conducted. To achieve this, silica nanoparticles were synthesized in poly (ethylene glycol) (PEG) and poly (vinyl pyrrolidone) (PVP) solution incorporated with enrofloxacin (EFX) (as a model hydrophobic drug), using a simple synthetic strategy of hybrid materials which avoided waste and multi-step processes. The impacts of PVP/PEG molar ratios, temperature, and pH of the release medium on release kinetic were investigated. The physicochemical properties of the drug-loaded composites were studied by Fourier transform infrared (FT-IR) spectra, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). In vitro drug release studies demonstrated that the drug release rate, which was evaluated by analyzing the experimental data with seven kinetic models in a primarily non-Fickian diffusion-controlled process, aligned well with both Ritger-Peppas and Sahlin-Peppas equations.
Optical diagnostics of osteoblast cells and osteogenic drug screening

NASA Astrophysics Data System (ADS)

Kolanti, Elayaraja; Veerla, Sarath C.; Khajuria, Deepak K.; Roy Mahapatra, D.

2016-02-01

Microfluidic device based diagnostics involving optical fibre path, in situ imaging and spectroscopy are gaining importance due to recent advances in diagnostics instrumentation and methods, besides other factors such as low amount of reagent required for analysis, short investigation times, and potential possibilities to replace animal model based study in near future. It is possible to grow and monitor tissues in vitro in microfluidic lab-on-chip. It may become a transformative way of studying how cells interact with drugs, pathogens and biomaterials in physiologically relevant microenvironments. To a large extent, progress in developing clinically viable solutions has been constrained because of (i) contradiction between in vitro and in vivo results and (ii) animal model based and clinical studies which is very expensive. Our study here aims to evaluate the usefulness of microfluidic device based 3D tissue growth and monitoring approach to better emulate physiologically and clinically relevant microenvironments in comparison to conventional in vitro 2D culture. Moreover, the microfluidic methodology permits precise high-throughput investigations through real-time imaging while using very small amounts of reagents and cells. In the present study, we report on the details of an osteoblast cell based 3D microfluidic platform which we employ for osteogenic drug screening. The drug formulation is functionalized with fluorescence and other biomarkers for imaging and spectroscopy, respectively. Optical fibre coupled paths are used to obtain insight regarding the role of stress/flow pressure fluctuation and nanoparticle-drug concentration on the osteoblast growth and osteogenic properties of bone.
Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory.

PubMed

Durán, Claudio; Daminelli, Simone; Thomas, Josephine M; Haupt, V Joachim; Schroeder, Michael; Cannistraci, Carlo Vittorio

2017-04-26

The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation frameworks-with unsupervised pure topological-based models designed for general-purpose link prediction in bipartite networks. Surprisingly, our results show that the bipartite topology alone, if adequately exploited by means of the recently proposed local-community-paradigm (LCP) theory-initially detected in brain-network topological self-organization and afterwards generalized to any complex network-is able to suggest highly reliable predictions, with comparable performance with the state-of-the-art-supervised methods that exploit additional (non-topological, for instance biochemical) DTI knowledge. Furthermore, a detailed analysis of the novel predictions revealed that each class of methods prioritizes distinct true interactions; hence, combining methodologies based on diverse principles represents a promising strategy to improve drug-target discovery. To conclude, this study promotes the power of bio-inspired computing, demonstrating that simple unsupervised rules inspired by principles of topological self-organization and adaptiveness arising during learning in living intelligent systems (like the brain) can efficiently equal perform complicated algorithms based on advanced, supervised and knowledge-based engineering. © The Author 2017. Published by Oxford University Press.
An alternative approach based on artificial neural networks to study controlled drug release.

