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.

2010 drug packaging review: identifying problems to prevent errors.

PubMed

2011-06-01

Prescrire's analyses showed that the quality of drug packaging in 2010 still left much to be desired. Potentially dangerous packaging remains a significant problem: unclear labelling is source of medication errors; dosing devices for some psychotropic drugs create a risk of overdose; child-proof caps are often lacking; and too many patient information leaflets are misleading or difficult to understand. Everything that is needed for safe drug packaging is available; it is now up to regulatory agencies and drug companies to act responsibly. In the meantime, health professionals can help their patients by learning to identify the pitfalls of drug packaging and providing safe information to help prevent medication errors.

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

Screening approach for identifying candidate drugs and drug-drug interactions related to hip fracture risk in persons with Alzheimer disease.

PubMed

Tolppanen, Anna-Maija; Taipale, Heidi; Koponen, Marjaana; Tanskanen, Antti; Lavikainen, Piia; Paananen, Jussi; Tiihonen, Jari; Hartikainen, Sirpa

2017-08-01

To assess whether a "drugome-wide" screen with case-crossover design is a feasible approach for identifying candidate drugs and drug-drug interactions. All community-dwelling residents of Finland who received a clinically verified Alzheimer disease diagnosis in 2005 to 2011 and experienced incident hip fracture (HF) afterwards (N = 4851). Three scenarios were used to test the sensitivity of this approach (1) hazard period 0 to 30 and control period 31 to 61 days before HF, (2) hazard period 0 to 30 and control period 336 to 366 days before HF, and (3) hazard period 0 to 14 and control period 16 to 30 days before HF. Nine, 44, and 5 drugs were associated with increased HF risk and 8, 23, and 4 with decreased risk in scenarios 1, 2, and 3, respectively. Six drugs were identified with scenario 1 only and 54 and 1 with scenarios 2 and 3, respectively. Only six drugs (metoprolol, simvastatin, trimethoprim, codeine combinations, fentanyl, and paracetamol) were associated with HF in all scenarios, four with 1 and 2 (cefalexin, buprenorphine, olanzapine, and memantine), and one with 1 and 3 (enalapril) or 2 and 3 (ciprofloxacin). The direction of associations was the same in all/both scenarios. The interaction results were equally versatile, with hydroxocobalamin*oxazepam being the only interaction observed in all scenarios. Case-crossover analysis is a potential approach for identifying candidate drugs and drug-drug interactions associated with adverse events as it implicitly controls for fixed confounders. The results are highly dependent on applied hazard and control periods, but the choice of periods can help in targeting the analyses to different phases of drug use. Copyright © 2017 John Wiley & Sons, Ltd.

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can

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

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

Chanumolu, Sree Krishna; Rout, Chittaranjan; Chauhan, Rajinder S

2012-01-01

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. UniDrug-Target is expected to accelerate

Consumer confusion between prescription drug precautions and side effects.

PubMed

Amoozegar, Jacqueline B; Rupert, Douglas J; Sullivan, Helen W; O'Donoghue, Amie C

2017-06-01

Multiple studies have identified consumers' difficulty correctly interpreting risk information provided about prescription drugs, whether in printed format or online. This study's purpose was to explore whether consumers can distinguish between prescription drug precautions and side effects presented on brand-name drug websites. Participants (n=873) viewed fictitious drug websites that presented both precautions and side effects for one of four drugs, and they completed a survey assessing recall and comprehension. We coded open-ended recall data to identify whether drug precautions were mentioned and, if so, how they were interpreted. Approximately 15% of participants mentioned at least one drug precaution. The majority (59.7%) misinterpreted precautions as potential side effects. Participants who misinterpreted precautions rated the drugs as significantly more likely to cause side effects than participants who accurately interpreted the precautions. Age, education, literacy, and other factors did not appear to predict precaution interpretation. At least some consumers are likely to interpret precautions on drug websites as potential side effects, which might affect consumer preferences, treatment decisions, and medication safety. Healthcare providers should be aware of this potential confusion, assess patients' understanding of precautions and potential side effects, and address any misunderstandings. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Identifying Demand Responses to Illegal Drug Supply Interdictions.

PubMed

Cunningham, Scott; Finlay, Keith

2016-10-01

Successful supply-side interdictions into illegal drug markets are predicated on the responsiveness of drug prices to enforcement and the price elasticity of demand for addictive drugs. We present causal estimates that targeted interventions aimed at methamphetamine input markets ('precursor control') can temporarily increase retail street prices, but methamphetamine consumption is weakly responsive to higher drug prices. After the supply interventions, purity-adjusted prices increased then quickly returned to pre-treatment levels within 6-12 months, demonstrating the short-term effects of precursor control. The price elasticity of methamphetamine demand is -0.13 to -0.21 for self-admitted drug treatment admissions and between -0.24 and -0.28 for hospital inpatient admissions. We find some evidence of a positive cross-price effect for cocaine, but we do not find robust evidence that increases in methamphetamine prices increased heroin, alcohol, or marijuana drug use. This study can inform policy discussions regarding other synthesized drugs, including illicit use of pharmaceuticals. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets.

PubMed

Miller, Martin L; Molinelli, Evan J; Nair, Jayasree S; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M; Singer, Samuel; Schwartz, Gary K; Sander, Chris

2013-09-24

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depends on the activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies.

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

How to Identify Drug Paraphernalia

MedlinePlus

... red eyes, changes in pupil size, or eye movements Items or associations that may indicate interest in illegal drugs or drug use. Clothing, jewelry, tattoos, teen slang with drug culture messages. Websites, music, or publications that glamorize drug use. Where do ...

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…

Drug Repositioning for Effective Prostate Cancer Treatment.

PubMed

Turanli, Beste; Grøtli, Morten; Boren, Jan; Nielsen, Jens; Uhlen, Mathias; Arga, Kazim Y; Mardinoglu, Adil

2018-01-01

Drug repositioning has gained attention from both academia and pharmaceutical companies as an auxiliary process to conventional drug discovery. Chemotherapeutic agents have notorious adverse effects that drastically reduce the life quality of cancer patients so drug repositioning is a promising strategy to identify non-cancer drugs which have anti-cancer activity as well as tolerable adverse effects for human health. There are various strategies for discovery and validation of repurposed drugs. In this review, 25 repurposed drug candidates are presented as result of different strategies, 15 of which are already under clinical investigation for treatment of prostate cancer (PCa). To date, zoledronic acid is the only repurposed, clinically used, and approved non-cancer drug for PCa. Anti-cancer activities of existing drugs presented in this review cover diverse and also known mechanisms such as inhibition of mTOR and VEGFR2 signaling, inhibition of PI3K/Akt signaling, COX and selective COX-2 inhibition, NF-κB inhibition, Wnt/β-Catenin pathway inhibition, DNMT1 inhibition, and GSK-3β inhibition. In addition to monotherapy option, combination therapy with current anti-cancer drugs may also increase drug efficacy and reduce adverse effects. Thus, drug repositioning may become a key approach for drug discovery in terms of time- and cost-efficiency comparing to conventional drug discovery and development process.

ICD-10 codes used to identify adverse drug events in administrative data: a systematic review.

PubMed

Hohl, Corinne M; Karpov, Andrei; Reddekopp, Lisa; Doyle-Waters, Mimi; Stausberg, Jürgen

2014-01-01

Adverse drug events, the unintended and harmful effects of medications, are important outcome measures in health services research. Yet no universally accepted set of International Classification of Diseases (ICD) revision 10 codes or coding algorithms exists to ensure their consistent identification in administrative data. Our objective was to synthesize a comprehensive set of ICD-10 codes used to identify adverse drug events. We developed a systematic search strategy and applied it to five electronic reference databases. We searched relevant medical journals, conference proceedings, electronic grey literature and bibliographies of relevant studies, and contacted content experts for unpublished studies. One author reviewed the titles and abstracts for inclusion and exclusion criteria. Two authors reviewed eligible full-text articles and abstracted data in duplicate. Data were synthesized in a qualitative manner. Of 4241 titles identified, 41 were included. We found a total of 827 ICD-10 codes that have been used in the medical literature to identify adverse drug events. The median number of codes used to search for adverse drug events was 190 (IQR 156-289) with a large degree of variability between studies in the numbers and types of codes used. Authors commonly used external injury (Y40.0-59.9) and disease manifestation codes. Only two papers reported on the sensitivity of their code set. Substantial variability exists in the methods used to identify adverse drug events in administrative data. Our work may serve as a point of reference for future research and consensus building in this area.

ICD-10 codes used to identify adverse drug events in administrative data: a systematic review

PubMed Central

Hohl, Corinne M; Karpov, Andrei; Reddekopp, Lisa; Stausberg, Jürgen

2014-01-01

Background Adverse drug events, the unintended and harmful effects of medications, are important outcome measures in health services research. Yet no universally accepted set of International Classification of Diseases (ICD) revision 10 codes or coding algorithms exists to ensure their consistent identification in administrative data. Our objective was to synthesize a comprehensive set of ICD-10 codes used to identify adverse drug events. Methods We developed a systematic search strategy and applied it to five electronic reference databases. We searched relevant medical journals, conference proceedings, electronic grey literature and bibliographies of relevant studies, and contacted content experts for unpublished studies. One author reviewed the titles and abstracts for inclusion and exclusion criteria. Two authors reviewed eligible full-text articles and abstracted data in duplicate. Data were synthesized in a qualitative manner. Results Of 4241 titles identified, 41 were included. We found a total of 827 ICD-10 codes that have been used in the medical literature to identify adverse drug events. The median number of codes used to search for adverse drug events was 190 (IQR 156–289) with a large degree of variability between studies in the numbers and types of codes used. Authors commonly used external injury (Y40.0–59.9) and disease manifestation codes. Only two papers reported on the sensitivity of their code set. Conclusions Substantial variability exists in the methods used to identify adverse drug events in administrative data. Our work may serve as a point of reference for future research and consensus building in this area. PMID:24222671

Drug Synergy Screen and Network Modeling in Dedifferentiated Liposarcoma Identifies CDK4 and IGF1R as Synergistic Drug Targets

PubMed Central

Miller, Martin L.; Molinelli, Evan J.; Nair, Jayasree S.; Sheikh, Tahir; Samy, Rita; Jing, Xiaohong; He, Qin; Korkut, Anil; Crago, Aimee M.; Singer, Samuel; Schwartz, Gary K.; Sander, Chris

2014-01-01

Dedifferentiated liposarcoma (DDLS) is a rare but aggressive cancer with high recurrence and low response rates to targeted therapies. Increasing treatment efficacy may require combinations of targeted agents that counteract the effects of multiple abnormalities. To identify a possible multicomponent therapy, we performed a combinatorial drug screen in a DDLS-derived cell line and identified cyclin-dependent kinase 4 (CDK4) and insulin-like growth factor 1 receptor (IGF1R) as synergistic drug targets. We measured the phosphorylation of multiple proteins and cell viability in response to systematic drug combinations and derived computational models of the signaling network. These models predict that the observed synergy in reducing cell viability with CDK4 and IGF1R inhibitors depend on activity of the AKT pathway. Experiments confirmed that combined inhibition of CDK4 and IGF1R cooperatively suppresses the activation of proteins within the AKT pathway. Consistent with these findings, synergistic reductions in cell viability were also found when combining CDK4 inhibition with inhibition of either AKT or epidermal growth factor receptor (EGFR), another receptor similar to IGF1R that activates AKT. Thus, network models derived from context-specific proteomic measurements of systematically perturbed cancer cells may reveal cancer-specific signaling mechanisms and aid in the design of effective combination therapies. PMID:24065146

Unifying Theories of Psychedelic Drug Effects

PubMed Central

Swanson, Link R.

2018-01-01

How do psychedelic drugs produce their characteristic range of acute effects in perception, emotion, cognition, and sense of self? How do these effects relate to the clinical efficacy of psychedelic-assisted therapies? Efforts to understand psychedelic phenomena date back more than a century in Western science. In this article I review theories of psychedelic drug effects and highlight key concepts which have endured over the last 125 years of psychedelic science. First, I describe the subjective phenomenology of acute psychedelic effects using the best available data. Next, I review late 19th-century and early 20th-century theories—model psychoses theory, filtration theory, and psychoanalytic theory—and highlight their shared features. I then briefly review recent findings on the neuropharmacology and neurophysiology of psychedelic drugs in humans. Finally, I describe recent theories of psychedelic drug effects which leverage 21st-century cognitive neuroscience frameworks—entropic brain theory, integrated information theory, and predictive processing—and point out key shared features that link back to earlier theories. I identify an abstract principle which cuts across many theories past and present: psychedelic drugs perturb universal brain processes that normally serve to constrain neural systems central to perception, emotion, cognition, and sense of self. I conclude that making an explicit effort to investigate the principles and mechanisms of psychedelic drug effects is a uniquely powerful way to iteratively develop and test unifying theories of brain function. PMID:29568270

Using Functional Signatures to Identify Repositioned Drugs for Breast, Myelogenous Leukemia and Prostate Cancer

PubMed Central

Shigemizu, Daichi; Hu, Zhenjun; Hung, Jui-Hung; Huang, Chia-Ling; Wang, Yajie; DeLisi, Charles

2012-01-01

The cost and time to develop a drug continues to be a major barrier to widespread distribution of medication. Although the genomic revolution appears to have had little impact on this problem, and might even have exacerbated it because of the flood of additional and usually ineffective leads, the emergence of high throughput resources promises the possibility of rapid, reliable and systematic identification of approved drugs for originally unintended uses. In this paper we develop and apply a method for identifying such repositioned drug candidates against breast cancer, myelogenous leukemia and prostate cancer by looking for inverse correlations between the most perturbed gene expression levels in human cancer tissue and the most perturbed expression levels induced by bioactive compounds. The method uses variable gene signatures to identify bioactive compounds that modulate a given disease. This is in contrast to previous methods that use small and fixed signatures. This strategy is based on the observation that diseases stem from failed/modified cellular functions, irrespective of the particular genes that contribute to the function, i.e., this strategy targets the functional signatures for a given cancer. This function-based strategy broadens the search space for the effective drugs with an impressive hit rate. Among the 79, 94 and 88 candidate drugs for breast cancer, myelogenous leukemia and prostate cancer, 32%, 13% and 17% respectively are either FDA-approved/in-clinical-trial drugs, or drugs with suggestive literature evidences, with an FDR of 0.01. These findings indicate that the method presented here could lead to a substantial increase in efficiency in drug discovery and development, and has potential application for the personalized medicine. PMID:22346740

Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

PubMed

San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

2014-12-01

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

A proteomic approach to identifying new drug targets (potentiating topoisomerase II poisons).

PubMed

Jenkins, J R

2008-10-01

Topoisomerase II poisons are an established part of best clinical practice for the treatment of a number of solid tumours and haematological malignancies. However, toxicity and resistance to chemotherapeutic drugs often complicate the treatment. Furthermore, topoisomerase II poisons can also induce sister chromatid exchange, chromosomal recombination and chromosome aberrations and are associated with a significant risk of secondary leukaemia. It would therefore be of great clinical benefit if the efficacy of topoisomerase II inhibitors could be enhanced without the increased toxic side effects. It is proposed that clinical agents targeting topoisomerase II can be enhanced by inhibiting proteins that modulate topoisomerase II. The aim is to identify proteins, that by the nature of their interaction with topoisomerase II, represent putative drug targets.

Corifungin, a New Drug Lead against Naegleria, Identified from a High-Throughput Screen

PubMed Central

Debnath, Anjan; Tunac, Josefino B.; Galindo-Gómez, Silvia; Silva-Olivares, Angélica; Shibayama, Mineko

2012-01-01

Primary amebic meningoencephalitis (PAM) is a rapidly fatal infection caused by the free-living ameba Naegleria fowleri. The drug of choice in treating PAM is the antifungal antibiotic amphotericin B, but its use is associated with severe adverse effects. Moreover, few patients treated with amphotericin B have survived PAM. Therefore, fast-acting and efficient drugs are urgently needed for the treatment of PAM. To facilitate drug screening for this pathogen, an automated, high-throughput screening methodology was developed and validated for the closely related species Naegleria gruberi. Five kinase inhibitors and an NF-kappaB inhibitor were hits identified in primary screens of three compound libraries. Most importantly for a preclinical drug discovery pipeline, we identified corifungin, a water-soluble polyene macrolide with a higher activity against Naegleria than that of amphotericin B. Transmission electron microscopy of N. fowleri trophozoites incubated with different concentrations of corifungin showed disruption of cytoplasmic and plasma membranes and alterations in mitochondria, followed by complete lysis of amebae. In vivo efficacy of corifungin in a mouse model of PAM was confirmed by an absence of detectable amebae in the brain and 100% survival of mice for 17 days postinfection for a single daily intraperitoneal dose of 9 mg/kg of body weight given for 10 days. The same dose of amphotericin B did not reduce ameba growth, and mouse survival was compromised. Based on these results, the U.S. FDA has approved orphan drug status for corifungin for the treatment of PAM. PMID:22869574

Drug side effect extraction from clinical narratives of psychiatry and psychology patients

PubMed Central

Kocher, Jean-Pierre A; Chute, Christopher G; Savova, Guergana K

2011-01-01

Objective To extract physician-asserted drug side effects from electronic medical record clinical narratives. Materials and methods Pattern matching rules were manually developed through examining keywords and expression patterns of side effects to discover an individual side effect and causative drug relationship. A combination of machine learning (C4.5) using side effect keyword features and pattern matching rules was used to extract sentences that contain side effect and causative drug pairs, enabling the system to discover most side effect occurrences. Our system was implemented as a module within the clinical Text Analysis and Knowledge Extraction System. Results The system was tested in the domain of psychiatry and psychology. The rule-based system extracting side effects and causative drugs produced an F score of 0.80 (0.55 excluding allergy section). The hybrid system identifying side effect sentences had an F score of 0.75 (0.56 excluding allergy section) but covered more side effect and causative drug pairs than individual side effect extraction. Discussion The rule-based system was able to identify most side effects expressed by clear indication words. More sophisticated semantic processing is required to handle complex side effect descriptions in the narrative. We demonstrated that our system can be trained to identify sentences with complex side effect descriptions that can be submitted to a human expert for further abstraction. Conclusion Our system was able to extract most physician-asserted drug side effects. It can be used in either an automated mode for side effect extraction or semi-automated mode to identify side effect sentences that can significantly simplify abstraction by a human expert. PMID:21946242

Prescription drug coverage and effects on drug expenditures among elderly Medicare beneficiaries.

PubMed

Huh, Soonim; Rice, Thomas; Ettner, Susan L

2008-06-01

To identify determinants of drug coverage among elderly Medicare beneficiaries and to investigate the impact of drug coverage on drug expenditures with and without taking selection bias into account. The primary data were from the 2000 Medicare Current Beneficiary Survey (MCBS) Cost and Use file, linked to other data sources at the county or state-level that provided instrumental variables. Community-dwelling elderly Medicare beneficiaries who completed the survey were included in the study (N=7,525). A probit regression to predict the probability of having drug coverage and the effects of drug coverage on drug expenditures was estimated by a two-part model, assuming no correlation across equations. In addition, the discrete factor model estimated choice of drug coverage and expenditures for prescription drugs simultaneously to control for self-selection into drug coverage, allowing for correlation of error terms across equations. Findings indicated that unobservable characteristics leading elderly Medicare beneficiaries to purchase drug coverage also lead them to have higher drug expenditures on conditional use (i.e., adverse selection), while the same unobservable factors do not influence their decisions whether to use any drugs. After controlling for potential selection bias, the probability of any drug use among persons with drug coverage use was 4.5 percent higher than among those without, and drug coverage led to an increase in drug expenditures of $308 among those who used prescription drugs. Given significant adverse selection into drug coverage before the implementation of the Medicare Prescription Drug Improvement and Modernization Act, it is essential that selection effects be monitored as beneficiaries choose whether or not to enroll in this voluntary program.

Application of the Pareto principle to identify and address drug-therapy safety issues.

PubMed

Müller, Fabian; Dormann, Harald; Pfistermeister, Barbara; Sonst, Anja; Patapovas, Andrius; Vogler, Renate; Hartmann, Nina; Plank-Kiegele, Bettina; Kirchner, Melanie; Bürkle, Thomas; Maas, Renke

2014-06-01

Adverse drug events (ADE) and medication errors (ME) are common causes of morbidity in patients presenting at emergency departments (ED). Recognition of ADE as being drug related and prevention of ME are key to enhancing pharmacotherapy safety in ED. We assessed the applicability of the Pareto principle (~80 % of effects result from 20 % of causes) to address locally relevant problems of drug therapy. In 752 cases consecutively admitted to the nontraumatic ED of a major regional hospital, ADE, ME, contributing drugs, preventability, and detection rates of ADE by ED staff were investigated. Symptoms, errors, and drugs were sorted by frequency in order to apply the Pareto principle. In total, 242 ADE were observed, and 148 (61.2 %) were assessed as preventable. ADE contributed to 110 inpatient hospitalizations. The ten most frequent symptoms were causally involved in 88 (80.0 %) inpatient hospitalizations. Only 45 (18.6 %) ADE were recognized as drug-related problems until discharge from the ED. A limited set of 33 drugs accounted for 184 (76.0 %) ADE; ME contributed to 57 ADE. Frequency-based listing of ADE, ME, and drugs involved allowed identification of the most relevant problems and development of easily to implement safety measures, such as wall and pocket charts. The Pareto principle provides a method for identifying the locally most relevant ADE, ME, and involved drugs. This permits subsequent development of interventions to increase patient safety in the ED admission process that best suit local needs.

Heat effects on drug delivery across human skin

PubMed Central

Hao, Jinsong; Ghosh, Priyanka; Li, S. Kevin; Newman, Bryan; Kasting, Gerald B.; Raney, Sam G.

2016-01-01

Introduction Exposure to heat can impact the clinical efficacy and/or safety of transdermal and topical drug products. Understanding these heat effects and designing meaningful in vitro and in vivo methods to study them are of significant value to the development and evaluation of drug products dosed to the skin. Areas covered This review provides an overview of the underlying mechanisms and the observed effects of heat on the skin and on transdermal/topical drug delivery, thermoregulation and heat tolerability. The designs of several in vitro and in vivo heat effect studies and their results are reviewed. Expert opinion There is substantial evidence that elevated temperature can increase transdermal/topical drug delivery. However, in vitro and in vivo methods reported in the literature to study heat effects of transdermal/topical drug products have utilized inconsistent study conditions, and in vitro models require better characterization. Appropriate study designs and controls remain to be identified, and further research is warranted to evaluate in vitro-in vivo correlations and the ability of in vitro models to predict in vivo effects. The physicochemical and pharmacological properties of the drug(s) and the drug product, as well as dermal clearance and heat gradients may require careful consideration. PMID:26808472

Systematic identification of proteins that elicit drug side effects

PubMed Central

Kuhn, Michael; Al Banchaabouchi, Mumna; Campillos, Monica; Jensen, Lars Juhl; Gross, Cornelius; Gavin, Anne-Claude; Bork, Peer

2013-01-01

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug–target relations to identify overrepresented protein–side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations. PMID:23632385

Identifying types of drug intoxication : laboratory evaluation of a subject-examination procedure

DOT National Transportation Integrated Search

1985-05-01

The Los Angeles Police Department (LAPD) has developed a rating procedures for use in detecting drug-impaired drivers. The purpose of the rating procedures is to determine whether the driver is impaired and to identify the responsible drug class (e.g...

Effect of colour of drugs: systematic review of perceived effect of drugs and of their effectiveness.

PubMed

de Craen, A J; Roos, P J; de Vries, A L; Kleijnen, J

To assess the impact of the colour of a drug's formulation on its perceived effect and its effectiveness and to examine whether antidepressant drugs available in the Netherlands are different in colour from hypnotic, sedative, and anxiolytic drugs. Systematic review of 12 published studies. Six studies examined the perceived action of different coloured drugs and six the influence of the colour of a drug on its effectiveness. The colours of samples of 49 drugs affecting the central nervous system were assessed using a colour atlas. Perceived stimulant action versus perceived depressant action of colour of drugs; the trials that assessed the effect of drugs in different colours were done in patients with different diseases and had different outcome measures. The studies on perceived action of coloured drugs showed that red, yellow, and orange are associated with a stimulant effect, while blue and green are related to a tranquillising effect. The trials that assessed the impact of the colour of drugs on their effectiveness showed inconsistent differences between colours. The quality of the methods of these trials was variable. Hypnotic, sedative, and anxiolytic drugs were more likely than antidepressants to be green, blue, or purple. Colours affect the perceived action of a drug and seem to influence the effectiveness of a drug. Moreover, a relation exists between the colouring of drugs that affect the central nervous system and the indications for which they are used. Research contributing to a better understanding of the effect of the colour of drugs is warranted.

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

History as a tool in identifying "new" old drugs.

PubMed

Riddle, John M

2002-01-01

To trace the history of a natural product and its use, it is necessary to identify to correct plant among around a half-million species. One must also know how and when harvest the plant and the morphology of location and extraction. Within the same species plant chemistry varies, depending upon climatic and soil conditions, stage of maturity and even diurnal factors. To all of these variations must be added the diagnostic ability of physicians and native healers (to distinguish between Hippocratically-trained Western physicians and whose knowledge is less formally taught). Seldom was a disease identified as we Know it today, but the constellations of symptoms described, when studied carefully within the framework historical setting of the culture, can be related to modern medicine. It is essential to study the historical contemporary usage data in the language in which those accounts were writTen. Translators are often philologists who are not sensitive to medical nuances. Modern readers of translated historical documents often are unaware of the precision the authors delivered in describing medical afflictions and their treatments. Natural product drugs are truly products of human knowledge. Because so many modern pharmaceuticals are manufactured synthetically we forget that once either the compound or its affinity had a home in a natural product. Over 2,500 years ago man first used a drug obtained from white willow bark, which was aspirin or acetylsalicylic acid. Today's scientists continue to be bewildered by just what aspirin's mechanisms of action are, discovering new modes of action, and how they relate to medical diagnostics. Whatever the science of aspirin, an intelligent person today takes it just as our ancestors did fo millennia. Throughout time, explanations continue to vary just as purpose of administration do as well. Nevertheless, aspirin is perceived as being beneficial. Historical in-use data can also be a factor in judging a drug's safety, since

Predict drug permeability to blood–brain-barrier from clinical phenotypes: drug side effects and drug indications

PubMed Central

Gao, Zhen; Chen, Yang; Cai, Xiaoshu; Xu, Rong

2017-01-01

Abstract Motivation: Blood–Brain-Barrier (BBB) is a rigorous permeability barrier for maintaining homeostasis of Central Nervous System (CNS). Determination of compound’s permeability to BBB is prerequisite in CNS drug discovery. Existing computational methods usually predict drug BBB permeability from chemical structure and they generally apply to small compounds passing BBB through passive diffusion. As abundant information on drug side effects and indications has been recorded over time through extensive clinical usage, we aim to explore BBB permeability prediction from a new angle and introduce a novel approach to predict BBB permeability from drug clinical phenotypes (drug side effects and drug indications). This method can apply to both small compounds and macro-molecules penetrating BBB through various mechanisms besides passive diffusion. Results: We composed a training dataset of 213 drugs with known brain and blood steady-state concentrations ratio and extracted their side effects and indications as features. Next, we trained SVM models with polynomial kernel and obtained accuracy of 76.0%, AUC 0.739, and F1 score (macro weighted) 0.760 with Monte Carlo cross validation. The independent test accuracy was 68.3%, AUC 0.692, F1 score 0.676. When both chemical features and clinical phenotypes were available, combining the two types of features achieved significantly better performance than chemical feature based approach (accuracy 85.5% versus 72.9%, AUC 0.854 versus 0.733, F1 score 0.854 versus 0.725; P < e−90). We also conducted de novo prediction and identified 110 drugs in SIDER database having the potential to penetrate BBB, which could serve as start point for CNS drug repositioning research. Availability and Implementation: https://github.com/bioinformatics-gao/CASE-BBB-prediction-Data Contact: rxx@case.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27993785

Influence of drug colour on perceived drug effects and efficacy.

PubMed

Tao, Da; Wang, Tieyan; Wang, Tieshan; Qu, Xingda

2018-02-01

A drug's physical characteristics, such as colour, could be factors influencing its therapeutic effects. It is not well understood whether people's expectations on drug effects and efficacy are affected by colour, especially among Chinese population. This study was conducted to examine people's expectations on drug effects and efficacy on the basis of drug colour, and to reveal possible gender differences in colour-related drug expectations. Participants (n = 224) were asked to classify seven single-coloured and six two-coloured capsules into one of four categories of drug effects, and to indicate the strength of drug efficacy. It is found that all the coloured capsules yielded non-chance distributions in classifications of drug effects, with six single-coloured and four two-coloured capsules associated with specific drug effects. Colour also conveyed differential strengths of drug efficacy in general and in relation to specific drug effects. There were gender differences in drug expectations for some colours and colour combinations. Practitioner Summary: Drug colour was found to have impacts on perceived drug effects and efficacy. The findings from the present study can be used by ergonomics practitioners to design appropriate drug colours in support of drug differentiation, therapeutic effects and medication adherence.

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness.

PubMed

Boyce, Richard D; Horn, John R; Hassanzadeh, Oktie; Waard, Anita de; Schneider, Jodi; Luciano, Joanne S; Rastegar-Mojarad, Majid; Liakata, Maria

2013-01-26

Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug's efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File - Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug

Identifying genomic and developmental causes of adverse drug reactions in children

PubMed Central

Becker, Mara L; Leeder, J Steven

2011-01-01

Adverse drug reactions are a concern for all clinicians who utilize medications to treat adults and children; however, the frequency of adult and pediatric adverse drug reactions is likely to be under-reported. In this age of genomics and personalized medicine, identifying genetic variation that results in differences in drug biotransformation and response has contributed to significant advances in the utilization of several commonly used medications in adults. In order to better understand the variability of drug response in children however, we must not only consider differences in genotype, but also variation in gene expression during growth and development, namely ontogeny. In this article, recommendations for systematically approaching pharmacogenomic studies in children are discussed, and several examples of studies that investigate the genomic and developmental contribution to adverse drug reactions in children are reviewed. PMID:21121777

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

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness

PubMed Central

2013-01-01

Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug’s efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File – Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

PubMed

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-12-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

Exploring the associations between drug side-effects and therapeutic indications.

PubMed

Wang, Fei; Zhang, Ping; Cao, Nan; Hu, Jianying; Sorrentino, Robert

2014-10-01

Drug therapeutic indications and side-effects are both measurable patient phenotype changes in response to the treatment. Inferring potential drug therapeutic indications and identifying clinically interesting drug side-effects are both important and challenging tasks. Previous studies have utilized either chemical structures or protein targets to predict indications and side-effects. In this study, we compared drug therapeutic indication prediction using various information including chemical structures, protein targets and side-effects. We also compared drug side-effect prediction with various information sources including chemical structures, protein targets and therapeutic indication. Prediction performance based on 10-fold cross-validation demonstrates that drug side-effects and therapeutic indications are the most predictive information source for each other. In addition, we extracted 6706 statistically significant indication-side-effect associations from all known drug-disease and drug-side-effect relationships. We further developed a novel user interface that allows the user to interactively explore these associations in the form of a dynamic bipartitie graph. Many relationship pairs provide explicit repositioning hypotheses (e.g., drugs causing postural hypotension are potential candidates for hypertension) and clear adverse-reaction watch lists (e.g., drugs for heart failure possibly cause impotence). All data sets and highly correlated disease-side-effect relationships are available at http://astro.temple.edu/∼tua87106/druganalysis.html. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Pyrimethamine as a Potent and Selective Inhibitor of Acute Myeloid Leukemia Identified by High-throughput Drug Screening.

PubMed

Sharma, Amit; Jyotsana, Nidhi; Lai, Courteney K; Chaturvedi, Anuhar; Gabdoulline, Razif; Görlich, Kerstin; Murphy, Cecilia; Blanchard, Jan E; Ganser, Arnold; Brown, Eric; Hassell, John A; Humphries, R Keith; Morgan, Michael; Heuser, Michael

2016-01-01

Hematopoietic stem and progenitor cell differentiation are blocked in acute myeloid leukemia (AML) resulting in cytopenias and a high risk of death. Most patients with AML become resistant to treatment due to lack of effective cytotoxic and differentiation promoting compounds. High MN1 expression confers poor prognosis to AML patients and induces resistance to cytarabine and alltrans-retinoic acid (ATRA) induced differentiation. Using a high-throughput drug screening, we identified the dihydrofolate reductase (DHFR) antagonist pyrimethamine to be a potent inducer of apoptosis and differentiation in several murine and human leukemia cell lines. Oral pyrimethamine treatment was effective in two xenograft mouse models and specifically targeted leukemic cells in human AML cell lines and primary patient cells, while CD34+ cells from healthy donors were unaffected. The antileukemic effects of PMT could be partially rescued by excess folic acid, suggesting an oncogenic function of folate metabolism in AML. Thus, our study identifies pyrimethamine as a candidate drug that should be further evaluated in AML treatment.

Identifying the translational gap in the evaluation of drug-induced QTc interval prolongation

PubMed Central

Chain, Anne SY; Dubois, Vincent FS; Danhof, Meindert; Sturkenboom, Miriam CJM; Della Pasqua, Oscar

2013-01-01

Aims Given the similarities in QTc response between dogs and humans, dogs are used in pre-clinical cardiovascular safety studies. The objective of our investigation was to characterize the PKPD relationships and identify translational gaps across species following the administration of three compounds known to cause QTc interval prolongation, namely cisapride, d, l-sotalol and moxifloxacin. Methods Pharmacokinetic and pharmacodynamic data from experiments in conscious dogs and clinical trials were included in this analysis. First, pharmacokinetic modelling and deconvolution methods were applied to derive drug concentrations at the time of each QT measurement. A Bayesian PKPD model was then used to describe QT prolongation, allowing discrimination of drug-specific effects from other physiological factors known to alter QT interval duration. A threshold of ≥10 ms was used to explore the probability of prolongation after drug administration. Results A linear relationship was found to best describe the pro-arrhythmic effects of cisapride, d,l-sotalol and moxifloxacin both in dogs and in humans. The drug-specific parameter (slope) in dogs was statistically significantly different from humans. Despite such differences, our results show that the probability of QTc prolongation ≥10 ms in dogs nears 100% for all three compounds at the therapeutic exposure range in humans. Conclusions Our findings indicate that the slope of PKPD relationship in conscious dogs may be used as the basis for the prediction of drug-induced QTc prolongation in humans. Furthermore, the risk of QTc prolongation can be expressed in terms of the probability associated with an increase ≥10 ms, allowing direct inferences about the clinical relevance of the pro-arrhythmic potential of a molecule. PMID:23351036

Walking on thin ice! Identifying methamphetamine "drug mules" on digital plain radiography.

PubMed

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J; Flach, P M

2014-04-01

The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in "drug mules" by plain abdominal digital radiography (DR). The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all "drug mules" and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. There were 16 true-positive "drug mules" identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA "drug mules", although DR is associated with high diagnostic insecurity and underreports the total internal payload.

Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets.

PubMed

Vashisht, Rohit; Bhat, Ashwini G; Kushwaha, Shreeram; Bhardwaj, Anshu; Brahmachari, Samir K

2014-10-11

The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis (Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to a lack of systems level understanding that can innovate the process of fast acting and high efficacy drug discovery. The enhanced functional annotations of the Mtb genome, which were previously obtained through a crowd sourcing approach was used to reconstruct the metabolic network of Mtb in a bottom up manner. We represent this information by developing a novel Systems Biology Spindle Map of Metabolism (SBSM) and comprehend its static and dynamic structure using various computational approaches based on simulation and design. The reconstructed metabolism of Mtb encompasses 961 metabolites, involved in 1152 reactions catalyzed by 890 protein coding genes, organized into 50 pathways. By accounting for static and dynamic analysis of SBSM in Mtb we identified various critical proteins required for the growth and survival of bacteria. Further, we assessed the potential of these proteins as putative drug targets that are fast acting and less toxic. Further, we formulate a novel concept of metabolic persister genes (MPGs) and compared our predictions with published in vitro and in vivo experimental evidence. Through such analyses, we report for the first time that de novo biosynthesis of NAD may give rise to bacterial persistence in Mtb under conditions of metabolic stress induced by conventional anti-tuberculosis therapy. We propose such MPG's as potential combination of drug targets for existing antibiotics that can improve their efficacy and efficiency for drug tolerant bacteria. The systems level framework formulated by us to identify potential non-toxic drug targets and strategies to circumvent the issue of bacterial persistence can substantially aid in the process of TB drug

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post- chemotherapy tissues

PubMed Central

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-01-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens. PMID:26515599

A new method to assess Pavlovian conditioning of psychostimulant drug effects.

PubMed

Damianopoulos, E N; Carey, R J

1994-07-01

Experimental studies of psychoactive drugs by pavlovian drug-conditioning methods, which originally began with investigations of drug-induced responses mediated by the autonomic nervous system, have now been expanded to include drug-induced response effects expressed as modulations of spontaneous motoric behaviors. In the latter application, however, equivalent behavioral response outcomes in post-treatment tests for conditioning can occur following a psychostimulant drug treatment either through drug interference effects on habituation processes, drug-induced stress effects and/or by pavlovian conditioning of the drug-induced motoric activation effect. Current methodologies for the study of pavlovian conditioned drug effects and/or drug sensitization cannot distinguish among these possibilities. This methodological inadequacy was addressed by a modification of the conventional paired-unpaired treatment protocol. In the new protocol, the animal is sequentially placed into two test compartments with the drug treatment administered in conjunction with placement into the second test compartment. This design permits a differentiation of a pavlovian conditioned drug responses from non-conditioned drug effects through continuous measurement of the non-drug behavioral baseline in both the drug and non-drug control treatment groups combined with multiple response measurements and post-treatment tests for conditioning at variable post-conditioning intervals. The present study details the use of the new modified pavlovian protocol with repeated cocaine (10 mg/kg) treatment. A cocaine conditioned response at 1, 7, and 21 days post-conditioning was identified and distinguished from habituation and stress effects.

A systematic review of cost-effectiveness analyses of drugs for postmenopausal osteoporosis.

PubMed

Hiligsmann, Mickaël; Evers, Silvia M; Ben Sedrine, Wafa; Kanis, John A; Ramaekers, Bram; Reginster, Jean-Yves; Silverman, Stuart; Wyers, Caroline E; Boonen, Annelies

2015-03-01

Given the limited availability of healthcare resources and the recent introduction of new anti-osteoporosis drugs, the interest in the cost effectiveness of drugs in postmenopausal osteoporosis remains and even increases. This study aims to identify all recent economic evaluations on drugs for postmenopausal osteoporosis, to critically appraise the reporting quality, and to summarize the results. A literature search using Medline, the National Health Service Economic Evaluation database and the Cost-Effectiveness Analysis Registry was undertaken to identify original articles published between January 1, 2008 and December 31, 2013. Studies that assessed cost effectiveness of drugs in postmenopausal osteoporosis were included. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement was used to assess the quality of reporting of these articles. Of 1,794 articles identified, 39 studies fulfilled the inclusion criteria. They were conducted in 14 different countries and nine active interventions were assessed. When compared with no treatment, active osteoporotic drugs were generally cost effective in postmenopausal women aged over 60-65 years with low bone mass, especially those with prior vertebral fractures. Key drivers of cost effectiveness included individual fracture risk, medication adherence, selected comparators and country-specific analyses. Quality of reporting varied between studies with an average score of 17.9 out of 24 (range 7-21.5). This review found a substantial number of published cost-effectiveness analyses of drugs in osteoporosis in the last 6 years. Results and critical appraisal of these articles can help decision makers when prioritizing health interventions and can inform the development of future economic evaluations.

Principles that underpin effective school-based drug education.

PubMed

Midford, Richard; Munro, Geoffrey; McBride, Nyanda; Snow, Pamela; Ladzinski, Ursula

2002-01-01

This study identifies the conceptual underpinnings of effective school-based drug education practice in light of contemporary research evidence and the practical experience of a broad range of drug education stakeholders. The research involved a review of the literature, a national survey of 210 Australian teachers and others involved in drug education, and structured interviews with 22 key Australian drug education policy stakeholders. The findings from this research have been distilled and presented as a list of 16 principles that underpin effective drug education. In broad terms, drug education should be evidence-based, developmentally appropriate, sequential, and contextual. Programs should be initiated before drug use commences. Strategies should be linked to goals and should incorporate harm minimization. Teaching should be interactive and use peer leaders. The role of the classroom teacher is central. Certain program content is important, as is social and resistance skills training. Community values, the social context of use, and the nature of drug harm have to be addressed. Coverage needs to be adequate and supported by follow-up. It is envisaged that these principles will provide all those involved in the drug education field with a set of up-to-date, research-based guidelines against which to reference decisions on program design, selection, implementation, and evaluation.

A novel in vitro image-based assay identifies new drug leads for giardiasis.

PubMed

Hart, Christopher J S; Munro, Taylah; Andrews, Katherine T; Ryan, John H; Riches, Andrew G; Skinner-Adams, Tina S

2017-04-01

Giardia duodenalis is an intestinal parasite that causes giardiasis, a widespread human gastrointestinal disease. Treatment of giardiasis relies on a small arsenal of compounds that can suffer from limitations including side-effects, variable treatment efficacy and parasite drug resistance. Thus new anti-Giardia drug leads are required. The search for new compounds with anti-Giardia activity currently depends on assays that can be labour-intensive, expensive and restricted to measuring activity at a single time-point. Here we describe a new in vitro assay to assess anti-Giardia activity. This image-based assay utilizes the Perkin-Elmer Operetta ® and permits automated assessment of parasite growth at multiple time points without cell-staining. Using this new approach, we assessed the "Malaria Box" compound set for anti-Giardia activity. Three compounds with sub-μM activity (IC 50 0.6-0.9 μM) were identified as potential starting points for giardiasis drug discovery. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Three-Dimensional Cell Culture-Based Screening Identifies the Anthelmintic Drug Nitazoxanide as a Candidate for Treatment of Colorectal Cancer.

PubMed

Senkowski, Wojciech; Zhang, Xiaonan; Olofsson, Maria Hägg; Isacson, Ruben; Höglund, Urban; Gustafsson, Mats; Nygren, Peter; Linder, Stig; Larsson, Rolf; Fryknäs, Mårten

2015-06-01

Because dormant cancer cells in hypoxic and nutrient-deprived regions of solid tumors provide a major obstacle to treatment, compounds targeting those cells might have clinical benefits. Here, we describe a high-throughput drug screening approach, using glucose-deprived multicellular tumor spheroids (MCTS) with inner hypoxia, to identify compounds that specifically target this cell population. We used a concept of drug repositioning-using known molecules for new indications. This is a promising strategy to identify molecules for rapid clinical advancement. By screening 1,600 compounds with documented clinical history, we aimed to identify candidates with unforeseen potential for repositioning as anticancer drugs. Our screen identified five molecules with pronounced MCTS-selective activity: nitazoxanide, niclosamide, closantel, pyrvinium pamoate, and salinomycin. Herein, we show that all five compounds inhibit mitochondrial respiration. This suggests that cancer cells in low glucose concentrations depend on oxidative phosphorylation rather than solely glycolysis. Importantly, continuous exposure to the compounds was required to achieve effective treatment. Nitazoxanide, an FDA-approved antiprotozoal drug with excellent pharmacokinetic and safety profile, is the only molecule among the screening hits that reaches high plasma concentrations persisting for up to a few hours after single oral dose. Nitazoxanide activated the AMPK pathway and downregulated c-Myc, mTOR, and Wnt signaling at clinically achievable concentrations. Nitazoxanide combined with the cytotoxic drug irinotecan showed anticancer activity in vivo. We here report that the FDA-approved anthelmintic drug nitazoxanide could be a potential candidate for advancement into cancer clinical trials. ©2015 American Association for Cancer Research.

Marijuana and Cocaine Effect Expectancies and Drug Use Patterns.

ERIC Educational Resources Information Center

Schafer, John; Brown, Sandra A.