PubMed

Reis, Marcus A A; Sinisterra, Rubén D; Belchior, Jadson C

2004-02-01

An alternative methodology based on artificial neural networks is proposed to be a complementary tool to other conventional methods to study controlled drug release. Two systems are used to test the approach; namely, hydrocortisone in a biodegradable matrix and rhodium (II) butyrate complexes in a bioceramic matrix. Two well-established mathematical models are used to simulate different release profiles as a function of fundamental properties; namely, diffusion coefficient (D), saturation solubility (C(s)), drug loading (A), and the height of the device (h). The models were tested, and the results show that these fundamental properties can be predicted after learning the experimental or model data for controlled drug release systems. The neural network results obtained after the learning stage can be considered to quantitatively predict ideal experimental conditions. Overall, the proposed methodology was shown to be efficient for ideal experiments, with a relative average error of <1% in both tests. This approach can be useful for the experimental analysis to simulate and design efficient controlled drug-release systems. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association
A matrix approach to guide IHC-based tissue biomarker development in oncology drug discovery.

PubMed

Smith, Neil R; Womack, Christopher

2014-01-01

Immunohistochemistry (IHC) is a core platform for the analysis of tissue samples, and there is an increasing demand for reliable and quantitative IHC-based tissue biomarkers in oncology clinical research and development (R&D) environments. Biomarker assay and drug development proceed in parallel. Furthermore, biomarker assay requirements change with each phase of drug development. We have therefore developed a matrix tool to enable researchers to evaluate whether a particular IHC biomarker assay is fit for purpose. Experience gained from the development of 130 IHC biomarkers, supporting a large number of oncology drug projects, was used to formulate a practical approach to IHC assay development. The resultant matrix grid and accompanying work flow incorporates 16 core decision points that link antibody and assay specificity and sensitivity, and assay performance in preclinical and clinical samples, with stages of drug development. The matrix provides a means to ensure that relevant information on an IHC assay in development is recorded and communicated consistently and that minimum assay validation requirements are met. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Omics Approaches To Probe Microbiota and Drug Metabolism Interactions.

PubMed

Nichols, Robert G; Hume, Nicole E; Smith, Philip B; Peters, Jeffrey M; Patterson, Andrew D

2016-12-19

The drug metabolism field has long recognized the beneficial and sometimes deleterious influence of microbiota in the absorption, distribution, metabolism, and excretion of drugs. Early pioneering work with the sulfanilamide precursor prontosil pointed toward the necessity not only to better understand the metabolic capabilities of the microbiota but also, importantly, to identify the specific microbiota involved in the generation and metabolism of drugs. However, technological limitations important for cataloging the microbiota community as well as for understanding and/or predicting their metabolic capabilities hindered progress. Current advances including mass spectrometry-based metabolite profiling as well as culture-independent sequence-based identification and functional analysis of microbiota have begun to shed light on microbial metabolism. In this review, case studies will be presented to highlight key aspects (e.g., microbiota identification, metabolic function and prediction, metabolite identification, and profiling) that have helped to clarify how the microbiota might impact or be impacted by drug metabolism. Lastly, a perspective of the future of this field is presented that takes into account what important knowledge is lacking and how to tackle these problems.
Insights from investigating the interactions of adamantane-based drugs with the M2 proton channel from the H1N1 swine virus.

PubMed

Wang, Jing-Fang; Wei, Dong-Qing; Chou, Kuo-Chen

2009-10-16

The M2 proton channel is one of indispensable components for the influenza A virus that plays a vital role in its life cycle and hence is an important target for drug design against the virus. In view of this, the three-dimensional structure of the H1N1-M2 channel was developed based on the primary sequence taken from a patient recently infected by the H1N1 (swine flu) virus. With an explicit water-membrane environment, molecular docking studies were performed for amantadine and rimantadine, the two commercial drugs generally used to treat influenza A infection. It was found that their binding affinity to the H1N1-M2 channel is significantly lower than that to the H5N1-M2 channel, fully consistent with the recent report that the H1N1 swine virus was resistant to the two drugs. The findings and the relevant analysis reported here might provide useful structural insights for developing effective drugs against the new swine flu virus.
21 CFR 201.125 - Drugs for use in teaching, law enforcement, research, and analysis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 4 2011-04-01 2011-04-01 false Drugs for use in teaching, law enforcement, research, and analysis. 201.125 Section 201.125 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... § 201.125 Drugs for use in teaching, law enforcement, research, and analysis. A drug subject to § 201...

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