1991-01-01

Content analyzed self-reports from 704 college students and used results to develop Marijuana Effect Expectancy Questionnaire and Cocaine Effect Expectancy Questionnaire. Identified six marijuana expectancies and five cocaine expectancies. Drug effect expectancies distinguished between patterns of nonuse and varying degrees of use of these two…

Exploring Spanish health social media for detecting drug effects

PubMed Central

2015-01-01

Background Adverse Drug reactions (ADR) cause a high number of deaths among hospitalized patients in developed countries. Major drug agencies have devoted a great interest in the early detection of ADRs due to their high incidence and increasing health care costs. Reporting systems are available in order for both healthcare professionals and patients to alert about possible ADRs. However, several studies have shown that these adverse events are underestimated. Our hypothesis is that health social networks could be a significant information source for the early detection of ADRs as well as of new drug indications. Methods In this work we present a system for detecting drug effects (which include both adverse drug reactions as well as drug indications) from user posts extracted from a Spanish health forum. Texts were processed using MeaningCloud, a multilingual text analysis engine, to identify drugs and effects. In addition, we developed the first Spanish database storing drugs as well as their effects automatically built from drug package inserts gathered from online websites. We then applied a distant-supervision method using the database on a collection of 84,000 messages in order to extract the relations between drugs and their effects. To classify the relation instances, we used a kernel method based only on shallow linguistic information of the sentences. Results Regarding Relation Extraction of drugs and their effects, the distant supervision approach achieved a recall of 0.59 and a precision of 0.48. Conclusions The task of extracting relations between drugs and their effects from social media is a complex challenge due to the characteristics of social media texts. These texts, typically posts or tweets, usually contain many grammatical errors and spelling mistakes. Moreover, patients use lay terminology to refer to diseases, symptoms and indications that is not usually included in lexical resources in languages other than English. PMID:26100267

Exploring Spanish health social media for detecting drug effects.

PubMed

Segura-Bedmar, Isabel; Martínez, Paloma; Revert, Ricardo; Moreno-Schneider, Julián

2015-01-01

Adverse Drug reactions (ADR) cause a high number of deaths among hospitalized patients in developed countries. Major drug agencies have devoted a great interest in the early detection of ADRs due to their high incidence and increasing health care costs. Reporting systems are available in order for both healthcare professionals and patients to alert about possible ADRs. However, several studies have shown that these adverse events are underestimated. Our hypothesis is that health social networks could be a significant information source for the early detection of ADRs as well as of new drug indications. In this work we present a system for detecting drug effects (which include both adverse drug reactions as well as drug indications) from user posts extracted from a Spanish health forum. Texts were processed using MeaningCloud, a multilingual text analysis engine, to identify drugs and effects. In addition, we developed the first Spanish database storing drugs as well as their effects automatically built from drug package inserts gathered from online websites. We then applied a distant-supervision method using the database on a collection of 84,000 messages in order to extract the relations between drugs and their effects. To classify the relation instances, we used a kernel method based only on shallow linguistic information of the sentences. Regarding Relation Extraction of drugs and their effects, the distant supervision approach achieved a recall of 0.59 and a precision of 0.48. The task of extracting relations between drugs and their effects from social media is a complex challenge due to the characteristics of social media texts. These texts, typically posts or tweets, usually contain many grammatical errors and spelling mistakes. Moreover, patients use lay terminology to refer to diseases, symptoms and indications that is not usually included in lexical resources in languages other than English.

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.

Predicting Adverse Drug Effects from Literature- and Database-Mined Assertions.

PubMed

La, Mary K; Sedykh, Alexander; Fourches, Denis; Muratov, Eugene; Tropsha, Alexander

2018-06-06

Given that adverse drug effects (ADEs) have led to post-market patient harm and subsequent drug withdrawal, failure of candidate agents in the drug development process, and other negative outcomes, it is essential to attempt to forecast ADEs and other relevant drug-target-effect relationships as early as possible. Current pharmacologic data sources, providing multiple complementary perspectives on the drug-target-effect paradigm, can be integrated to facilitate the inference of relationships between these entities. This study aims to identify both existing and unknown relationships between chemicals (C), protein targets (T), and ADEs (E) based on evidence in the literature. Cheminformatics and data mining approaches were employed to integrate and analyze publicly available clinical pharmacology data and literature assertions interrelating drugs, targets, and ADEs. Based on these assertions, a C-T-E relationship knowledge base was developed. Known pairwise relationships between chemicals, targets, and ADEs were collected from several pharmacological and biomedical data sources. These relationships were curated and integrated according to Swanson's paradigm to form C-T-E triangles. Missing C-E edges were then inferred as C-E relationships. Unreported associations between drugs, targets, and ADEs were inferred, and inferences were prioritized as testable hypotheses. Several C-E inferences, including testosterone → myocardial infarction, were identified using inferences based on the literature sources published prior to confirmatory case reports. Timestamping approaches confirmed the predictive ability of this inference strategy on a larger scale. The presented workflow, based on free-access databases and an association-based inference scheme, provided novel C-E relationships that have been validated post hoc in case reports. With refinement of prioritization schemes for the generated C-E inferences, this workflow may provide an effective computational method for

Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery

PubMed Central

Gough, Albert H.; Chen, Ning; Shun, Tong Ying; Lezon, Timothy R.; Boltz, Robert C.; Reese, Celeste E.; Wagner, Jacob; Vernetti, Lawrence A.; Grandis, Jennifer R.; Lee, Adrian V.; Stern, Andrew M.; Schurdak, Mark E.; Taylor, D. Lansing

2014-01-01

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology. PMID:25036749

Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery.

PubMed

Gough, Albert H; Chen, Ning; Shun, Tong Ying; Lezon, Timothy R; Boltz, Robert C; Reese, Celeste E; Wagner, Jacob; Vernetti, Lawrence A; Grandis, Jennifer R; Lee, Adrian V; Stern, Andrew M; Schurdak, Mark E; Taylor, D Lansing

2014-01-01

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

Effects of senolytic drugs on human mesenchymal stromal cells.

PubMed

Grezella, Clara; Fernandez-Rebollo, Eduardo; Franzen, Julia; Ventura Ferreira, Mónica Sofia; Beier, Fabian; Wagner, Wolfgang

2018-04-18

Senolytic drugs are thought to target senescent cells and might thereby rejuvenate tissues. In fact, such compounds were suggested to increase health and lifespan in various murine aging models. So far, effects of senolytic drugs have not been analysed during replicative senescence of human mesenchymal stromal cells (MSCs). In this study, we tested four potentially senolytic drugs: ABT-263 (navitoclax), quercetin, nicotinamide riboside, and danazol. The effects of these compounds were analysed during long-term expansion of MSCs, until replicative senescence. Furthermore, we determined the effect on molecular markers for replicative senescence, such as senescence-associated beta-galactosidase staining (SA-β-gal), telomere attrition, and senescence-associated DNA methylation changes. Co-culture experiments of fluorescently labelled early and late passages revealed that particularly ABT-263 had a significant but moderate senolytic effect. This was in line with reduced SA-β-gal staining in senescent MSCs upon treatment with ABT-263. However, none of the drugs had significant effects on the maximum number of population doublings, telomere length, or epigenetic senescence predictions. Of the four tested drugs, only ABT-263 revealed a senolytic effect in human MSCs-and even treatment with this compound did not rejuvenate MSCs with regard to telomere length or epigenetic senescence signature. It will be important to identify more potent senolytic drugs to meet the high hopes for regenerative medicine.

The effect of grapefruit juice on drug disposition

PubMed Central

Hanley, Michael J.; Cancalon, Paul; Widmer, Wilbur W.; Greenblatt, David J.

2011-01-01

Introduction Since their initial discovery in 1989, grapefruit juice-drug interactions have received extensive interest from the scientific, medical, regulatory, and lay communities. Although knowledge regarding the effects of grapefruit juice on drug disposition continues to expand, the list of drugs studied in the clinical setting remains relatively limited. Areas covered This article reviews the in vitro effects of grapefruit juice and its constituents on the activity of cytochrome P450 enzymes, organic anion-transporting polypeptides, P-glycoprotein, esterases and sulfotransferases. The translational applicability of the in vitro findings to the clinical setting is discussed for each drug metabolizing enzyme and transporter. Reported area under the plasma concentration-time curve ratios for available grapefruit juice-drug interaction studies are also provided. Relevant investigations were identified by searching the Pubmed electronic database from 1989 to 2010. Expert opinion Grapefruit juice increases the bioavailability of some orally-administered drugs that are metabolized by CYP3A and normally undergo extensive presystemic extraction. In addition, grapefruit juice can decrease the oral absorption of a few drugs that rely on organic anion-transporting polypeptides in the gastrointestinal tract for their uptake. The number of drugs shown to interact with grapefruit juice in vitro is far greater than the number of clinically relevant grapefruit juice-drug interactions. For the majority of patients, complete avoidance of grapefruit juice is unwarranted. PMID:21254874

Illicit Drug Use in a Community-Based Sample of Heterosexually Identified Emerging Adults

ERIC Educational Resources Information Center

Halkitis, Perry N.; Manasse, Ashley N.; McCready, Karen C.

2010-01-01

In this study we assess lifetime and recent drug use patterns among 261 heterosexually identified 18- to 25-year-olds through brief street intercept surveys conducted in New York City. Marijuana, hallucinogens, powder cocaine, and ecstasy were the most frequently reported drugs for both lifetime and recent use. Findings further suggest significant…

Effects of Maternal Work Incentives on Teen Drug Arrests

PubMed Central

Corman, Hope; Dave, Dhaval; Kalil, Ariel; Reichman, Nancy E.

2017-01-01

Purpose This study exploits differences in the implementation of welfare reform across states and over time in the United States in the attempt to identify causal effects of welfare reform on youth arrests for drug-related crimes between 1990 and 2005, the period during which welfare reform unfolded. Methodology Using monthly arrest data from the U.S. Federal Bureau of Investigation's Uniform Crime Reports, we estimate the effects of welfare reform implementation on drug-related arrests among 15–17 year olds in the United States between 1990 and 2005. We use a difference-in-differences (DD) approach that exploits the implementation of welfare reform across states and over time to estimate effects for teens exposed to welfare reform. Findings The findings, based on numerous different model specifications, suggest that welfare reform had no statistically significant effect on teen drug arrests. Most estimates were positive and suggestive of a small (3%) increase in arrests. Originality/Value This study investigated the effects of a broad-based policy change that altered maternal employment, family income, and other family characteristics on youth drug arrests. PMID:28989228

Walking on thin ice! Identifying methamphetamine “drug mules” on digital plain radiography

PubMed Central

Abdul Rashid, S N; Mohamad Saini, S B; Abdul Hamid, S; Muhammad, S J; Mahmud, R; Thali, M J

2014-01-01

Objective: The purpose of this study was to retrospectively evaluate the sensitivity, specificity and accuracy of identifying methamphetamine (MA) internal payloads in “drug mules” by plain abdominal digital radiography (DR). Methods: The study consisted of 35 individuals suspected of internal MA drug containers. A total of 59 supine digital radiographs were collected. An overall calculation regarding the diagnostic accuracy for all “drug mules” and a specific evaluation concerning the radiological appearance of drug packs as well as the rate of clearance and complications in correlation with the reader's experience were performed. The gold standard was the presence of secured drug packs in the faeces. Results: There were 16 true-positive “drug mules” identified. DR of all drug carriers for Group 1 (forensic imaging experienced readers, n = 2) exhibited a sensitivity of 100%, a mean specificity of 76.3%, positive predictive value (PPV) of 78.5%, negative predictive value (NPV) of 100% and a mean accuracy 87.2%. Group 2 (inexperienced readers, n = 3) showed a lower sensitivity (93.7%), a mean specificity of 86%, a PPV of 86.5%, an NPV of 94.1% and a mean accuracy of 89.5%. The interrater agreement within Group 1 was 0.72 and within Group 2 averaged to 0.79, indicating a fair to very good agreement. Conclusion: DR is a valuable screening tool in cases of MA body packers with huge internal payloads being associated with a high diagnostic insecurity. Diagnostic insecurity on plain films may be overcome by low-dose CT as a cross-sectional imaging modality and addressed by improved radiological education in reporting drug carriers on imaging. Advances in knowledge: Diagnostic signs (double-condom and halo signs) on digital plain radiography are specific in MA “drug mules”, although DR is associated with high diagnostic insecurity and underreports the total internal payload. PMID:24472728

Examining factors that influence the effectiveness of cleaning antineoplastic drugs from drug preparation surfaces: a pilot study.

PubMed

Hon, Chun-Yip; Chua, Prescillia Ps; Danyluk, Quinn; Astrakianakis, George

2014-06-01

Occupational exposure to antineoplastic drugs has been documented to result in various adverse health effects. Despite the implementation of control measures to minimize exposure, detectable levels of drug residual are still found on hospital work surfaces. Cleaning these surfaces is considered as one means to minimize the exposure potential. However, there are no consistent guiding principles related to cleaning of contaminated surfaces resulting in hospitals to adopt varying practices. As such, this pilot study sought to evaluate current cleaning protocols and identify those factors that were most effective in reducing contamination on drug preparation surfaces. Three cleaning variables were examined: (1) type of cleaning agent (CaviCide®, Phenokil II™, bleach and chlorhexidine), (2) application method of cleaning agent (directly onto surface or indirectly onto a wipe) and (3) use of isopropyl alcohol after cleaning agent application. Known concentrations of antineoplastic drugs (either methotrexate or cyclophosphamide) were placed on a stainless steel swatch and then, systematically, each of the three cleaning variables was tested. Surface wipes were collected and quantified using high-performance liquid chromatography-tandem mass spectrometry to determine the percent residual of drug remaining (with 100% being complete elimination of the drug). No one single cleaning agent proved to be effective in completely eliminating all drug contamination. The method of application had minimal effect on the amount of drug residual. In general, application of isopropyl alcohol after the use of cleaning agent further reduced the level of drug contamination although measureable levels of drug were still found in some cases.

Putative histidine kinase inhibitors with antibacterial effect against multi-drug resistant clinical isolates identified by in vitro and in silico screens

NASA Astrophysics Data System (ADS)

Velikova, Nadya; Fulle, Simone; Manso, Ana Sousa; Mechkarska, Milena; Finn, Paul; Conlon, J. Michael; Oggioni, Marco Rinaldo; Wells, Jerry M.; Marina, Alberto

2016-05-01

Novel antibacterials are urgently needed to address the growing problem of bacterial resistance to conventional antibiotics. Two-component systems (TCS) are widely used by bacteria to regulate gene expression in response to various environmental stimuli and physiological stress and have been previously proposed as promising antibacterial targets. TCS consist of a sensor histidine kinase (HK) and an effector response regulator. The HK component contains a highly conserved ATP-binding site that is considered to be a promising target for broad-spectrum antibacterial drugs. Here, we describe the identification of putative HK autophosphorylation inhibitors following two independent experimental approaches: in vitro fragment-based screen via differential scanning fluorimetry and in silico structure-based screening, each followed up by the exploration of analogue compounds as identified by ligand-based similarity searches. Nine of the tested compounds showed antibacterial effect against multi-drug resistant clinical isolates of bacterial pathogens and include three novel scaffolds, which have not been explored so far in other antibacterial compounds. Overall, putative HK autophosphorylation inhibitors were found that together provide a promising starting point for further optimization as antibacterials.

A probabilistic approach to identify putative drug targets in biochemical networks.

PubMed

Murabito, Ettore; Smallbone, Kieran; Swinton, Jonathan; Westerhoff, Hans V; Steuer, Ralf

2011-06-06

Network-based drug design holds great promise in clinical research as a way to overcome the limitations of traditional approaches in the development of drugs with high efficacy and low toxicity. This novel strategy aims to study how a biochemical network as a whole, rather than its individual components, responds to specific perturbations in different physiological conditions. Proteins exerting little control over normal cells and larger control over altered cells may be considered as good candidates for drug targets. The application of network-based drug design would greatly benefit from using an explicit computational model describing the dynamics of the system under investigation. However, creating a fully characterized kinetic model is not an easy task, even for relatively small networks, as it is still significantly hampered by the lack of data about kinetic mechanisms and parameters values. Here, we propose a Monte Carlo approach to identify the differences between flux control profiles of a metabolic network in different physiological states, when information about the kinetics of the system is partially or totally missing. Based on experimentally accessible information on metabolic phenotypes, we develop a novel method to determine probabilistic differences in the flux control coefficients between the two observable phenotypes. Knowledge of how differences in flux control are distributed among the different enzymatic steps is exploited to identify points of fragility in one of the phenotypes. Using a prototypical cancerous phenotype as an example, we demonstrate how our approach can assist researchers in developing compounds with high efficacy and low toxicity. © 2010 The Royal Society

Drug-drug Interactions of Statins Potentially Leading to Muscle-Related Side Effects in Hospitalized Patients.

PubMed

Bucsa, Camelia; Farcas, Andreea; Leucuta, D; Mogosan, Cristina; Bojita, M; Dumitrascu, D L

2015-01-01

The associations of drugs that may interact with the statins resulting in elevated serum concentration of the statins are an important risk factor for statin induced muscle disorders. We aimed to determine the prevalence of these associations in all hospitalized patients that had been prescribed statins before/during hospitalization and to find out how often they are associated with muscle-related side effects. This prospective, non-interventional study performed in two internal medicine departments included patients with statin therapy before/during hospitalization. Data on each patient demographic characteristics, co-morbidities and treatment was collected from medical charts and interviews. We evaluated patients' therapy for the targeted associations using Thomson Micromedex Drug Interactions checker and we ranked the identified drug-drug interactions (DDIs) accordingly. Each patient with statin treatment before admission was additionally interviewed in order to identify muscular symptoms. In 109 patients on statin treatment we found 35 potential (p) DDIs of statins in 30 (27.5%) patients, most of which were in the therapy before admission (27 pDDIs). The pDDIs were moderate (20 pDDIs) and major (15 pDDIs). Of the total number of pDDIs, 24 were targeting the muscular system. The drugs most frequently involved in the statins' pDDIs were amiodarone and fenofibrate. Two of the patients with pDDIs reported muscle pain, both having additional risk factors for statin induced muscular effects. The prevalence of statins' pDDIs was high in our study, mostly in the therapy before admission, with only a small number of pDDIs resulting in clinical outcome.

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs

PubMed Central

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F.; Lecuit, Marc

2016-01-01

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents. PMID:27177310

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs.

PubMed

Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F; Lecuit, Marc

2016-05-12

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents.

iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking

PubMed Central

Min, Jian-Liang; Chou, Kuo-Chen

2013-01-01

With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results. PMID:24371828

Using RNA-seq and targeted nucleases to identify mechanisms of drug resistance in acute myeloid leukemia.

PubMed

Rathe, Susan K; Moriarity, Branden S; Stoltenberg, Christopher B; Kurata, Morito; Aumann, Natalie K; Rahrmann, Eric P; Bailey, Natashay J; Melrose, Ellen G; Beckmann, Dominic A; Liska, Chase R; Largaespada, David A

2014-08-13

The evolution from microarrays to transcriptome deep-sequencing (RNA-seq) and from RNA interference to gene knockouts using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and Transcription Activator-Like Effector Nucleases (TALENs) has provided a new experimental partnership for identifying and quantifying the effects of gene changes on drug resistance. Here we describe the results from deep-sequencing of RNA derived from two cytarabine (Ara-C) resistance acute myeloid leukemia (AML) cell lines, and present CRISPR and TALEN based methods for accomplishing complete gene knockout (KO) in AML cells. We found protein modifying loss-of-function mutations in Dck in both Ara-C resistant cell lines. CRISPR and TALEN-based KO of Dck dramatically increased the IC₅₀ of Ara-C and introduction of a DCK overexpression vector into Dck KO clones resulted in a significant increase in Ara-C sensitivity. This effort demonstrates the power of using transcriptome analysis and CRISPR/TALEN-based KOs to identify and verify genes associated with drug resistance.

Comprehensive prediction of drug-protein interactions and side effects for the human proteome

PubMed Central

Zhou, Hongyi; Gao, Mu; Skolnick, Jeffrey

2015-01-01

Identifying unexpected drug-protein interactions is crucial for drug repurposing. We develop a comprehensive proteome scale approach that predicts human protein targets and side effects of drugs. For drug-protein interaction prediction, FINDSITEcomb, whose average precision is ~30% and recall ~27%, is employed. For side effect prediction, a new method is developed with a precision of ~57% and a recall of ~24%. Our predictions show that drugs are quite promiscuous, with the average (median) number of human targets per drug of 329 (38), while a given protein interacts with 57 drugs. The result implies that drug side effects are inevitable and existing drugs may be useful for repurposing, with only ~1,000 human proteins likely causing serious side effects. A killing index derived from serious side effects has a strong correlation with FDA approved drugs being withdrawn. Therefore, it provides a pre-filter for new drug development. The methodology is free to the academic community on the DR. PRODIS (DRugome, PROteome, and DISeasome) webserver at http://cssb.biology.gatech.edu/dr.prodis/. DR. PRODIS provides protein targets of drugs, drugs for a given protein target, associated diseases and side effects of drugs, as well as an interface for the virtual target screening of new compounds. PMID:26057345

Identifying genetic loci affecting antidepressant drug response in depression using drug–gene interaction models

PubMed Central

Noordam, Raymond; Avery, Christy L; Visser, Loes E; Stricker, Bruno H

2016-01-01

Antidepressants are often only moderately successful in decreasing the severity of depressive symptoms. In part, antidepressant treatment response in patients with depression is genetically determined. However, although a large number of studies have been conducted aiming to identify genetic variants associated with antidepressant drug response in depression, only a few variants have been repeatedly identified. Within the present review, we will discuss the methodological challenges and limitations of the studies that have been conducted on this topic to date (e.g., ‘treated-only design’, statistical power) and we will discuss how specifically drug–gene interaction models can be used to be better able to identify genetic variants associated with antidepressant drug response in depression. PMID:27248517

Two-part random effects growth modeling to identify risks associated with alcohol and cannabis initiation, initial average use and changes in drug consumption in a sample of adult, male twins

PubMed Central

Gillespie, Nathan A.; Lubke, Gitta H.; Gardner, Charles O.; Neale, Michael C.; Kendler, Kenneth S.

2012-01-01

Aims Our aim was to profile alcohol and cannabis initiation and to characterize the effects of developmental and environmental risk factors on changes in average drug use over time. Design We fitted a two-part random effects growth model to identify developmental and environmental risks associated with alcohol and cannabis initiation, initial average use and changes in average use. Participants 1796 males aged 24–63 from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Measurements Data from three interview waves included self-report measures of average alcohol and cannabis use between ages 15 and 24, genetic risk of problem drug use, childhood environmental risks, personality, psychiatric symptoms, as well as personal, family and social risk factors. Findings Average alcohol and cannabis use were correlated at all ages. Genetic risk of drug use based on family history, higher sensation seeking, and peer group deviance predicted both alcohol and cannabis initiation. Higher drug availability predicted cannabis initiation while less parental monitoring and drug availability were the best predictors of how much cannabis individuals consumed over time. Conclusion The liability to initiate alcohol and cannabis, average drug use as well as changes in drug use during teenage years and young adulthood is associated with known risk factors. PMID:22177896

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Illicit drugs and the media: models of media effects for use in drug policy research.

PubMed

Lancaster, Kari; Hughes, Caitlin E; Spicer, Bridget; Matthew-Simmons, Francis; Dillon, Paul

2011-07-01

Illicit drugs are never far from the media gaze and although identified almost a decade ago as 'a new battleground' for the alcohol and other drug (AOD) field there has been limited research examining the role of the news media and its effects on audiences and policy. This paper draws together media theories from communication literature to examine media functions. We illustrate how each function is relevant for media and drugs research by drawing upon the existing literature examining Australian media coverage during the late 1990s of escalating heroin-related problems and proposed solutions. Media can influence audiences in four key ways: by setting the agenda and defining public interest; framing issues through selection and salience; indirectly shaping individual and community attitudes towards risk; and feeding into political debate and decision making. Each has relevance for the AOD field. For example, media coverage of the escalating heroin-related problems in Australia played a strong role in generating interest in heroin overdoses, framing public discourse in terms of a health and/or criminal issue and affecting political decisions. Implications AND CONCLUSION: Media coverage in relation to illicit drugs can have multifarious effects. Incorporating media communication theories into future research and actions is critical to facilitate understanding of the short- and long-term impacts of media coverage on illicit drugs and the avenues by which the AOD field can mitigate or inform future media debates on illicit drugs. © 2010 Australasian Professional Society on Alcohol and other Drugs.

The effectiveness and cost-effectiveness of diversion and aftercare programmes for offenders using class A drugs: a systematic review and economic evaluation.

PubMed

Hayhurst, Karen P; Leitner, Maria; Davies, Linda; Flentje, Rachel; Millar, Tim; Jones, Andrew; King, Carlene; Donmall, Michael; Farrell, Michael; Fazel, Seena; Harris, Rochelle; Hickman, Matthew; Lennox, Charlotte; Mayet, Soraya; Senior, Jane; Shaw, Jennifer

2015-01-01

The societal costs of problematic class A drug use in England and Wales exceed £15B; drug-related crime accounts for almost 90% of costs. Diversion plus treatment and/or aftercare programmes may reduce drug-related crime and costs. To assess the effectiveness and cost-effectiveness of diversion and aftercare for class A drug-using offenders, compared with no diversion. Adult class A drug-using offenders diverted to treatment or an aftercare programme for their drug use. Programmes to identify and divert problematic drug users to treatment (voluntary, court mandated or monitored services) at any point within the criminal justice system (CJS). Aftercare follows diversion and treatment, excluding care following prison or non-diversionary drug treatment. Thirty-three electronic databases and government online resources were searched for studies published between January 1985 and January 2012, including MEDLINE, PsycINFO and ISI Web of Science. Bibliographies of identified studies were screened. The UK Drug Data Warehouse, the UK Drug Treatment Outcomes Research Study and published statistics and reports provided data for the economic evaluation. Included studies evaluated diversion in adult class A drug-using offenders, in contact with the CJS. The main outcomes were drug use and offending behaviour, and these were pooled using meta-analysis. The economic review included full economic evaluations for adult opiate and/or crack, or powder, cocaine users. An economic decision analytic model, estimated incremental costs per unit of outcome gained by diversion and aftercare, over a 12-month time horizon. The perspectives included the CJS, NHS, social care providers and offenders. Probabilistic sensitivity analysis and one-way sensitivity analysis explored variance in parameter estimates, longer time horizons and structural uncertainty. Sixteen studies met the effectiveness review inclusion criteria, characterised by poor methodological quality, with modest sample sizes

Fetal effects of psychoactive drugs.

PubMed

Salisbury, Amy L; Ponder, Kathryn L; Padbury, James F; Lester, Barry M

2009-09-01

Psychoactive drug use by pregnant women has the potential to effect fetal development; the effects are often thought to be drug-specific and gestational age dependent. This article describes the effects of three drugs with similar molecular targets that involve monoaminergic transmitter systems: cocaine, methamphetamine, and selective serotonin re-uptake inhibitors (SSRIs) used to treat maternal depression during pregnancy. We propose a possible common epigenetic mechanism for their potential effects on the developing child. We suggest that exposure to these substances acts as a stressor that affects fetal programming, disrupts fetal placental monoamine transporter expression and alters neuroendocrine and neurotransmitter system development. We also discuss neurobehavioral techniques that may be useful in the early detection of the effects of in utero drug exposure.

An update on the use of C. elegans for preclinical drug discovery: screening and identifying anti-infective drugs.

PubMed

Kim, Wooseong; Hendricks, Gabriel Lambert; Lee, Kiho; Mylonakis, Eleftherios

2017-06-01

The emergence of antibiotic-resistant and -tolerant bacteria is a major threat to human health. Although efforts for drug discovery are ongoing, conventional bacteria-centered screening strategies have thus far failed to yield new classes of effective antibiotics. Therefore, new paradigms for discovering novel antibiotics are of critical importance. Caenorhabditis elegans, a model organism used for in vivo, offers a promising solution for identification of anti-infective compounds. Areas covered: This review examines the advantages of C. elegans-based high-throughput screening over conventional, bacteria-centered in vitro screens. It discusses major anti-infective compounds identified from large-scale C. elegans-based screens and presents the first clinically-approved drugs, then known bioactive compounds, and finally novel small molecules. Expert opinion: There are clear advantages of using a C. elegans-infection based screening method. A C. elegans-based screen produces an enriched pool of non-toxic, efficacious, potential anti-infectives, covering: conventional antimicrobial agents, immunomodulators, and anti-virulence agents. Although C. elegans-based screens do not denote the mode of action of hit compounds, this can be elucidated in secondary studies by comparing the results to target-based screens, or conducting subsequent target-based screens, including the genetic knock-down of host or bacterial genes.

Prenatal care and counseling of female drug-abusers: effects on drug abuse and perinatal outcome.

PubMed

Kukko, H; Halmesmäki, E

1999-01-01

To evaluate the efficacy of a specific counseling and withdrawal program for drug-abusing pregnant women and its effect on perinatal outcome. An analysis of 120 pregnancies followed in 111 drug-abusing women giving birth at the Department of Obstetrics and Gynecology, Helsinki University Central Hospital, in 1985-95. Personnel responsible for local maternity care in the Helsinki area were trained to identify pregnant drug-abusers and to refer them to our hospital for clinical antenatal care and counseling with psychological and social support. Substance abuse during pregnancy was monitored by self-report and serial urine screenings. Obstetric and perinatal outcome were compared between those who succeeded in quitting totally or reducing drug use, and those who continued their drug use throughout pregnancy. The significance of the differences was tested by Student's unpaired t-test and binomial t-test. Of the women, 62% registered before the 20th week of pregnancy and 32% during the 20th-29th week of pregnancy (mean 18.4+/-6.6 weeks). Twelve women were admitted to an obstetric ward for withdrawal. In 73 of the 120 (61%) pregnancies the woman succeeded either in quitting totally or reducing drug abuse. Among this group, incidence of preterm birth (4.1%) was smaller (p<0.001), and gestational age (39.8+/-2.2 weeks) and birth weight (3393+/-605 gr) higher (p<0.05) than those (19.6%, 38.3+/-3.4 wk and 3049+/-728 gr, respectively) in the group continuing their drug abuse. Additionally, the percentage of normal delivery (80.8%) was higher (p<0.05), and incidence of withdrawal symptoms (19.2%), lower (p<0.001) than for those who continued drug abuse (65.2% and 47.8%, respectively). Carefully monitored counseling program for pregnant drug abusers is effective in reducing the amount of drugs used and improves perinatal outcome.

Identifying high risk medications causing potential drug-drug interactions in outpatients: A prescription database study based on an online surveillance system.

PubMed

Toivo, T M; Mikkola, J A V; Laine, K; Airaksinen, M

2016-01-01

Drug-drug interactions (DDIs) are a significant cause for adverse drug events (ADEs). DDIs are often predictable and preventable, but their prevention and management require systematic service development. Most DDI studies focus on interaction rates in hospitalized patients. Less is known of DDIs in outpatients, particularly how community pharmacists could contribute to DDI management by applying their surveillance systems for identifying high-risk medications. The study was related to the implementation of the first online DDI surveillance system in Finnish community pharmacies. The goal was to demonstrate how community pharmacies can utilize their prospective surveillance system 1) for identifying high risk medications causing potential DDIs in outpatients, 2) for collaborative service development with local physicians, and 3) for academic risk management research purposes. All DDI alerts given by the online surveillance system were collected during a one-month period in 16 out of 17 University Pharmacy outlets in Finland, covering approximately 10% of the national outpatient prescription volume. The surveillance system was based on the FASS database, which categorizes DDIs into four classes (A-D) according to their clinical significance. Potential drug-drug DDIs were analyzed for 276,891 dispensed community pharmacy prescriptions. Potential DDIs were associated with 10.8%, or 31,110 of these prescriptions. Clinically significant interaction alerts categorized as FASS classes D (most severe, should be avoided) and C (clinically significant but controllable) were associated with 0.5% and 7.0% of the prescriptions, respectively. Methotrexate and warfarin had the highest risk of causing potentially serious (class D) interactions. These interaction alerts were most frequently between methotrexate and NSAIDs and warfarin and NSAIDs. In general, NSAIDs were the most commonly interacting drugs in this study. This study demonstrates that community pharmacies can actively

Using Click Chemistry to Identify Potential Drug Targets in Plasmodium

DTIC Science & Technology

2015-04-01

step of the Plasmodium mammalian cycle . Inhibiting this step can block malaria at an early step. However, few anti-malarials target liver infection...points in the life cycle of malaria parasites. PLoS Biol 12: e1001806. 2. Falae A, Combe A, Amaladoss A, Carvalho T, Menard R, et al. (2010) Role of...AWARD NUMBER: W81XWH-13-1-0429 TITLE: Using "Click Chemistry" to Identify Potential Drug Targets in Plasmodium PRINCIPAL INVESTIGATOR: Dr. Purnima

Drug Discontinuation Effects Are Part of the Pharmacology of a Drug

PubMed Central

2011-01-01

Most reviews of drug withdrawal effects focus on drugs of potential abuse such as opioids, benzodiazepines, etc. Abrupt discontinuation of many other drugs used in medicine cause withdrawal syndromes, some of which can be fatal. Discontinuation of a number of cardiovascular drugs can increase risk of cardiovascular events above that of people not taking these drugs. These include β-adrenergic receptor antagonists, aspirin, HMG-CoA reductase inhibitors (statins), and heparin. Rebound hypertension occurs after abrupt cessation of many antihypertensive drugs. The possibility of discontinuation syndromes has usually been neglected until adverse clinical events force them to be noticed. Attention to the possibility of drug discontinuation effects is an important part of drug safety evaluation. PMID:21849624

What is known about the cost-effectiveness of orphan drugs? Evidence from cost-utility analyses.

PubMed

Picavet, E; Cassiman, D; Simoens, S

2015-06-01

In times of financial and economic hardship, governments are looking to contain pharmaceutical expenditure by focusing on cost-effective drugs. Because of their high prices and difficulties in demonstrating effectiveness in small patient populations, orphan drugs are often perceived as not able to meet traditional reimbursement threshold value for money. The aim of this study was to provide an overview of the available evidence on the cost-effectiveness of orphan drugs. All orphan drugs listed as authorized on the website of the European Medicines Agency on 21 November 2013 were included in the analysis. Cost-utility analyses (CUAs) were identified by searching the Tufts Medical Center Cost-Effectiveness Analysis Registry and Embase. For each CUA, a number of variables were collected. The search identified 23 articles on the Tufts registry and 167 articles on Embase. The final analysis included 45 CUAs and 61 incremental cost-utility ratios (ICURs) for 19 orphan drugs. Of all ICURS, 16·3% were related to dominant drugs (i.e. more effective and less expensive than the comparator), 70·5% were related to drugs that are more effective, but at a higher cost, and 13·1% were related to dominated drugs (i.e. less effective and more expensive than the comparator). The median overall ICUR was €40 242 per quality-adjusted life year (QALY) with a minimum ICUR of €6311/QALY and a maximum ICUR of €974,917/QALY. This study demonstrates that orphan drugs can meet traditional reimbursement thresholds. Considering a threshold of £30,000/QALY, in this study, ten (52·6%) of a total of 19 orphan drugs for which data were available meet the threshold. As much as fifteen orphan drugs (78·9%) are eligible for reimbursement if a threshold of €80,000/QALY is considered. © 2015 John Wiley & Sons Ltd.

Effective Drug Delivery in Diffuse Intrinsic Pontine Glioma: A Theoretical Model to Identify Potential Candidates

PubMed Central

El-Khouly, Fatma E.; van Vuurden, Dannis G.; Stroink, Thom; Hulleman, Esther; Kaspers, Gertjan J. L.; Hendrikse, N. Harry; Veldhuijzen van Zanten, Sophie E. M.

2017-01-01

Despite decades of clinical trials for diffuse intrinsic pontine glioma (DIPG), patient survival does not exceed 10% at two years post-diagnosis. Lack of benefit from systemic chemotherapy may be attributed to an intact bloodbrain barrier (BBB). We aim to develop a theoretical model including relevant physicochemical properties in order to review whether applied chemotherapeutics are suitable for passive diffusion through an intact BBB or whether local administration via convection-enhanced delivery (CED) may increase their therapeutic potential. Physicochemical properties (lipophilicity, molecular weight, and charge in physiological environment) of anticancer drugs historically and currently administered to DIPG patients, that affect passive diffusion over the BBB, were included in the model. Subsequently, the likelihood of BBB passage of these drugs was ascertained, as well as their potential for intratumoral administration via CED. As only non-molecularly charged, lipophilic, and relatively small sized drugs are likely to passively diffuse through the BBB, out of 51 drugs modeled, only 8 (15%)—carmustine, lomustine, erlotinib, vismodegib, lenalomide, thalidomide, vorinostat, and mebendazole—are theoretically qualified for systemic administration in DIPG. Local administration via CED might create more therapeutic options, excluding only positively charged drugs and drugs that are either prodrugs and/or only available as oral formulation. A wide variety of drugs have been administered systemically to DIPG patients. Our model shows that only few are likely to penetrate the BBB via passive diffusion, which may partly explain the lack of efficacy. Drug distribution via CED is less dependent on physicochemical properties and may increase the therapeutic options for DIPG. PMID:29164054

Quantitative prediction of drug side effects based on drug-related features.

PubMed

Niu, Yanqing; Zhang, Wen

2017-09-01

Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.

A qualitative examination of the effects of international counter-drug interdictions.

PubMed

Toth, Alexander G; Mitchell, Ojmarrh

2018-05-01

The purpose of this study is to utilize unique qualitative data to determine the effects of sporadic international drug interdictions on drug trafficking, and to assess whether the responses of drug traffickers align with rational choice theory. Qualitative data obtained from 23 high-level United States Drug Enforcement Administration (DEA) informants, who are embedded in international drug trafficking groups, are examined to identify common responses to drug interdiction operations. The findings indicate that sporadic counter-drug interdictions do not a have permanent deterrent effect on transnational drug smuggling operations. However, these types of law enforcement operations produce temporary alterations in drug trafficking, as traffickers adopted a variety of methods to thwart the efforts of law enforcement-often by relying on information acquired from corrupt local law enforcement. The results also indicate that while interdiction operations displaced trafficking activities (temporally, spatially, and methodological), there is little evidence that drug traffickers responded to such operations by moving into new areas (i.e., malign spatial displacement). Sporadic international drug interdiction programs do little to deter drug trafficking organizations (DTOs) from engaging in their illicit trade. Instead, DTOs adjust in a calculating manner to these operations to ensure that their illegal products reach consumer marketplaces, which is congruent with the rational choice theoretical perspective. Copyright © 2018 Elsevier B.V. All rights reserved.

Drug-Induced Acute Myocardial Infarction: Identifying ‘Prime Suspects’ from Electronic Healthcare Records-Based Surveillance System

PubMed Central

Coloma, Preciosa M.; Schuemie, Martijn J.; Trifirò, Gianluca; Furlong, Laura; van Mulligen, Erik; Bauer-Mehren, Anna; Avillach, Paul; Kors, Jan; Sanz, Ferran; Mestres, Jordi; Oliveira, José Luis; Boyer, Scott; Helgee, Ernst Ahlberg; Molokhia, Mariam; Matthews, Justin; Prieto-Merino, David; Gini, Rosa; Herings, Ron; Mazzaglia, Giampiero; Picelli, Gino; Scotti, Lorenza; Pedersen, Lars; van der Lei, Johan; Sturkenboom, Miriam

2013-01-01

Background Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in ‘real-world’ settings. Objective To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. Methods Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996–2010. Primary care physicians’ medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. Results Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs (‘prime suspects’): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. Limitations Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. Conclusion A strategy to identify potentially drug-induced AMI from electronic healthcare data has

A systematic approach to identify therapeutic effects of natural products based on human metabolite information.

PubMed

Noh, Kyungrin; Yoo, Sunyong; Lee, Doheon

2018-06-13

Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods.

Alcohol effects on drug-nutrient interactions.

PubMed

Seitz, H K

1985-01-01

The interaction of ethanol with drugs and xenobiotics is complex because ethanol can affect any of the following steps; absorption, plasma protein binding, hepatic blood flow, distribution, hepatic uptake of drugs, and phase I and II hepatic metabolism. The ingestion of ethanol can lead to malabsorption of a variety of nutrients and can modify the absorption of various drugs. High concentrations of ethanol in conjunction with aspirin causes gastric mucosal damage. The principal effect of acute ethanol ingestion on drug metabolism is inhibition of microsomal drug metabolism. The synergistic effects of ethanol on central nervous system depressants can be explained by this mechanism. In contrast, chronic ethanol consumption increases mixed function oxidation and drug metabolism. The cross tolerance between ethanol and sedatives in chronic alcoholics may be due to this effect of alcohol. In addition, enhanced production of hepatotoxic products from certain drugs and xenobiotics and an increased activation of procarcinogens to carcinogens can result from this microsomal induction. The increased susceptibility to hepatotoxins and the enhanced carcinogenesis in the alcoholic may be explained by this fact. Other effects of the interaction between drugs and ethanol are the result of changes in organ susceptibility, best demonstrated for the central nervous system. Subsequently, the presence of liver disease has a great effect on drug metabolism in alcoholics.

Evaluation of the effects of a designated program on illegal drug cessation among adolescents who experiment with drugs.

PubMed

Chang, Chiu-Ching; Liao, Jung-Yu; Huang, Chiu-Mieh; Hsu, Hsiao-Pei; Chen, Chih-Che; Guo, Jong-Long

2018-01-16

Studies indicate that adolescent-onset drug users experience a greater likelihood of dependence that continues into adulthood. The importance of early intervention was evident in treating adolescents before their substance use progressed. We examined the effectiveness of an intervention program that prevents students who experiment with drugs from reusing them. The study was based on 10 out of 18 invited schools that were randomly assigned to either the intervention group (5 schools, n = 43) or the comparison group (5 schools, n = 41). The intervention group received an E-course program that comprised a main intervention course (12 sessions) and a booster course (2 sessions). By reducing the burden of teaching content during the 14 sessions, the in-class counselor had opportunities for face-to-face discussions with students on their ambivalence toward quitting illegal drugs. The comparison group received the conventional didactic drug prevention course (2 sessions). Outcomes in terms of stress management, refusal skills, pros of drug use, cons of drug use, and drug use resistance self-efficacy were measured via structured questionnaires conducted thrice: at baseline, after the main intervention sessions, and after the booster sessions. A linear mixed model (LMM) was employed to investigate the effects of time and groups on the outcome variables with group, time, and group × time as fixed effects. Subjects and schools were selected as random effects in order to consider both within-subject and within-school correlations. There was a significant group × time interaction with regard to stress management, refusal skills, pros of drug use, and drug use resistance self-efficacy, excluding cons of drug use. The intervention group displayed better stress management compared to the comparison group after the booster intervention. Similar between-group differences were identified in that the intervention group displayed better refusal skills and drug use

A yeast-based assay identifies drugs that interfere with immune evasion of the Epstein-Barr virus.

PubMed

Voisset, Cécile; Daskalogianni, Chrysoula; Contesse, Marie-Astrid; Mazars, Anne; Arbach, Hratch; Le Cann, Marie; Soubigou, Flavie; Apcher, Sébastien; Fåhraeus, Robin; Blondel, Marc

2014-04-01

Epstein-Barr virus (EBV) is tightly associated with certain human cancers, but there is as yet no specific treatment against EBV-related diseases. The EBV-encoded EBNA1 protein is essential to maintain viral episomes and for viral persistence. As such, EBNA1 is expressed in all EBV-infected cells, and is highly antigenic. All infected individuals, including individuals with cancer, have CD8(+) T cells directed towards EBNA1 epitopes, yet the immune system fails to detect and destroy cells harboring the virus. EBV immune evasion depends on the capacity of the Gly-Ala repeat (GAr) domain of EBNA1 to inhibit the translation of its own mRNA in cis, thereby limiting the production of EBNA1-derived antigenic peptides presented by the major histocompatibility complex (MHC) class I pathway. Here we establish a yeast-based assay for monitoring GAr-dependent inhibition of translation. Using this assay we identify doxorubicin (DXR) as a compound that specifically interferes with the GAr effect on translation in yeast. DXR targets the topoisomerase-II-DNA complexes and thereby causes genomic damage. We show, however, that the genotoxic effect of DXR and various analogs thereof is uncoupled from the effect on GAr-mediated translation control. This is further supported by the observation that etoposide and teniposide, representing another class of topoisomerase-II-DNA targeting drugs, have no effect on GAr-mediated translation control. DXR and active analogs stimulate, in a GAr-dependent manner, EBNA1 expression in mammalian cells and overcome GAr-dependent restriction of MHC class I antigen presentation. These results validate our approach as an effective high-throughput screening assay to identify drugs that interfere with EBV immune evasion and, thus, constitute candidates for treating EBV-related diseases, in particular EBV-associated cancers.

Fast dissolving drug-drug eutectics with improved compressibility and synergistic effects.

PubMed

Thipparaboina, Rajesh; Thumuri, Dinesh; Chavan, Rahul; Naidu, V G M; Shastri, Nalini R

2017-06-15

Combinational therapy has become increasingly popular in recent times due to various advantages like greater therapeutic effect, reduced number of prescriptions, lower administrative costs, and an increase in patient compliance. Drug-drug multicomponent adducts could help in combination of drugs at supramolecular level. Two drug-drug eutectics of etodolac with paracetamol (EP) and etodolac with propranolol hydrochloride (EPHC) were successfully designed and synthesized for the first time. These eutectics significantly improved dissolution and material properties. A 6 to 9 fold enhancement in % dissolution efficiency was found at 1min suggesting the fast dissolving capabilities of the eutectic mixtures when compared to plain drug. In addition, eutectic mixtures have shown improved hardness compared to plain drugs. EP and EPHC have shown around 5 fold and 3 fold improvements in hardness respectively at 10MPa when compared to plain etodolac. Cell culture studies have shown improved effects of EP. Western blotting analysis revealed that the said combination successfully reduced various inflammatory mediators like TNF-α, COX-2 and IL-6. Whereas, the eutectic combination EPHC has shown enhanced cytotoxic effects with synergistic combination index and favorable dose reduction index. The generated multi-component systems EP and EPHC with fast dissolving capabilities, improved hardness at lower pressures and synergistic effects represent prospective combinations for effective treatment of osteoarthritis and cancer chemotherapy respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

[Machine Learning-based Prediction of Seizure-inducing Action as an Adverse Drug Effect].

PubMed

Gao, Mengxuan; Sato, Motoshige; Ikegaya, Yuji

2018-01-01

　During the preclinical research period of drug development, animal testing is widely used to help screen out a drug's dangerous side effects. However, it remains difficult to predict side effects within the central nervous system. Here, we introduce a machine learning-based in vitro system designed to detect seizure-inducing side effects before clinical trial. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices that were bath-perfused with each of 14 different drugs, and at 5 different concentrations of each drug. For each of these experimental conditions, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs) that induced seizure-like events, and identified diphenhydramine, enoxacin, strychnine and theophylline as "seizure-inducing" drugs, which have indeed been reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to pre-clinically detect seizure-inducing side effects of drugs.

Drug policy: making effective drugs available without bankrupting the healthcare system.

PubMed

Laupacis, Andreas; Anderson, Geoffrey; O'Brien, Bernie

2002-01-01

To the extent possible, drug policy should be based upon good quality evidence. This must extend beyond the traditional focus on efficacy and safety in carefully selected patients, to evidence about real-world effectiveness, cost-effectiveness and safety of drugs. This paper will consider methods of improving the quality of the evidence currently available, and the implications of requiring that evidence. Historically, there has been a direct link between research evidence and policy at the level of licensing - drugs are only made available after they have been shown to be safe and efficacious in well-designed and independently assessed research studies. We propose that this reliance on evidence be logically extended to cover the formulary inclusion and post-marketing surveillance aspects of modern prescription drug policy. More specifically we propose that the decision to initially list a drug on a benefit formulary be based on evidence from relevant head-to-head comparisons and well-designed cost-effectiveness analyses. This evidence would be produced by industry in cooperation with independent peer-reviewed funding agencies. Drugs could only be added to a formulary if they met specific predetermined criteria, and drugs could be removed as superior alternatives became available. The provincial governments are monopsony buyers of medicines, and they wield the power to determine public payer "market access'for medicines. This power (within and across provinces) could be used more effectively to negotiate price in the context of reimbursement. The effect of different methods of influencing prescribing (e.g., 'limited access?) upon drug utilization and patient outcomes should be rigorously assessed, including the randomization of groups of patients or communities to different strategies. We also propose that all drugs on the formulary would be subject to a well-designed post-marketing surveillance program. This program would build on the existing passive reporting of

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

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

An Ensemble Approach for Drug Side Effect Prediction

PubMed Central

Jahid, Md Jamiul; Ruan, Jianhua

2014-01-01

In silico prediction of drug side-effects in early stage of drug development is becoming more popular now days, which not only reduces the time for drug design but also reduces the drug development costs. In this article we propose an ensemble approach to predict drug side-effects of drug molecules based on their chemical structure. Our idea originates from the observation that similar drugs have similar side-effects. Based on this observation we design an ensemble approach that combine the results from different classification models where each model is generated by a different set of similar drugs. We applied our approach to 1385 side-effects in the SIDER database for 888 drugs. Results show that our approach outperformed previously published approaches and standard classifiers. Furthermore, we applied our method to a number of uncharacterized drug molecules in DrugBank database and predict their side-effect profiles for future usage. Results from various sources confirm that our method is able to predict the side-effects for uncharacterized drugs and more importantly able to predict rare side-effects which are often ignored by other approaches. The method described in this article can be useful to predict side-effects in drug design in an early stage to reduce experimental cost and time. PMID:25327524

In Silico Repositioning-Chemogenomics Strategy Identifies New Drugs with Potential Activity against Multiple Life Stages of Schistosoma mansoni

PubMed Central

Neves, Bruno J.; Braga, Rodolpho C.; Bezerra, José C. B.; Cravo, Pedro V. L.; Andrade, Carolina H.

2015-01-01

Morbidity and mortality caused by schistosomiasis are serious public health problems in developing countries. Because praziquantel is the only drug in therapeutic use, the risk of drug resistance is a concern. In the search for new schistosomicidal drugs, we performed a target-based chemogenomics screen of a dataset of 2,114 proteins to identify drugs that are approved for clinical use in humans that may be active against multiple life stages of Schistosoma mansoni. Each of these proteins was treated as a potential drug target, and its amino acid sequence was used to interrogate three databases: Therapeutic Target Database (TTD), DrugBank and STITCH. Predicted drug-target interactions were refined using a combination of approaches, including pairwise alignment, conservation state of functional regions and chemical space analysis. To validate our strategy, several drugs previously shown to be active against Schistosoma species were correctly predicted, such as clonazepam, auranofin, nifedipine, and artesunate. We were also able to identify 115 drugs that have not yet been experimentally tested against schistosomes and that require further assessment. Some examples are aprindine, gentamicin, clotrimazole, tetrabenazine, griseofulvin, and cinnarizine. In conclusion, we have developed a systematic and focused computer-aided approach to propose approved drugs that may warrant testing and/or serve as lead compounds for the design of new drugs against schistosomes. PMID:25569258

An enhanced Petri-net model to predict synergistic effects of pairwise drug combinations from gene microarray data.

PubMed

Jin, Guangxu; Zhao, Hong; Zhou, Xiaobo; Wong, Stephen T C

2011-07-01

Prediction of synergistic effects of drug combinations has traditionally been relied on phenotypic response data. However, such methods cannot be used to identify molecular signaling mechanisms of synergistic drug combinations. In this article, we propose an enhanced Petri-Net (EPN) model to recognize the synergistic effects of drug combinations from the molecular response profiles, i.e. drug-treated microarray data. We addressed the downstream signaling network of the targets for the two individual drugs used in the pairwise combinations and applied EPN to the identified targeted signaling network. In EPN, drugs and signaling molecules are assigned to different types of places, while drug doses and molecular expressions are denoted by color tokens. The changes of molecular expressions caused by treatments of drugs are simulated by two actions of EPN: firing and blasting. Firing is to transit the drug and molecule tokens from one node or place to another, and blasting is to reduce the number of molecule tokens by drug tokens in a molecule node. The goal of EPN is to mediate the state characterized by control condition without any treatment to that of treatment and to depict the drug effects on molecules by the drug tokens. We applied EPN to our generated pairwise drug combination microarray data. The synergistic predictions using EPN are consistent with those predicted using phenotypic response data. The molecules responsible for the synergistic effects with their associated feedback loops display the mechanisms of synergism. The software implemented in Python 2.7 programming language is available from request. stwong@tmhs.org.

Effects of acute doses of prosocial drugs methamphetamine and alcohol on plasma oxytocin levels.

PubMed

Bershad, Anya K; Kirkpatrick, Matthew G; Seiden, Jacob A; de Wit, Harriet

2015-06-01

Many drugs, including alcohol and stimulants, demonstrably increase sociability and verbal interaction and are recreationally consumed in social settings. One drug, 3,4-methylenedioxymethamphetamine (MDMA, ecstasy), seems to produce its prosocial effects by increasing plasma oxytocin levels, and the oxytocin system has been implicated in responses to several other drugs of abuse. Here, we sought to investigate the effects of 2 other "social" drugs on plasma oxytocin levels--methamphetamine and alcohol. Based on their shared capacity to enhance sociability, we hypothesized that both methamphetamine and alcohol would increase plasma oxytocin levels. In study 1, 11 healthy adult volunteers attended 3 sessions during which they received methamphetamine (10 mg or 20 mg) or placebo under double-blind conditions. Subjective drug effects, cardiovascular effects, and plasma oxytocin levels were measured at regular intervals throughout the sessions. In study 2, 8 healthy adult volunteers attended a single session during which they received 1 beverage containing placebo, and then a beverage containing alcohol (0.8 g/kg). Subjective effects, breath alcohol levels, and plasma oxytocin levels were measured at regular intervals. Both methamphetamine and alcohol produced their expected physiological and subjective effects, but neither of these drugs increased plasma oxytocin levels. The neurobiological mechanisms mediating the prosocial effects of drugs such as alcohol and methamphetamine remain to be identified.

An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

PubMed Central

Naveed, Hammad; Hameed, Umar S.; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

2015-01-01

Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of 11 drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the peroxisome proliferator-activated receptor gamma and the oncogene B-cell lymphoma 2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development. Availability and implementation: The program, datasets and results are freely available to academic users at http://sfb.kaust.edu.sa/Pages/Software.aspx. Contact: xin.gao@kaust.edu.sa and stefan.arold@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26286808

Identifying injection drug use and estimating population size of people who inject drugs using healthcare administrative datasets.

PubMed

Janjua, Naveed Zafar; Islam, Nazrul; Kuo, Margot; Yu, Amanda; Wong, Stanley; Butt, Zahid A; Gilbert, Mark; Buxton, Jane; Chapinal, Nuria; Samji, Hasina; Chong, Mei; Alvarez, Maria; Wong, Jason; Tyndall, Mark W; Krajden, Mel

2018-05-01

Large linked healthcare administrative datasets could be used to monitor programs providing prevention and treatment services to people who inject drugs (PWID). However, diagnostic codes in administrative datasets do not differentiate non-injection from injection drug use (IDU). We validated algorithms based on diagnostic codes and prescription records representing IDU in administrative datasets against interview-based IDU data. The British Columbia Hepatitis Testers Cohort (BC-HTC) includes ∼1.7 million individuals tested for HCV/HIV or reported HBV/HCV/HIV/tuberculosis cases in BC from 1990 to 2015, linked to administrative datasets including physician visit, hospitalization and prescription drug records. IDU, assessed through interviews as part of enhanced surveillance at the time of HIV or HCV/HBV diagnosis from a subset of cases included in the BC-HTC (n = 6559), was used as the gold standard. ICD-9/ICD-10 codes for IDU and injecting-related infections (IRI) were grouped with records of opioid substitution therapy (OST) into multiple IDU algorithms in administrative datasets. We assessed the performance of IDU algorithms through calculation of sensitivity, specificity, positive predictive, and negative predictive values. Sensitivity was highest (90-94%), and specificity was lowest (42-73%) for algorithms based either on IDU or IRI and drug misuse codes. Algorithms requiring both drug misuse and IRI had lower sensitivity (57-60%) and higher specificity (90-92%). An optimal sensitivity and specificity combination was found with two medical visits or a single hospitalization for injectable drugs with (83%/82%) and without OST (78%/83%), respectively. Based on algorithms that included two medical visits, a single hospitalization or OST records, there were 41,358 (1.2% of 11-65 years individuals in BC) recent PWID in BC based on health encounters during 3- year period (2013-2015). Algorithms for identifying PWID using diagnostic codes in linked administrative

How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.

PubMed

Lecca, Paola

2018-01-01

We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of

Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets.

PubMed

Vasaikar, Suhas; Bhatia, Pooja; Bhatia, Partap G; Chu Yaiw, Koon

2016-11-21

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing efficiency against treatment.

[Failure mode and effects analysis on computerized drug prescriptions].

PubMed

Paredes-Atenciano, J A; Roldán-Aviña, J P; González-García, Mercedes; Blanco-Sánchez, M C; Pinto-Melero, M A; Pérez-Ramírez, C; Calvo Rubio-Burgos, Miguel; Osuna-Navarro, F J; Jurado-Carmona, A M

2015-01-01

To identify and analyze errors in drug prescriptions of patients treated in a "high resolution" hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in "unspecified route of administration" and "dosage unspecified", with no significant decreases observed in the second phase, although it did detect, "incorrect dosing time", "contraindication due to drug allergy", "wrong patient" or "duplicate prescription", which resulted in the improvement of prescriptions. Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network.

PubMed

Roider, Helge G; Pavlova, Nadia; Kirov, Ivaylo; Slavov, Stoyan; Slavov, Todor; Uzunov, Zlatyo; Weiss, Bertram

2014-03-11

Information about drug-target relations is at the heart of drug discovery. There are now dozens of databases providing drug-target interaction data with varying scope, and focus. Therefore, and due to the large chemical space, the overlap of the different data sets is surprisingly small. As searching through these sources manually is cumbersome, time-consuming and error-prone, integrating all the data is highly desirable. Despite a few attempts, integration has been hampered by the diversity of descriptions of compounds, and by the fact that the reported activity values, coming from different data sets, are not always directly comparable due to usage of different metrics or data formats. We have built Drug2Gene, a knowledge base, which combines the compound/drug-gene/protein information from 19 publicly available databases. A key feature is our rigorous unification and standardization process which makes the data truly comparable on a large scale, allowing for the first time effective data mining in such a large knowledge corpus. As of version 3.2, Drug2Gene contains 4,372,290 unified relations between compounds and their targets most of which include reported bioactivity data. We extend this set with putative (i.e. homology-inferred) relations where sufficient sequence homology between proteins suggests they may bind to similar compounds. Drug2Gene provides powerful search functionalities, very flexible export procedures, and a user-friendly web interface. Drug2Gene v3.2 has become a mature and comprehensive knowledge base providing unified, standardized drug-target related information gathered from publicly available data sources. It can be used to integrate proprietary data sets with publicly available data sets. Its main goal is to be a 'one-stop shop' to identify tool compounds targeting a given gene product or for finding all known targets of a drug. Drug2Gene with its integrated data set of public compound-target relations is freely accessible without

Identifying Patients With Problematic Drug Use in the Emergency Department: Results of a Multisite Study

PubMed Central

Konstantopoulos, Wendy L. Macias; Dreifuss, Jessica A.; McDermott, Katherine A.; Parry, Blair Alden; Howell, Melissa L.; Mandler, Raul N.; Fitzmaurice, Garrett M.; Bogenschutz, Michael P.; Weiss, Roger D.

2014-01-01

Study objective Drug-related emergency department (ED) visits have steadily increased, with substance users relying heavily on the ED for medical care. The present study aims to identify clinical correlates of problematic drug use that would facilitate identification of ED patients in need of substance use treatment. Methods Using previously validated tests, 15,224 adult ED patients across 6 academic institutions were prescreened for drug use as part of a large randomized prospective trial. Data for 3,240 participants who reported drug use in the past 30 days were included. Self-reported variables related to demographics, substance use, and ED visit were examined to determine their correlative value for problematic drug use. Results Of the 3,240 patients, 2,084 (64.3%) met criteria for problematic drug use (Drug Abuse Screening Test score ≥3). Age greater than or equal to 30 years, tobacco smoking, daily or binge alcohol drinking, daily drug use, primary noncannabis drug use, resource-intense ED triage level, and perceived drug-relatedness of ED visit were highly correlated with problematic drug use. Among primary cannabis users, correlates of problematic drug use were age younger than 30 years, tobacco smoking, binge drinking, daily drug use, and perceived relatedness of the ED visit to drug use. Conclusion Clinical correlates of drug use problems may assist the identification of ED patients who would benefit from comprehensive screening, intervention, and referral to treatment. A clinical decision rule is proposed. The correlation between problematic drug use and resource-intense ED triage levels suggests that ED-based efforts to reduce the unmet need for substance use treatment may help decrease overall health care costs. PMID:24999283

Studying a Drug-like, RNA-Focused Small Molecule Library Identifies Compounds That Inhibit RNA Toxicity in Myotonic Dystrophy.

PubMed

Rzuczek, Suzanne G; Southern, Mark R; Disney, Matthew D

2015-12-18

There are many RNA targets in the transcriptome to which small molecule chemical probes and lead therapeutics are desired. However, identifying compounds that bind and modulate RNA function in cellulo is difficult. Although rational design approaches have been developed, they are still in their infancies and leave many RNAs "undruggable". In an effort to develop a small molecule library that is biased for binding RNA, we computationally identified "drug-like" compounds from screening collections that have favorable properties for binding RNA and for suitability as lead drugs. As proof-of-concept, this collection was screened for binding to and modulating the cellular dysfunction of the expanded repeating RNA (r(CUG)(exp)) that causes myotonic dystrophy type 1. Hit compounds bind the target in cellulo, as determined by the target identification approach Competitive Chemical Cross-Linking and Isolation by Pull-down (C-ChemCLIP), and selectively improve several disease-associated defects. The best compounds identified from our 320-member library are more potent in cellulo than compounds identified by high-throughput screening (HTS) campaigns against this RNA. Furthermore, the compound collection has a higher hit rate (9% compared to 0.01-3%), and the bioactive compounds identified are not charged; thus, RNA can be "drugged" with compounds that have favorable pharmacological properties. Finally, this RNA-focused small molecule library may serve as a useful starting point to identify lead "drug-like" chemical probes that affect the biological (dys)function of other RNA targets by direct target engagement.

Mood effects of antiepileptic drugs.

PubMed

Reijs, Rianne; Aldenkamp, Albert P; De Krom, Marc

2004-02-01

This article reviews our knowledge about a specific subgroup of chronic CNS-related side effects of antiepileptic drugs (AED) treatment, i.e., the effects of AEDs on mood. In line with a recent hypothesis, using the experience of AED treatment in psychiatry, we examined whether mood effects are related to the known anticonvulsant mechanisms of action of the AEDs. Specifically we examined whether AEDs, acting through potentiation of GABAergic neurotransmitter release, have "sedating" effects on mood, whereas AEDs that act through the reduction of excitatory glutamate neurotransmitter release have "activating" effects on mood. The results of this review yield evidence that there are relationships between the known anticonvulsant mechanisms of action of the AEDs and mood effects. Mood effects occur especially when the drugs have a sustained effect on neuronal mechanisms, in particular when the inhibitory or excitatory neurotransmitter release is altered. Drugs with "use-dependent" impact on sodium or calcium channels probably have a more transient impact and do not lead to interictal stable mood effects. Drugs with multiple mechanisms of action seem to combine a favorable efficacy profile with an increased risk of severe mood problems. The quality of the evidence, however, is not conclusive and there are many paradoxical results. One reason for this lack of "fit" may be the use in this review of a simplified classification, based only on the predominant mechanism of action to classify a drug. Only a limited number of AEDs (ethosuximide, tiagabine) are characterized by a single anticonvulsant mechanism of action. Probably more detailed coupling of mechanisms of action (e.g., inspecting the type and route of impact on GABA release) and mood effects may give less confusing results. The use of magnetic resonance imaging techniques such as spectroscopy may provide interesting results.

Neurocircuitry for modeling drug effects.

PubMed

Noori, Hamid R; Spanagel, Rainer; Hansson, Anita C

2012-09-01

The identification and functional understanding of the neurocircuitry that mediates alcohol and drug effects that are relevant for the development of addictive behavior is a fundamental challenge in addiction research. Here we introduce an assumption-free construction of a neurocircuitry that mediates acute and chronic drug effects on neurotransmitter dynamics that is solely based on rodent neuroanatomy. Two types of data were considered for constructing the neurocircuitry: (1) information on the cytoarchitecture and neurochemical connectivity of each brain region of interest obtained from different neuroanatomical techniques; (2) information on the functional relevance of each region of interest with respect to alcohol and drug effects. We used mathematical data mining and hierarchical clustering methods to achieve the highest standards in the preprocessing of these data. Using this approach, a dynamical network of high molecular and spatial resolution containing 19 brain regions and seven neurotransmitter systems was obtained. Further graph theoretical analysis suggests that the neurocircuitry is connected and cannot be separated into further components. Our analysis also reveals the existence of a principal core subcircuit comprised of nine brain regions: the prefrontal cortex, insular cortex, nucleus accumbens, hypothalamus, amygdala, thalamus, substantia nigra, ventral tegmental area and raphe nuclei. Finally, by means of algebraic criteria for synchronizability of the neurocircuitry, the suitability for in silico modeling of acute and chronic drug effects is indicated. Indeed, we introduced as an example a dynamical system for modeling the effects of acute ethanol administration in rats and obtained an increase in dopamine release in the nucleus accumbens-a hallmark of drug reinforcement-to an extent similar to that seen in numerous microdialysis studies. We conclude that the present neurocircuitry provides a structural and dynamical framework for large

A screen to identify drug resistant variants to target-directed anti-cancer agents

PubMed Central

Azam, Mohammad; Raz, Tal; Nardi, Valentina; Opitz, Sarah L.

2003-01-01

The discovery of oncogenes and signal transduction pathways important for mitogenesis has triggered the development of target-specific small molecule anti-cancer compounds. As exemplified by imatinib (Gleevec), a specific inhibitor of the Chronic Myeloid Leukemia (CML)-associated Bcr-Abl kinase, these agents promise impressive activity in clinical trials, with low levels of clinical toxicity. However, such therapy is susceptible to the emergence of drug resistance due to amino acid substitutions in the target protein. Defining the spectrum of such mutations is important for patient monitoring and the design of next-generation inhibitors. Using imatinib and BCR/ABL as a paradigm for a drug-target pair, we recently reported a retroviral vector-based screening strategy to identify the spectrum of resistance-conferring mutations. Here we provide a detailed methodology for the screen, which can be generally applied to any drug-target pair. PMID:14615817

New drug candidates for liposomal delivery identified by computer modeling of liposomes' remote loading and leakage.

PubMed

Cern, Ahuva; Marcus, David; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2017-04-28

Remote drug loading into nano-liposomes is in most cases the best method for achieving high concentrations of active pharmaceutical ingredients (API) per nano-liposome that enable therapeutically viable API-loaded nano-liposomes, referred to as nano-drugs. This approach also enables controlled drug release. Recently, we constructed computational models to identify APIs that can achieve the desired high concentrations in nano-liposomes by remote loading. While those previous models included a broad spectrum of experimental conditions and dealt only with loading, here we reduced the scope to the molecular characteristics alone. We model and predict API suitability for nano-liposomal delivery by fixing the main experimental conditions: liposome lipid composition and size to be similar to those of Doxil® liposomes. On that basis, we add a prediction of drug leakage from the nano-liposomes during storage. The latter is critical for having pharmaceutically viable nano-drugs. The "load and leak" models were used to screen two large molecular databases in search of candidate APIs for delivery by nano-liposomes. The distribution of positive instances in both loading and leakage models was similar in the two databases screened. The screening process identified 667 molecules that were positives by both loading and leakage models (i.e., both high-loading and stable). Among them, 318 molecules received a high score in both properties and of these, 67 are FDA-approved drugs. This group of molecules, having diverse pharmacological activities, may be the basis for future liposomal drug development. Copyright © 2017 Elsevier B.V. All rights reserved.

Potential risks resulting from fruit/vegetable-drug interactions: effects on drug-metabolizing enzymes and drug transporters.

PubMed

Rodríguez-Fragoso, Lourdes; Martínez-Arismendi, José Luis; Orozco-Bustos, Danae; Reyes-Esparza, Jorge; Torres, Eliseo; Burchiel, Scott W

2011-05-01

It has been well established that complex mixtures of phytochemicals in fruits and vegetables can be beneficial for human health. Moreover, it is becoming increasingly apparent that phytochemicals can influence the pharmacological activity of drugs by modifying their absorption characteristics through interactions with drug transporters as well as drug-metabolizing enzyme systems. Such effects are more likely to occur in the intestine and liver, where high concentrations of phytochemicals may occur. Alterations in cytochrome P450 and other enzyme activities may influence the fate of drugs subject to extensive first-pass metabolism. Although numerous studies of nutrient-drug interactions have been published and systematic reviews and meta-analyses of these studies are available, no generalizations on the effect of nutrient-drug interactions on drug bioavailability are currently available. Several publications have highlighted the unintended consequences of the combined use of nutrients and drugs. Many phytochemicals have been shown to have pharmacokinetic interactions with drugs. The present review is limited to commonly consumed fruits and vegetables with significant beneficial effects as nutrients and components in folk medicine. Here, we discuss the phytochemistry and pharmacokinetic interactions of the following fruit and vegetables: grapefruit, orange, tangerine, grapes, cranberry, pomegranate, mango, guava, black raspberry, black mulberry, apple, broccoli, cauliflower, watercress, spinach, tomato, carrot, and avocado. We conclude that our knowledge of the potential risk of nutrient-drug interactions is still limited. Therefore, efforts to elucidate potential risks resulting from food-drug interactions should be intensified in order to prevent undesired and harmful clinical consequences. © 2011 Institute of Food Technologists®

A Text Searching Tool to Identify Patients with Idiosyncratic Drug-Induced Liver Injury.

PubMed

Heidemann, Lauren; Law, James; Fontana, Robert J

2017-03-01

Idiosyncratic drug-induced liver injury (DILI) is an uncommon but important cause of liver disease that is challenging to diagnose and identify in the electronic medical record (EMR). To develop an accurate, reliable, and efficient method of identifying patients with bonafide DILI in an EMR system. In total, 527,000 outpatient and ER encounters in an EPIC-based EMR were searched for potential DILI cases attributed to eight drugs. A searching algorithm that extracted 200 characters of text around 14 liver injury terms in the EMR were extracted and collated. Physician investigators reviewed the data outputs and used standardized causality assessment methods to adjudicate the potential DILI cases. A total of 101 DILI cases were identified from the 2564 potential DILI cases that included 62 probable DILI cases, 25 possible DILI cases, nine historical DILI cases, and five allergy-only cases. Elimination of the term "liver disease" from the search strategy improved the search recall from 4 to 19 %, while inclusion of the four highest yield liver injury terms further improved the positive predictive value to 64 % but reduced the overall case detection rate by 47 %. RUCAM scores of the 57 probable DILI cases were generally high and concordant with expert opinion causality assessment scores. A novel text searching tool was developed that identified a large number of DILI cases from a widely used EMR system. A computerized extraction of dictated text followed by the manual review of text snippets can rapidly identify bona fide cases of idiosyncratic DILI.

Side effects associated with anti-HIV drugs.

PubMed

Highleyman, L

1998-04-01

Many side effects are associated with the use of anti-HIV drugs, impacting the development of drug resistance and the quality of life for HIV-patients. Concern about side effects is a primary factor in deterring people from beginning HIV therapy. Frequency and severity of side effects vary greatly, but they are frequently more common and severe in people who are taking a new drug or who have advanced HIV disease. Information on side effects comes largely from clinical trials; however, many side effects are not discovered until the drug has been approved and used by larger numbers of people. Side effects vary from serious toxicities that require stopping treatment to uncomfortable or annoying side effects that interfere with daily life. A table categorizes the four major side effects (nausea, fever, skin rash, and fatigue) and divides them into grades that describe their intensity. A chart lists the side effects associated with specific anti-HIV drugs. Suggestions for managing side effects are included.

Effect of drug reminder packaging on medication adherence: a systematic review revealing research gaps

PubMed Central

2014-01-01

Background This was a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Evidence mapping was used to reveal the effect of drug reminder packaging on medication adherence, to identify research gaps and to make suggestions for future research. Methods PubMed, Embase, CINAHL and PsycINFO were searched with an end date of September 2013 using the Medical Subject Headings (MeSH) term ‘medication adherence’ and 20 different search terms for ‘drug reminder packaging’, limited to the English and German languages. Additional references were identified through cross-referencing. All prospective controlled trials with an intervention using drug reminder packaging for patients taking at least one medication without the assistance of a health-care professional were included in the evidence mapping of the effect of drug reminder packaging on adherence and outcomes according to the Economic, Clinical and Humanistic Outcomes (ECHO) model. Results A total of 30 studies met the inclusion criteria: 10 randomized controlled trials, 19 controlled clinical trials and 1 cohort study. Drug reminder packaging had a significant effect on at least one adherence parameter in 17 studies (57%). The methodological quality was strong in five studies. Two studies provided complete information. Clear research gaps emerged. Conclusions Overall, the studies showed a positive effect of drug reminder packaging on adherence and clinical outcomes. However, poor reporting and important gaps like missing humanistic and economic outcomes and neglected safety issues limit the drawing of firm conclusions. Suggestions are made for future research. PMID:24661495

A Practical Bayesian Design to Identify the Maximum Tolerated Dose Contour for Drug Combination Trials

PubMed Central

Zhang, Liangcai; Yuan, Ying

2016-01-01

Drug combination therapy has become the mainstream approach to cancer treatment. One fundamental feature that makes combination trials different from single-agent trials is the existence of the maximum tolerated dose (MTD) contour, i.e., multiple MTDs. As a result, unlike single-agent phase I trials, which aim to find a single MTD, it is often of interest to find the MTD contour for combination trials. We propose a new dose-finding design, the waterfall design, to find the MTD contour for drug combination trials. Taking the divide-and-conquer strategy, the waterfall design divides the task of finding the MTD contour into a sequence of one-dimensional dose-finding processes, known as subtrials. The subtrials are conducted sequentially in a certain order, such that the results of each subtrial will be used to inform the design of subsequent subtrials. Such information borrowing allows the waterfall design to explore the two-dimensional dose space efficiently using a limited sample size, and decreases the chance of overdosing and underdosing patients. To accommodate the consideration that doses on the MTD contour may have very different efficacy or synergistic effects due to drug-drug interaction, we further extend our approach to a phase I/II design with the goal of finding the MTD with the highest efficacy. Simulation studies show that the waterfall design is safer and has higher probability of identifying the true MTD contour than some existing designs. The R package “BOIN” to implement the waterfall design is freely available from CRAN. PMID:27580928

Cost-effectiveness and pricing of antibacterial drugs.

PubMed

Verhoef, Talitha I; Morris, Stephen

2015-01-01

Growing resistance to antibacterial agents has increased the need for the development of new drugs to treat bacterial infections. Given increasing pressure on limited health budgets, it is important to study the cost-effectiveness of these drugs, as well as their safety and efficacy, to find out whether or not they provide value for money and should be reimbursed. In this article, we systematically reviewed 38 cost-effectiveness analyses of new antibacterial agents. Most studies showed the new antibacterial drugs were cost-effective compared to older generation drugs. Drug pricing is a complicated process, involving different stakeholders, and has a large influence on cost-effectiveness. Value-based pricing is a method to determine the price of a drug at which it can be cost-effective. It is currently unclear what the influence of value-based pricing will be on the prices of new antibacterial agents, but an important factor will be the definition of 'value', which as well as the impact of the drug on patient health might also include other factors such as wider social impact and the health impact of disease. © 2015 The Authors. Chemical Biology & Drug Design Published by John Wiley & Sons Ltd.

Do preclinical seizure models preselect certain adverse effects of antiepileptic drugs.

PubMed

Meldrum, Brian

2002-06-01

Classical screening tests (maximal electroshock, MES, and threshold pentylenetetrazol, PTZ) employ non-epileptic rodents and identify antiepileptic drugs (AEDs) with mechanisms of action associated with significant CNS side effects. Thus MES identifies drugs acting on Na+ channels that produce cerebellar toxicity. It may be possible to produce novel AEDs more selectively targeted at voltage-sensitive (VS) ion channels. There is little specific evidence for the likely success of this strategy with subunit selective agents targeted at the different VS Na+ channels. Drugs targeted at specific VS Ca++ channels (T, N, P/Q types) may be useful in generalised seizures. There are many as yet unexplored possibilities relating to K+ channels. GABA related drugs acting on PTZ clonic seizures tend to induce sedation and muscle hypotonia. Studies in mice, particularly with knock-in mutations, but also with subunit selective agents acting via the GABA(A) benzodiazepine site, suggest that it is possible to produce agents which do or do not induce particular side effects (sedative, hypnotic, anxiolytic, muscle relaxant, amnesia, anaesthesia). Whether these findings transfer to man has yet to be established. Acquired epilepsy in rodents (e.g. kindling or spontaneous seizures following chemically- or electrically-induced status epilepticus) or acquired epilepsy in man (following prolonged febrile seizures or traumatic brain injury) is associated with multiple changes in the function and subunit composition of ion channels and receptor molecules. Optimal screening of novel AEDs, both for efficacy and side effects, requires models with receptor and ion channel changes similar to those in the target human syndrome.

Identifying mechanism-of-action targets for drugs and probes

PubMed Central

Gregori-Puigjané, Elisabet; Setola, Vincent; Hert, Jérôme; Crews, Brenda A.; Irwin, John J.; Lounkine, Eugen; Marnett, Lawrence; Roth, Bryan L.; Shoichet, Brian K.

2012-01-01

Notwithstanding their key roles in therapy and as biological probes, 7% of approved drugs are purported to have no known primary target, and up to 18% lack a well-defined mechanism of action. Using a chemoinformatics approach, we sought to “de-orphanize” drugs that lack primary targets. Surprisingly, targets could be easily predicted for many: Whereas these targets were not known to us nor to the common databases, most could be confirmed by literature search, leaving only 13 Food and Drug Administration—approved drugs with unknown targets; the number of drugs without molecular targets likely is far fewer than reported. The number of worldwide drugs without reasonable molecular targets similarly dropped, from 352 (25%) to 44 (4%). Nevertheless, there remained at least seven drugs for which reasonable mechanism-of-action targets were unknown but could be predicted, including the antitussives clemastine, cloperastine, and nepinalone; the antiemetic benzquinamide; the muscle relaxant cyclobenzaprine; the analgesic nefopam; and the immunomodulator lobenzarit. For each, predicted targets were confirmed experimentally, with affinities within their physiological concentration ranges. Turning this question on its head, we next asked which drugs were specific enough to act as chemical probes. Over 100 drugs met the standard criteria for probes, and 40 did so by more stringent criteria. A chemical information approach to drug-target association can guide therapeutic development and reveal applications to probe biology, a focus of much current interest. PMID:22711801

A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors

PubMed Central

Jahchan, Nadine S; Dudley, Joel T; Mazur, Pawel K; Flores, Natasha; Yang, Dian; Palmerton, Alec; Zmoos, Anne-Flore; Vaka, Dedeepya; Tran, Kim QT; Zhou, Margaret; Krasinska, Karolina; Riess, Jonathan W; Neal, Joel W; Khatri, Purvesh; Park, Kwon S; Butte, Atul J; Sage, Julien

2013-01-01

Small cell lung cancer (SCLC) is an aggressive neuroendocrine subtype of lung cancer with high mortality. We used a systematic drug-repositioning bioinformatics approach querying a large compendium of gene expression profiles to identify candidate FDA-approved drugs to treat SCLC. We found that tricyclic antidepressants and related molecules potently induce apoptosis in both chemonaïve and chemoresistant SCLC cells in culture, in mouse and human SCLC tumors transplanted into immunocompromised mice, and in endogenous tumors from a mouse model for human SCLC. The candidate drugs activate stress pathways and induce cell death in SCLC cells, at least in part by disrupting autocrine survival signals involving neurotransmitters and their G protein-coupled receptors. The candidate drugs inhibit the growth of other neuroendocrine tumors, including pancreatic neuroendocrine tumors and Merkel cell carcinoma. These experiments identify novel targeted strategies that can be rapidly evaluated in patients with neuroendocrine tumors through the repurposing of approved drugs. PMID:24078773

Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets

PubMed Central

Akala, Hoseah M.; Macharia, Rosaline W.; Juma, Dennis W.; Cheruiyot, Agnes C.; Andagalu, Ben; Brown, Mathew L.; El-Shemy, Hany A.; Nyanjom, Steven G.

2017-01-01

Malaria causes about half a million deaths annually, with Plasmodium falciparum being responsible for 90% of all the cases. Recent reports on artemisinin resistance in Southeast Asia warrant urgent discovery of novel drugs for the treatment of malaria. However, most bioactive compounds fail to progress to treatments due to safety concerns. Drug repositioning offers an alternative strategy where drugs that have already been approved as safe for other diseases could be used to treat malaria. This study screened approved drugs for antimalarial activity using an in silico chemogenomics approach prior to in vitro verification. All the P. falciparum proteins sequences available in NCBI RefSeq were mined and used to perform a similarity search against DrugBank, TTD and STITCH databases to identify similar putative drug targets. Druggability indices of the potential P. falciparum drug targets were obtained from TDR targets database. Functional amino acid residues of the drug targets were determined using ConSurf server which was used to fine tune the similarity search. This study predicted 133 approved drugs that could target 34 P. falciparum proteins. A literature search done at PubMed and Google Scholar showed 105 out of the 133 drugs to have been previously tested against malaria, with most showing activity. For further validation, drug susceptibility assays using SYBR Green I method were done on a representative group of 10 predicted drugs, eight of which did show activity against P. falciparum 3D7 clone. Seven had IC50 values ranging from 1 μM to 50 μM. This study also suggests drug-target association and hence possible mechanisms of action of drugs that did show antiplasmodial activity. The study results validate the use of proteome-wide target similarity approach in identifying approved drugs with activity against P. falciparum and could be adapted for other pathogens. PMID:29088219

Identifying and assessing highly hazardous drugs within quality risk management programs.

PubMed

Sussman, Robert G; Schatz, Anthony R; Kimmel, Tracy A; Ader, Allan; Naumann, Bruce D; Weideman, Patricia A

2016-08-01

Historically, pharmaceutical industry regulatory guidelines have assigned certain active pharmaceutical ingredients (APIs) to various categories of concern, such as "cytotoxic", "hormones", and "steroids". These categories have been used to identify APIs requiring segregation or dedication in order to prevent cross-contamination and protect the quality and safety of drug products. Since these terms were never defined by regulatory authorities, and many novel pharmacological mechanisms challenge these categories, there is a recognized need to modify the historical use of these terms. The application of a risk-based approach using a health-based limit, such as an acceptable daily exposure (ADE), is more appropriate for the development of a Quality Risk Management Program (QRMP) than the use of categories of concern. The toxicological and pharmacological characteristics of these categories are discussed to help identify and prioritize compounds requiring special attention. Controlling airborne concentrations and the contamination of product contact surfaces in accordance with values derived from quantitative risk assessments can prevent adverse effects in workers and patients, regardless of specific categorical designations to which these APIs have been assigned. The authors acknowledge the movement away from placing compounds into categories and, while not yet universal, the importance of basing QRMPs on compound-specific ADEs and risk assessments. Based on the results of a risk assessment, segregation and dedication may also be required for some compounds to prevent cross contamination during manufacture of APIs. Copyright © 2016 Elsevier Inc. All rights reserved.

Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Information Technology-Based Interventions to Improve Drug-Drug Interaction Outcomes: A Systematic Review on Features and Effects.

PubMed

Nabovati, Ehsan; Vakili-Arki, Hasan; Taherzadeh, Zhila; Saberi, Mohammad Reza; Medlock, Stephanie; Abu-Hanna, Ameen; Eslami, Saeid

2017-01-01

The purpose of this systematic review was to identify features and effects of information technology (IT)-based interventions on outcomes related to drug-drug interactions (DDI outcomes). A literature search was conducted in Medline, EMBASE, and the Cochrane Library for published English-language studies. Studies were included if a main outcome was related to DDIs, the intervention involved an IT-based system, and the study design was experimental or observational with controls. Study characteristics, including features and effects of IT-based interventions, were extracted. Nineteen studies comprising five randomized controlled trials (RCT), five non-randomized controlled trials (NRCT) and nine observational studies with controls (OWC) were included. Sixty-four percent of prescriber-directed interventions, and all non-prescriber interventions, were effective. Each of the following characteristics corresponded to groups of studies of which a majority were effective: automatic provision of recommendations within the providers' workflow, intervention at the time of decision-making, integration into other systems, and requiring the reason for not following the recommendations. Only two studies measured clinical outcomes: an RCT that showed no significant improvement and an OWC that showed improvement, but did not statistically assess the effect. Most studies that measured surrogate outcomes (e.g. potential DDIs) and other outcomes (e.g. adherence to alerts) showed improvements. IT-based interventions improve surrogate clinical outcomes and adherence to DDI alerts. However, there is lack of robust evidence about their effectiveness on clinical outcomes. It is recommended that researchers consider the identified features of effective interventions in the design of interventions and evaluate the effectiveness on DDI outcomes, particularly clinical outcomes.

Accounting for the drug life cycle and future drug prices in cost-effectiveness analysis.

PubMed

Hoyle, Martin

2011-01-01

Economic evaluations of health technologies typically assume constant real drug prices and model only the cohort of patients currently eligible for treatment. It has recently been suggested that, in the UK, we should assume that real drug prices decrease at 4% per annum and, in New Zealand, that real drug prices decrease at 2% per annum and at patent expiry the drug price falls. It has also recently been suggested that we should model multiple future incident cohorts. In this article, the cost effectiveness of drugs is modelled based on these ideas. Algebraic expressions are developed to capture all costs and benefits over the entire life cycle of a new drug. The lifetime of a new drug in the UK, a key model parameter, is estimated as 33 years, based on the historical lifetime of drugs in England over the last 27 years. Under the proposed methodology, cost effectiveness is calculated for seven new drugs recently appraised in the UK. Cost effectiveness as assessed in the future is also estimated. Whilst the article is framed in mathematics, the findings and recommendations are also explained in non-mathematical language. The 'life-cycle correction factor' is introduced, which is used to convert estimates of cost effectiveness as traditionally calculated into estimates under the proposed methodology. Under the proposed methodology, all seven drugs appear far more cost effective in the UK than published. For example, the incremental cost-effectiveness ratio decreases by 46%, from £61, 900 to £33, 500 per QALY, for cinacalcet versus best supportive care for end-stage renal disease, and by 45%, from £31,100 to £17,000 per QALY, for imatinib versus interferon-α for chronic myeloid leukaemia. Assuming real drug prices decrease over time, the chance that a drug is publicly funded increases over time, and is greater when modelling multiple cohorts than with a single cohort. Using the methodology (compared with traditional methodology) all drugs in the UK and New

Cost-effectiveness and Pricing of Antibacterial Drugs

PubMed Central

Verhoef, Talitha I; Morris, Stephen

2015-01-01

Growing resistance to antibacterial agents has increased the need for the development of new drugs to treat bacterial infections. Given increasing pressure on limited health budgets, it is important to study the cost-effectiveness of these drugs, as well as their safety and efficacy, to find out whether or not they provide value for money and should be reimbursed. In this article, we systematically reviewed 38 cost-effectiveness analyses of new antibacterial agents. Most studies showed the new antibacterial drugs were cost-effective compared to older generation drugs. Drug pricing is a complicated process, involving different stakeholders, and has a large influence on cost-effectiveness. Value-based pricing is a method to determine the price of a drug at which it can be cost-effective. It is currently unclear what the influence of value-based pricing will be on the prices of new antibacterial agents, but an important factor will be the definition of ‘value’, which as well as the impact of the drug on patient health might also include other factors such as wider social impact and the health impact of disease. PMID:25521641

Prediction of the cause, effects, and prevention of drug-nutrient interactions using attributes and attribute values.

PubMed

Roe, D A

1985-01-01

Drug-nutrient interactions and their adverse outcomes have previously been identified by observation, investigation, and literature reports. Knowing the attributes of the drugs, availability of knowledge base management systems for microcomputer use can facilitate prediction of the mechanism and the effects of drug-nutrient interactions. Examples used to illustrate this approach are prediction of lactose intolerance in drug-induced malabsorption, and prediction of the mechanism responsible for drug-induced flush reactions. In the future we see that there may be many opportunities to use this system further in the investigation of complex drug-nutrient interactions.

Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds.

PubMed

Gao, Mengxuan; Igata, Hideyoshi; Takeuchi, Aoi; Sato, Kaoru; Ikegaya, Yuji

2017-02-01

Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs) that induced seizure-like events and identified diphenhydramine, enoxacin, strychnine and theophylline as "seizure-inducing" drugs, which indeed were reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to detect the seizure-inducing side effects of preclinical drugs. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Effect of drug law enforcement on drug market violence: a systematic review.

PubMed

Werb, Dan; Rowell, Greg; Guyatt, Gordon; Kerr, Thomas; Montaner, Julio; Wood, Evan

2011-03-01

Violence is amongst the primary concerns of communities around the world and research has demonstrated links between violence and the illicit drug trade, particularly in urban settings. Given the growing emphasis on evidence-based policy-making, and the ongoing severe drug market violence in Mexico and other settings, we conducted a systematic review to examine the impacts of drug law enforcement on drug market violence. We conducted a systematic review using Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines. Specifically, we undertook a search of English language electronic databases (Academic Search Complete, PubMed, PsycINFO, EMBASE, Web of Science, Sociological Abstracts, Social Service Abstracts, PAIS International and Lexis-Nexis), the Internet (Google, Google Scholar), and article reference lists, from database inception to January 24, 2011. Overall, 15 studies were identified that evaluated the impact of drug law enforcement on drug market violence, including 11 (73%) longitudinal analyses using linear regression, 2 (13%) mathematical drug market models, and 2 (13%) qualitative studies. Fourteen (93%) studies reported an adverse impact of drug law enforcement on levels of violence. Ten of the 11 (91%) studies employing longitudinal qualitative analyses found a significant association between drug law enforcement and drug market violence. Our findings suggest that increasing drug law enforcement is unlikely to reduce drug market violence. Instead, the existing evidence base suggests that gun violence and high homicide rates may be an inevitable consequence of drug prohibition and that disrupting drug markets can paradoxically increase violence. In this context, and since drug prohibition has not meaningfully reduced drug supply, alternative regulatory models will be required if drug supply and drug market violence are to be meaningfully reduced. Copyright © 2011 Elsevier B.V. All rights reserved.

Effectiveness and safety of drug-eluting stents in Ontario.

PubMed

Tu, Jack V; Bowen, James; Chiu, Maria; Ko, Dennis T; Austin, Peter C; He, Yaohua; Hopkins, Robert; Tarride, Jean-Eric; Blackhouse, Gord; Lazzam, Charles; Cohen, Eric A; Goeree, Ron

2007-10-04

The placement of drug-eluting stents decreases the frequency of repeat revascularization procedures in patients undergoing percutaneous coronary intervention (PCI) in randomized clinical trials. However, there is uncertainty about the effectiveness of drug-eluting stents, and increasing concern about their safety, in routine clinical practice. From the Cardiac Care Network of Ontario's population-based clinical registry of all patients undergoing PCI in Ontario, Canada, we identified a well-balanced cohort of 3751 pairs of patients, matched on the basis of propensity score, who received either bare-metal stents alone or drug-eluting stents alone during an index PCI procedure between December 1, 2003, and March 31, 2005. The primary outcomes of the study were the rates of target-vessel revascularization, myocardial infarction, and death. The 2-year rate of target-vessel revascularization was significantly lower among patients who received drug-eluting stents than among those who received bare-metal stents (7.4% vs. 10.7%, P<0.001). Drug-eluting stents were associated with significant reductions in the rate of target-vessel revascularization among patients with two or three risk factors for restenosis (i.e., presence of diabetes, small vessels [<3 mm in diameter], and long lesions [> or =20 mm]) but not among lower-risk patients. The 3-year mortality rate was significantly higher in the bare-metal-stent group than in the drug-eluting-stent group (7.8% vs. 5.5%, P<0.001), whereas the 2-year rate of myocardial infarction was similar in the two groups (5.2% and 5.7%, respectively; P=0.95). Drug-eluting stents are effective in reducing the need for target-vessel revascularization in patients at highest risk for restenosis, without a significantly increased rate of death or myocardial infarction. Copyright 2007 Massachusetts Medical Society.

Drug and Alcohol Exposed Children: Implications for Special Education for Students Identified as Behaviorally Disordered.

ERIC Educational Resources Information Center

Bauer, Anne M.

1991-01-01

This article reviews the literature on children prenatally exposed to drugs and alcohol, the potential impact on the educational and social services systems, and implications for programing for children identified as behaviorally disordered. (Author/JDD)

Drug Screening Identifies Niclosamide as an Inhibitor of Breast Cancer Stem-Like Cells

PubMed Central

Wang, Yu-Chi; Chao, Tai-Kuang; Chang, Cheng-Chang; Yo, Yi-Te; Yu, Mu-Hsien; Lai, Hung-Cheng

2013-01-01

The primary cause of death from breast cancer is the progressive growth of tumors and resistance to conventional therapies. It is currently believed that recurrent cancer is repopulated according to a recently proposed cancer stem cell hypothesis. New therapeutic strategies that specifically target cancer stem-like cells may represent a new avenue of cancer therapy. We aimed to discover novel compounds that target breast cancer stem-like cells. We used a dye-exclusion method to isolate side population (SP) cancer cells and, subsequently, subjected these SP cells to a sphere formation assay to generate SP spheres (SPS) from breast cancer cell lines. Surface markers, stemness genes, and tumorigenicity were used to test stem properties. We performed a high-throughput drug screening using these SPS. The effects of candidate compounds were assessed in vitro and in vivo. We successfully generated breast cancer SPS with stem-like properties. These SPS were enriched for CD44high (2.8-fold) and CD24low (4-fold) cells. OCT4 and ABCG2 were overexpressed in SPS. Moreover, SPS grew tumors at a density of 103, whereas an equivalent number of parental cells did not initiate tumor formation. A clinically approved drug, niclosamide, was identified from the LOPAC chemical library of 1,258 compounds. Niclosamide downregulated stem pathways, inhibited the formation of spheroids, and induced apoptosis in breast cancer SPS. Animal studies also confirmed this therapeutic effect. The results of this proof-of-principle study may facilitate the development of new breast cancer therapies in the near future. The extension of niclosamide clinical trials is warranted. PMID:24058587

Effect of Lipophilicity and Drug Ionization on Permeation Across Porcine Sublingual Mucosa.

PubMed

Goswami, Tarun; Li, Xiaoling; Jasti, Bhaskara R

2017-01-01

Sublingual route is one of the oldest alternative routes studied for the administration of drugs. However, the effect of physical-chemical properties on drug permeation via this route has not been systemically investigated. The objective of this study was to determine the effect of two key physicochemical properties, lipophilicity and ionization, on the transport of drugs across porcine sublingual mucosa. A series of β-blockers were used to study the effect of lipophilicity on drug permeation across the sublingual mucosa, while nimesulide (pKa 6.5) was used as a model drug to study the effect of degree of ionization on sublingual mucosa permeation of ionized and unionized species. Permeation of β-blockers increased linearly with an increase in the lipophilicity for the range of compounds studied. The permeability of nimesulide across sublingual mucosa decreased with an increase of pH. The flux of ionized and unionized forms of nimesulide was determined to delineate the contribution of ionized and unionized species to the total flux. At low pH, the apparent flux was primarily contributed by unionized species; however, when the pH is increased beyond its pKa, the primary contributor to the apparent flux, nimesulide, is ionized species. The contribution of each species to the apparent flux was shown to be determined by the thermodynamic activity of ionized or unionized species. This study identified the roles of lipophilicity and thermodynamic activity in drug permeation across the sublingual mucosa. The findings can help guide the design of sublingual drug delivery systems with optimal pH and solubility.

Morphology effect of nano-hydroxyapatite as a drug carrier of methotrexate.

PubMed

Sun, Haina; Liu, Shanshan; Zeng, Xiongfeng; Meng, Xianguang; Zhao, Lina; Wan, Yizao; Zuo, Guifu

2017-09-13

In this study, morphology effect of nano-hydroxyapatite as a drug carrier was investigated for the first time. Hydroxyapatite/methotrexate (HAp/MTX) hybrids with different morphologies were successfully prepared in situ using polyethylene glycol (PEG) as a template. SEM, TEM, XRD and FTIR results confirmed that the hybrids of different morphologies (laminated, rod-like and spherical) with similar phase composition and functional groups were obtained by changing the preparation parameters. UV-Vis spectroscopy was used to identify the drug loading capacity and drug release mechanism of the three hybrids with different morphologies. It is concluded that the laminated hybrid exhibits a higher drug loading capacity compared to the other two hybrids, and all the three hybrids showed a sustained slow release which were fitted well by Bhaskar equation. Additionally, the result of in vitro bioassay test confirms that the inhibition efficacy of the three hybrids showed a positive correlation to the drug loading capacity.

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.

An investigation into drug-related problems identifiable by commercial medication review software.

PubMed

Curtain, Colin; Bindoff, Ivan; Westbury, Juanita; Peterson, Gregory

2013-01-01

Accredited pharmacists conduct home medicines reviews (HMRs) to detect and resolve potential drug-related problems (DRPs). A commercial expert system, Medscope Review Mentor (MRM), has been developed to assist pharmacists in the detection and resolution of potential DRPs. This study compares types of DRPs identified with the commercial system which uses multiple classification ripple down rules (MCRDR) with the findings of pharmacists. HMR data from 570 reviews collected from accredited pharmacists was entered into MRM and the DRPs were identified. A list of themes describing the main concept of each DRP identified by MRM was developed to allow comparison with pharmacists. Theme types, frequencies, similarity and dissimilarity were explored. The expert system was capable of detecting a wide range of potential DRPs: 2854 themes; compared to pharmacists: 1680 themes. The system identified the same problems as pharmacists in many patient cases. Ninety of 119 types of themes identifiable by pharmacists were also identifiable by software. MRM could identify the same problems in the same patients as pharmacists for 389 problems, resulting in a low overlap of similarity with an averaged Jaccard Index of 0.09. MRM found significantly more potential DRPs than pharmacists. MRM identified a wide scope of DRPs approaching the range of DRPs that were identified by pharmacists. Differences may be associated with system consistency and perhaps human oversight or human selective prioritisation. DRPs identified by the system were still considered relevant even though the system identified a larger number of problems.

Amphetamine as a social drug: Effects of d-amphetamine on social processing and behavior

PubMed Central

Wardle, Margaret C.; Garner, Matthew J.; Munafò, Marcus R.; de Wit, Harriet

2012-01-01

Rationale Drug users often report using drugs to enhance social situations, and empirical studies support the idea that drugs increase both social behavior and the value of social interactions. One way drugs may affect social behavior is by altering social processing, for example by decreasing perceptions of negative emotion in others. Objectives We examined effects of d-amphetamine on processing of emotional facial expressions, and on the social behavior of talking. We predicted amphetamine would enhance attention, identification and responsivity to positive expressions, and that this in turn would predict increased talkativeness. Methods Over three sessions, 36 healthy normal adults received placebo, 10mg, and 20mg d-amphetamine under counterbalanced double-blind conditions. At each session we measured processing of happy, fearful, sad and angry expressions using an attentional visual probe task, a dynamic emotion identification task, and measures of facial muscle activity. We also measured talking. Results Amphetamine decreased the threshold for identifying all emotions, increased negative facial responses to sad expressions, and increased talkativeness. Contrary to our hypotheses, amphetamine did not alter attention to, identification of or facial responses to positive emotions specifically. Interestingly, the drug decreased the threshold to identify all emotions, and this effect was uniquely related to increased talkativeness, even after controlling for overall sensitivity to amphetamine. Conclusions The results suggest that amphetamine may encourage sociability by increasing sensitivity to subtle emotional expressions. These findings suggest novel social mechanisms that may contribute to the rewarding effects of amphetamine. PMID:22526538

Effectiveness and risks of combining antipsychotic drugs with electroconvulsive treatment.

PubMed

Sanz-Fuentenebro, Francisco Javier; Vidal Navarro, Ignacio; Ballesteros Sanz, Daniel; Verdura Vizcaíno, Ernesto

2011-01-01

The simultaneous application of electroconvulsive therapy (ECT) and psychotropic drugs is based on sparse data. Despite this, and the restrictive approach of the Guidelines and Consensus is widespread in the usual care, it is widely practiced in routine clinical. We reviewed the results of search on the topic in MEDLINE, PsychINFO, EMBASE and Cochrane, and the main guidelines on the subject and analyzed for drug groups. Except some reservation with regard to classical MAOIs, antidepressants are safe and effective enhancers of the TEC. It is desirable to discontinuation of BZD whenever clinically possible before the course of ECT for risk of interference, if not possible will have to use proper technique to ensure effective incentives. It is advisable to stop or reduce the dose of lithium prior to ECT based on a cost-benefit analysis of the risk of relapse, if maintained will be adjusted lower levels and cognitive effects minimizing techniques. The combination with "classic" and "atypical" antipsychotics power positive clinical effects and the risk of combined use is low. The positive data are collected with clozapine and ECT-resistant psychosis, with little presence of effects of the decrease of seizure threshold by clozapine, and important effect of empowerment, but of limited duration. Although it is strictly necessary to identify situations in terms of drugs, patient and ECT technique, and care necessary to develop tests that provide methodologically sound data, the combined use of ECT and psychotropic drugs in general presents an acceptable risk level and efficacy data by encouraging empowerment. Copyright © 2010 SEP y SEPB. Published by Elsevier Espana. All rights reserved.

Can we identify response markers to antihypertensive drugs? First results from the IDEAL Trial.

PubMed

Gueyffier, F; Subtil, F; Bejan-Angoulvant, T; Zerbib, Y; Baguet, J P; Boivin, J M; Mercier, A; Leftheriotis, G; Gagnol, J P; Fauvel, J P; Giraud, C; Bricca, G; Maucort-Boulch, D; Erpeldinger, S

2015-01-01

Current antihypertensive strategies do not take into account that individual characteristics may influence the magnitude of blood pressure (BP) reduction. Guidelines promote trial-and-error approaches with many different drugs. We conducted the Identification of the Determinants of the Efficacy of Arterial blood pressure Lowering drugs (IDEAL) Trial to identify factors associated with BP responses to perindopril and indapamide. IDEAL was a cross-over, double-blind, placebo-controlled trial, involving four 4-week periods: indapamide, perindopril and two placebo. Eligible patients were untreated, hypertensive and aged 25-70 years. The main outcome was systolic BP (SBP) response to drugs. The 112 participants with good compliance had a mean age of 52. One in every three participants was a woman. In middle-aged women, the SBP reduction from drugs was -11.5 mm Hg (indapamide) and -8.3 mm Hg (perindopril). In men, the response was significantly smaller: -4.8 mm Hg (indapamide) and -4.3 (perindopril) (P for sex differences 0.001 and 0.015, respectively). SBP response to perindopril decreased by 2 mm Hg every 10 years of age in both sexes (P=0.01). The response to indapamide increased by 3 mm Hg every 10 years of age gradient in women (P=0.02). Age and sex were important determinants of BP response for antihypertensive drugs in the IDEAL population. This should be taken into account when choosing drugs a priori.

A high throughput screening for TLR3-IRF3 signaling pathway modulators identifies several antipsychotic drugs as TLR inhibitors1

PubMed Central

Zhu, Jianzhong; Smith, Kevin; Hsieh, Paishiun N.; Mburu, Yvonne K.; Chattopadhyay, Saurabh; Sen, Ganes C.; Sarkar, Saumendra N.

2010-01-01

Toll-like Receptor 3 (TLR3) is one of the major innate immune sensors of double stranded RNA (dsRNA). The signal transduction pathway activated by TLR3, upon binding to dsRNA, leads to the activation of two major transcription factors: NF-κB and IRF3. In an effort to identify specific chemical modulators of TLR3-IRF3 signal transduction pathway we developed a cell-based read out system. Using the interferon stimulated gene 56 (ISG56) promoter driven firefly luciferase gene stably integrated in a TLR3 expressing HEK293 cell line, we were able to generate a cell line where treatment with dsRNA resulted in a dose dependent induction of luciferase activity. A screen of two pharmacologically active compound libraries using this system, identified a number of TLR3-IRF3 signaling pathway modulators. Among them we focused on a subset of inhibitors and characterized their mode of action. Several antipsychotic drugs, such as Sertraline, Trifluoperazine and Fluphenazine were found to be direct inhibitors of the innate immune signaling pathway. These inhibitors also showed the ability to inhibit ISG56 induction mediated by TLR4 and TLR7/8 pathways. Interestingly, they did not show significant effect on TLR3, TLR7 and TLR8 mediated NF-κB activation. Detailed analysis of the signaling pathway indicated that these drugs may be exerting their inhibitory effects on IRF3 via PI3K signaling pathway. The data presented here provides mechanistic explanation of possible anti-inflammatory roles of some antipsychotic drugs. PMID:20382888

Assessing the Effects of Non-steroidal Anti-inflammatory Drugs on Antihypertensive Drug Therapy Using Post-Marketing Surveillance Database

PubMed Central

Ishiguro, Chieko; Fujita, Toshiharu; Omori, Takashi; Fujii, Yosuke; Mayama, Takeshi; Sato, Tosiya

2008-01-01

Background Antihypertensive and non-steroidal anti-inflammatory drugs (NSAIDs) are used to treat many common diseases. However, it has been suspected that interactions between these drugs exist. Here, we assessed the interactions between non-selective NSAIDs and several classes of antihypertensive drugs. Methods The study design was a cohort study using “The Antihypertensive Drug Database,” which is a collection of data accumulated from Drug Use Investigations. Subjects newly starting antihypertensive drug therapy were identified in the database. We compared the “User” group, who were co-administered NSAIDs, with the “Non-user” group, who were not. The outcome measure was the change in systolic blood pressure from the baseline after 2 months of treatment. We estimated the non-adjusted and adjusted differences in the change in systolic blood pressure between the “User” and “Non-user” groups. Results Data were collected for a total of 1,204 subjects, of whom 364 were prescribed beta blockers, 60 were prescribed diuretics, 628 were prescribed angiotensin-converting enzyme inhibitors, and 152 were prescribed calcium channel blockers. The adjusted difference in the change in systolic blood pressure between the User (n = 301) and Non-user (n = 903) groups was 2.88 mmHg (95% confidence interval: 0.89, 4.87); thus, systolic blood pressure in the Non-User group decreased further from the baseline than that in the User group. In subjects administered beta blockers, diuretics, angiotensin-converting enzyme inhibitors, and calcium channel blockers, the corresponding differences were 0.37 mmHg (-3.24, 3.98), 6.11 mmHg (-3.16, 15.37), 3.85 mmHg (1.16, 6.66), and 3.50 mmHg (-2.03, 9.02). Conclusion The effectiveness of antihypertensive drugs was attenuated by the co-administration of NSAIDs. The differences in the effects of NSAIDs varied with different classes of antihypertensive drugs. PMID:18469490

Assessing the effects of non-steroidal anti-inflammatory drugs on antihypertensive drug therapy using post-marketing surveillance database.

PubMed

Ishiguro, Chieko; Fujita, Toshiharu; Omori, Takashi; Fujii, Yosuke; Mayama, Takeshi; Sato, Tosiya

2008-01-01

Antihypertensive and non-steroidal anti-inflammatory drugs (NSAIDs) are used to treat many common diseases. However, it has been suspected that interactions between these drugs exist. Here, we assessed the interactions between non-selective NSAIDs and several classes of antihypertensive drugs. The study design was a cohort study using "The Antihypertensive Drug Database," which is a collection of data accumulated from Drug Use Investigations. Subjects newly starting antihypertensive drug therapy were identified in the database. We compared the "User" group, who were co-administered NSAIDs, with the "Non-user" group, who were not. The outcome measure was the change in systolic blood pressure from the baseline after 2 months of treatment. We estimated the non-adjusted and adjusted differences in the change in systolic blood pressure between the "User" and "Non-user" groups. Data were collected for a total of 1,204 subjects, of whom 364 were prescribed beta blockers, 60 were prescribed diuretics, 628 were prescribed angiotensin-converting enzyme inhibitors, and 152 were prescribed calcium channel blockers. The adjusted difference in the change in systolic blood pressure between the User (n = 301) and Non-user (n = 903) groups was 2.88 mmHg (95% confidence interval: 0.89, 4.87); thus, systolic blood pressure in the Non-User group decreased further from the baseline than that in the User group. In subjects administered beta blockers, diuretics, angiotensin-converting enzyme inhibitors, and calcium channel blockers, the corresponding differences were 0.37 mmHg (-3.24, 3.98), 6.11 mmHg (-3.16, 15.37), 3.85 mmHg (1.16, 6.66), and 3.50 mmHg (-2.03, 9.02). The effectiveness of antihypertensive drugs was attenuated by the co-administration of NSAIDs. The differences in the effects of NSAIDs varied with different classes of antihypertensive drugs.

Exploring Inflammatory Disease Drug Effects on Neutrophil Function

PubMed Central

Wu, Xiaojie; Kim, Donghyuk; Young, Ashlyn T.; Haynes, Christy L.

2014-01-01

Neutrophils are critical inflammatory cells; thus, it is important to characterize the effects of drugs on neutrophil function in the context of inflammatory diseases. Herein, chemically guided neutrophil migration, known as chemotaxis, is studied in the context of drug treatment at the single cell level using a microfluidic platform, complemented by cell viability assays and calcium imaging. Three representative drugs known to inhibit surface receptor expression, signaling enzyme activity, and the elevation of intracellular Ca2+ levels, each playing a significant role in neutrophil chemotactic pathways, are used to examine the in vitro drug effects on cellular behaviors. The microfluidic device establishes a stable concentration gradient of chemokines across a cell culture chamber so that neutrophil migration can be monitored under various drug-exposure conditions. Different time- and concentration-dependent regulatory effects were observed by comparing the motility, polarization, and effectiveness of neutrophil chemotaxis in response to the three drugs. Viability assays revealed distinct drug capabilities in reducing neutrophil viability while calcium imaging clarified the role of Ca2+ in the neutrophil chemotactic pathway. This study provides mechanistic insight into the drug effects on neutrophil function, facilitating comparison of current and potential pharmaceutical approaches. PMID:24946254

Youth Illicit Drug Use Prevention: DARE Long-Term Evaluations and Federal Efforts To Identify Effective Programs.

ERIC Educational Resources Information Center

Kanof, Marjorie E.

The most widely used school-based substance abuse prevention program in the United States is the Drug Abuse Resistance Education (DARE) program, which is funded by a variety of sources, including private, federal, and other public entities. DAREs primary mission is to provide children with the information and skills they need to live drug- and…

A window into the intoxicated mind? Speech as an index of psychoactive drug effects.

PubMed

Bedi, Gillinder; Cecchi, Guillermo A; Slezak, Diego F; Carrillo, Facundo; Sigman, Mariano; de Wit, Harriet

2014-09-01

Abused drugs can profoundly alter mental states in ways that may motivate drug use. These effects are usually assessed with self-report, an approach that is vulnerable to biases. Analyzing speech during intoxication may present a more direct, objective measure, offering a unique 'window' into the mind. Here, we employed computational analyses of speech semantic and topological structure after ±3,4-methylenedioxymethamphetamine (MDMA; 'ecstasy') and methamphetamine in 13 ecstasy users. In 4 sessions, participants completed a 10-min speech task after MDMA (0.75 and 1.5 mg/kg), methamphetamine (20 mg), or placebo. Latent Semantic Analyses identified the semantic proximity between speech content and concepts relevant to drug effects. Graph-based analyses identified topological speech characteristics. Group-level drug effects on semantic distances and topology were assessed. Machine-learning analyses (with leave-one-out cross-validation) assessed whether speech characteristics could predict drug condition in the individual subject. Speech after MDMA (1.5 mg/kg) had greater semantic proximity than placebo to the concepts friend, support, intimacy, and rapport. Speech on MDMA (0.75 mg/kg) had greater proximity to empathy than placebo. Conversely, speech on methamphetamine was further from compassion than placebo. Classifiers discriminated between MDMA (1.5 mg/kg) and placebo with 88% accuracy, and MDMA (1.5 mg/kg) and methamphetamine with 84% accuracy. For the two MDMA doses, the classifier performed at chance. These data suggest that automated semantic speech analyses can capture subtle alterations in mental state, accurately discriminating between drugs. The findings also illustrate the potential for automated speech-based approaches to characterize clinically relevant alterations to mental state, including those occurring in psychiatric illness.

A practical classification of untoward drug effects.

PubMed Central

Gysling, E.; Heisler, S.

1975-01-01

All drug effects can be explained as results of complex interactions between the drug, the patient and his condition, and additional extrinsic factors. On the basis of these three "determinants", a practical classification of untoward drug effects (UDE) is suggested. UDE lists using this classification would fulfill the physician's informational needs better than the material with which he is presently provided. PMID:1148971

Cost-effectiveness of Newer Antiretroviral Drugs in Treatment-Experienced Patients with Multi-drug Resistant HIV Disease

PubMed Central

Bayoumi, Ahmed M.; Barnett, Paul G.; Joyce, Vilija R.; Griffin, Susan C.; Sun, Huiying; Bansback, Nick J.; Holodniy, Mark; Sanders, Gillian; Brown, Sheldon T.; Kyriakides, Tassos C.; Angus, Brian; Cameron, D. William; Anis, Aslam H.; Sculpher, Mark; Owens, Douglas K.

2014-01-01

Objective Newer antiretroviral drugs provide substantial benefits but are expensive. We determined the cost-effectiveness of using antiretroviral drugs in combination for patients with multi-drug resistant HIV disease. Design We built a cohort state-transition model representing treatment-experienced patients with low CD4 counts, high viral load levels, and multi-drug resistant virus. We estimated the effectiveness of newer drugs (those approved in 2005 or later) from published randomized trials. We estimated other parameters from a randomized trial and from the literature. The model had a lifetime time horizon and used the perspective of an ideal insurer in the United States. The interventions were combination antiretroviral therapy, consisting of two newer drugs and one conventional drug, compared to three conventional drugs. Outcome measures were life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness. Results Substituting newer antiretroviral drugs increased expected survival by 3.9 years in advanced HIV disease. The incremental cost-effectiveness ratio of newer, compared to conventional, antiretroviral drugs was $75,556/QALY gained. Sensitivity analyses showed that substituting only one newer antiretroviral drug cost $54,559 to $68,732/QALY, depending on assumptions about efficacy. Substituting three newer drugs cost $105,956 to $117,477/QALY. Cost-effectiveness ratios were higher if conventional drugs were not discontinued. Conclusions In treatment-experienced patients with advanced HIV disease, use of newer antiretroviral agents can be cost effective, given a cost-effectiveness threshold in the range of $50,000 to $75,000 per QALY gained. Newer antiretroviral agents should be used in carefully selected patients for whom less expensive options are clearly inferior. PMID:24129369

Effects of drug price reduction and prescribing restrictions on expenditures and utilisation of antihypertensive drugs in Korea

PubMed Central

Yoo, Ki-Bong; Lee, Sang Gyu; Park, Sohee; Kim, Tae Hyun; Ahn, Jeonghoon; Cho, Mee-Hyun; Park, Eun-Cheol

2015-01-01

Objectives To evaluate the quantitative effects of the drug price reduction on pharmaceutical expenditures and the new guidelines to restrict prescribing on drug utilisation for antihypertensive drugs. Design We used an interrupted time series design with the National patient sample data of Health Insurance Review and Assessment Service in South Korea. Methods 54 295 participants who were with primary hypertension from the National patient sample data of Health Insurance Review and Assessment Service were included. The study period was from March 2011 to December 2013. The dependent variables were antihypertensive drug costs, antihypertensive drug cost per prescribing day, daily drug utilisation, average number of drugs per month, percentage of original drugs per prescription, drug overutilisation and prohibited combinations. Segmented regression analysis was used. Results The drug price reduction reduced expenditure (US$−1.51, −10.2%), and the new guidelines reduced expenditures even more (US$−2.13; −16.2%). These policies saved US$4.22 (28%) of antihypertensive drug costs per patient in December 2013 compared to March 2012. Drug price reduction policy was introduced in April 2012. We established the policy effect by comparing it before (March 2012) with after(21 months later-December 2012). The effects of the guidelines decreased expenditures, daily drug utilisation and the average number of drugs per month more than did the drug price reduction. Conclusions Both policies saved money. The guidelines were more effective over time and had fewer side effects such as increasing daily drug utilisation and number of drugs than the effects of drug price reduction. PMID:26179644

Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.

PubMed

Romagnoli, Katrina M; Nelson, Scott D; Hines, Lisa; Empey, Philip; Boyce, Richard D; Hochheiser, Harry

2017-02-22

Drug information compendia and drug-drug interaction information databases are critical resources for clinicians and pharmacists working to avoid adverse events due to exposure to potential drug-drug interactions (PDDIs). Our goal is to develop information models, annotated data, and search tools that will facilitate the interpretation of PDDI information. To better understand the information needs and work practices of specialists who search and synthesize PDDI evidence for drug information resources, we conducted an inquiry that combined a thematic analysis of published literature with unstructured interviews. Starting from an initial set of relevant articles, we developed search terms and conducted a literature search. Two reviewers conducted a thematic analysis of included articles. Unstructured interviews with drug information experts were conducted and similarly coded. Information needs, work processes, and indicators of potential strengths and weaknesses of information systems were identified. Review of 92 papers and 10 interviews identified 56 categories of information needs related to the interpretation of PDDI information including drug and interaction information; study design; evidence including clinical details, quality and content of reports, and consequences; and potential recommendations. We also identified strengths/weaknesses of PDDI information systems. We identified the kinds of information that might be most effective for summarizing PDDIs. The drug information experts we interviewed had differing goals, suggesting a need for detailed information models and flexible presentations. Several information needs not discussed in previous work were identified, including temporal overlaps in drug administration, biological plausibility of interactions, and assessment of the quality and content of reports. Richly structured depictions of PDDI information may help drug information experts more effectively interpret data and develop recommendations

Adverse drug effects in hospitalized elderly: Data from the Healthcare Cost and Utilization Project

PubMed Central

Shamliyan, Tatyana

2010-01-01

We aimed to analyze trends in hospital admissions due to adverse drug effects between the years 2000 to 2007 among the elderly using the National Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project. We identified the discharges with the principal and all listed diagnoses related to adverse drug effects and associated hospital charges using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) codes. Between 2000 and 2007, 321,057 patients over 65 years were discharged with a principal diagnosis related to an adverse drug effect. Hospital charges were $5,329,276,300 or $666,159,537 annual cost. The number of discharges and total hospital charges did not change over the examined years, while mean charge per discharge increased on average by $1064 ± 384 per year. Total hospital charges for drug-induced gastritis with hemorrhage increased the most by $11,206,555 per year among those 66–84 years old and by $8,646,456 per year among those older than 85 years. During 2007, 791,931 elderly had adverse treatment effects among all listed diagnoses with hospital charges of $937,795,690. Effective drug management interventions are needed to improve safety of treatments in the elderly. PMID:22291486

Identifying adverse drug event information in clinical notes with distributional semantic representations of context.

PubMed

Henriksson, Aron; Kvist, Maria; Dalianis, Hercules; Duneld, Martin

2015-10-01

For the purpose of post-marketing drug safety surveillance, which has traditionally relied on the voluntary reporting of individual cases of adverse drug events (ADEs), other sources of information are now being explored, including electronic health records (EHRs), which give us access to enormous amounts of longitudinal observations of the treatment of patients and their drug use. Adverse drug events, which can be encoded in EHRs with certain diagnosis codes, are, however, heavily underreported. It is therefore important to develop capabilities to process, by means of computational methods, the more unstructured EHR data in the form of clinical notes, where clinicians may describe and reason around suspected ADEs. In this study, we report on the creation of an annotated corpus of Swedish health records for the purpose of learning to identify information pertaining to ADEs present in clinical notes. To this end, three key tasks are tackled: recognizing relevant named entities (disorders, symptoms, drugs), labeling attributes of the recognized entities (negation, speculation, temporality), and relationships between them (indication, adverse drug event). For each of the three tasks, leveraging models of distributional semantics - i.e., unsupervised methods that exploit co-occurrence information to model, typically in vector space, the meaning of words - and, in particular, combinations of such models, is shown to improve the predictive performance. The ability to make use of such unsupervised methods is critical when faced with large amounts of sparse and high-dimensional data, especially in domains where annotated resources are scarce. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Systems pharmacology identifies drug targets for Stargardt disease–associated retinal degeneration

PubMed Central

Chen, Yu; Palczewska, Grazyna; Mustafi, Debarshi; Golczak, Marcin; Dong, Zhiqian; Sawada, Osamu; Maeda, Tadao; Maeda, Akiko; Palczewski, Krzysztof

2013-01-01

A systems pharmacological approach that capitalizes on the characterization of intracellular signaling networks can transform our understanding of human diseases and lead to therapy development. Here, we applied this strategy to identify pharmacological targets for the treatment of Stargardt disease, a severe juvenile form of macular degeneration. Diverse GPCRs have previously been implicated in neuronal cell survival, and crosstalk between GPCR signaling pathways represents an unexplored avenue for pharmacological intervention. We focused on this receptor family for potential therapeutic interventions in macular disease. Complete transcriptomes of mouse and human samples were analyzed to assess the expression of GPCRs in the retina. Focusing on adrenergic (AR) and serotonin (5-HT) receptors, we found that adrenoceptor α 2C (Adra2c) and serotonin receptor 2a (Htr2a) were the most highly expressed. Using a mouse model of Stargardt disease, we found that pharmacological interventions that targeted both GPCR signaling pathways and adenylate cyclases (ACs) improved photoreceptor cell survival, preserved photoreceptor function, and attenuated the accumulation of pathological fluorescent deposits in the retina. These findings demonstrate a strategy for the identification of new drug candidates and FDA-approved drugs for the treatment of monogenic and complex diseases. PMID:24231350

Drug-Target Interactions: Prediction Methods and Applications.

PubMed

Anusuya, Shanmugam; Kesherwani, Manish; Priya, K Vishnu; Vimala, Antonydhason; Shanmugam, Gnanendra; Velmurugan, Devadasan; Gromiha, M Michael

2018-01-01

Identifying the interactions between drugs and target proteins is a key step in drug discovery. This not only aids to understand the disease mechanism, but also helps to identify unexpected therapeutic activity or adverse side effects of drugs. Hence, drug-target interaction prediction becomes an essential tool in the field of drug repurposing. The availability of heterogeneous biological data on known drug-target interactions enabled many researchers to develop various computational methods to decipher unknown drug-target interactions. This review provides an overview on these computational methods for predicting drug-target interactions along with available webservers and databases for drug-target interactions. Further, the applicability of drug-target interactions in various diseases for identifying lead compounds has been outlined. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

76 FR 44593 - Identifying the Center for Drug Evaluation and Research's Science and Research Needs...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-26

... . Submit written comments to the Division of Dockets Management (HFA-305), Food and Drug Administration... from CDER's offices were asked to identify: (1) Scientific challenges currently addressed on a case-by-case basis that might benefit from the development of a systematized approach; (2) recurrent science...

Effects of drug-carrier interactions on drug dissolution from binary and ternary matrices

NASA Astrophysics Data System (ADS)

Iqbal, Zafar

formulations and perform appropriate physical characterizations. (2) Characterize the increase in drug dissolution rates resulting from solid solution formulations. (3) Relate the initial dissolution rates to the drug solubility. (4) Explain the solubility enhancement from solid solution dosage in terms of the drug polymer interactions using the extended thermodynamic model. Two poorly water soluble drugs, levonorgestrel (LEVO) and ethinyl estradiol (EE) were formulated in seven solid solution preparations comprised of four carrier systems. Materials used as carriers included various combinations of the polymers PVP K-30, Copovidone (COP), Poloxamer 182, and the surfactant TweenRTM 20. Additionally, ibuprofen (IBU) was used in three formulations consisting of various combinations of PVP K-30, Copovidone and TweenRTM 20. Formulations with various drug weight fractions (0.5%--30%) were prepared using the solvent evaporation technique. Each formulation was tested for dissolution using intrinsic dissolution apparatus (USP). The solid solutions were compressed into tablets into the sample die that maintained a constant surface area during the dissolution process. DSC, XRD and NIRS scans identified that the crystalline peaks of the drug disappeared with the addition of the polymer for all ratios of EE, indicating the formation of solid solutions (to within the limits of detection of the equipment). This was also observed for the LEVO dispersions up to 10% drug loading. At higher drug loading, solutions were formed but some small degree crystallinity was also present. For each experiment, the initial dissolution rates were obtained from the slope of the mass dissolved vs. time plots taken at early times, and volume normalized initial dissolution rates RV were calculated by dividing the initial dissolution rate by the volume fraction of the drug in the formulation. Comparison of the RV values for the various formulations with a reference RV (typically that of the pure drug or of the

The Drug Effects Questionnaire: Psychometric Support across Three Drug Types

PubMed Central

Morean, Meghan E.; de Wit, Harriet; King, Andrea C.; Sofuoglu, Mehmet; Rueger, Sandra Y.; O’Malley, Stephanie S.

2013-01-01

Rationale The Drug Effects Questionnaire (DEQ) is widely used in studies of acute subjective response (SR) to a variety of substances, but the format of the DEQ varies widely across studies, and details of its psychometric properties are lacking. Thus, the field would benefit from demonstrating the reliability and validity of the DEQ for use across multiple substances. Objective The current study evaluated the psychometric properties of several variations of DEQ items, which assessed the extent to which participants (1) feel any substance effect(s), (2) feel high, (3) like the effects, (4) dislike the effects, and (5) want more of the substance using 100mm Visual Analog Scales. Methods DEQ data from three placebo-controlled studies were analyzed to examine SR to amphetamine, nicotine, and alcohol. We evaluated the internal structure of the DEQ for use with each substance as well as relationships between scale items, measures of similar constructs, and substance-related behaviors. Results Results provided preliminary psychometric support for items assessing each DEQ construct (FEEL, HIGH, DISLIKE, LIKE, and MORE). Conclusions Based on the study results, we identify several common limitations of extant variants of the DEQ and recommend an improved version of the measure. The simplicity and brevity of the DEQ combined with its promising psychometric properties support its use in future SR research across a variety of substances. PMID:23271193

A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects

PubMed Central

Bedi, Gillinder; Cecchi, Guillermo A; Slezak, Diego F; Carrillo, Facundo; Sigman, Mariano; de Wit, Harriet

2014-01-01

Abused drugs can profoundly alter mental states in ways that may motivate drug use. These effects are usually assessed with self-report, an approach that is vulnerable to biases. Analyzing speech during intoxication may present a more direct, objective measure, offering a unique ‘window' into the mind. Here, we employed computational analyses of speech semantic and topological structure after ±3,4-methylenedioxymethamphetamine (MDMA; ‘ecstasy') and methamphetamine in 13 ecstasy users. In 4 sessions, participants completed a 10-min speech task after MDMA (0.75 and 1.5 mg/kg), methamphetamine (20 mg), or placebo. Latent Semantic Analyses identified the semantic proximity between speech content and concepts relevant to drug effects. Graph-based analyses identified topological speech characteristics. Group-level drug effects on semantic distances and topology were assessed. Machine-learning analyses (with leave-one-out cross-validation) assessed whether speech characteristics could predict drug condition in the individual subject. Speech after MDMA (1.5 mg/kg) had greater semantic proximity than placebo to the concepts friend, support, intimacy, and rapport. Speech on MDMA (0.75 mg/kg) had greater proximity to empathy than placebo. Conversely, speech on methamphetamine was further from compassion than placebo. Classifiers discriminated between MDMA (1.5 mg/kg) and placebo with 88% accuracy, and MDMA (1.5 mg/kg) and methamphetamine with 84% accuracy. For the two MDMA doses, the classifier performed at chance. These data suggest that automated semantic speech analyses can capture subtle alterations in mental state, accurately discriminating between drugs. The findings also illustrate the potential for automated speech-based approaches to characterize clinically relevant alterations to mental state, including those occurring in psychiatric illness. PMID:24694926

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

PubMed Central

Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

2016-01-01

The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

High-throughput screen of drug repurposing library identifies inhibitors of Sarcocystis neurona growth.

PubMed

Bowden, Gregory D; Land, Kirkwood M; O'Connor, Roberta M; Fritz, Heather M

2018-04-01

The apicomplexan parasite Sarcocystis neurona is the primary etiologic agent of equine protozoal myeloencephalitis (EPM), a serious neurologic disease of horses. Many horses in the U.S. are at risk of developing EPM; approximately 50% of all horses in the U.S. have been exposed to S. neurona and treatments for EPM are 60-70% effective. Advancement of treatment requires new technology to identify new drugs for EPM. To address this critical need, we developed, validated, and implemented a high-throughput screen to test 725 FDA-approved compounds from the NIH clinical collections library for anti-S. neurona activity. Our screen identified 18 compounds with confirmed inhibitory activity against S. neurona growth, including compounds active in the nM concentration range. Many identified inhibitory compounds have well-defined mechanisms of action, making them useful tools to study parasite biology in addition to being potential therapeutic agents. In comparing the activity of inhibitory compounds identified by our screen to that of other screens against other apicomplexan parasites, we found that most compounds (15/18; 83%) have activity against one or more related apicomplexans. Interestingly, nearly half (44%; 8/18) of the inhibitory compounds have reported activity against dopamine receptors. We also found that dantrolene, a compound already formulated for horses with a peak plasma concentration of 37.8 ± 12.8 ng/ml after 500 mg dose, inhibits S. neurona parasites at low concentrations (0.065 μM [0.036-0.12; 95% CI] or 21.9 ng/ml [12.1-40.3; 95% CI]). These studies demonstrate the use of a new tool for discovering new chemotherapeutic agents for EPM and potentially providing new reagents to elucidate biologic pathways required for successful S. neurona infection. Copyright © 2018. Published by Elsevier Ltd.

A survey of antiepileptic drug responses identifies drugs with potential efficacy for seizure control in Wolf-Hirschhorn syndrome.

PubMed

Ho, Karen S; Markham, Leah M; Twede, Hope; Lortz, Amanda; Olson, Lenora M; Sheng, Xiaoming; Weng, Cindy; Wassman, E Robert; Newcomb, Tara; Wassman, E Robert; Carey, John C; Battaglia, Agatino

2018-04-01

Seizures are present in over 90% of infants and children with Wolf-Hirschhorn syndrome (WHS). When present, they significantly affect quality of life. The goal of this study was to use caregiver reports to describe the comparative efficacies of commonly used antiepileptic medications in a large population of individuals with WHS. A web-based, confidential caregiver survey was developed to capture seizure semiology and a chronologic record of seizure treatments as well as responses to each treatment. Adverse events for each drug were also cataloged. We received 141 complete survey responses (47% response rate) describing the seizures of individuals ranging in age from 4months to 61years (90 females: 51 males). Using the Early Childhood Epilepsy Severity Scale (E-Chess), WHS-associated seizures are demonstrably severe regardless of deletion size. The best-performing antiepileptic drugs (AEDs) for controlling seizures in this cohort were broad spectrum drugs clobazam, levetiracetam, and lamotrigine; whereas, the three commonly used carboxamide class drugs: carbamazepine, phenytoin, and oxcarbazepine, were reported to have little effect on, or even exacerbate, seizures. The carboxamide class drugs, along with phenobarbital and topiramate, were also associated with the highest rate of intolerance due to cooccurrence of adverse events. Levetiracetam, clobazam, and clonazepam demonstrated higher tolerability and comparatively less severe adverse events (Wilcoxon rank sum comparison between performance of levetiracetam and carboxamide class drugs gives a p<0.0001 after multiple comparison adjustment). This is the largest survey to date assessing WHS seizures. This study design is susceptible to possible bias, as the data are largely drawn from caregiver report and investigators had limited access to medical records. Despite this, our data suggest that the genetic etiology of seizures, together with an accurate electroclinical delineation, are important components of drug

Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus.

PubMed

Lu, Yao; Deng, Jingyuan; Rhodes, Judith C; Lu, Hui; Lu, Long Jason

2014-06-01

Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to

Short communication: cheminformatics analysis to identify predictors of antiviral drug penetration into the female genital tract.

PubMed

Thompson, Corbin G; Sedykh, Alexander; Nicol, Melanie R; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Kashuba, Angela D M

2014-11-01

The exposure of oral antiretroviral (ARV) drugs in the female genital tract (FGT) is variable and almost unpredictable. Identifying an efficient method to find compounds with high tissue penetration would streamline the development of regimens for both HIV preexposure prophylaxis and viral reservoir targeting. Here we describe the cheminformatics investigation of diverse drugs with known FGT penetration using cluster analysis and quantitative structure-activity relationships (QSAR) modeling. A literature search over the 1950-2012 period identified 58 compounds (including 21 ARVs and representing 13 drug classes) associated with their actual concentration data for cervical or vaginal tissue, or cervicovaginal fluid. Cluster analysis revealed significant trends in the penetrative ability for certain chemotypes. QSAR models to predict genital tract concentrations normalized to blood plasma concentrations were developed with two machine learning techniques utilizing drugs' molecular descriptors and pharmacokinetic parameters as inputs. The QSAR model with the highest predictive accuracy had R(2)test=0.47. High volume of distribution, high MRP1 substrate probability, and low MRP4 substrate probability were associated with FGT concentrations ≥1.5-fold plasma concentrations. However, due to the limited FGT data available, prediction performances of all models were low. Despite this limitation, we were able to support our findings by correctly predicting the penetration class of rilpivirine and dolutegravir. With more data to enrich the models, we believe these methods could potentially enhance the current approach of clinical testing.

Drug-Associated Acute Kidney Injury Identified in the United States Food and Drug Administration Adverse Event Reporting System Database.

PubMed

Welch, Hanna K; Kellum, John A; Kane-Gill, Sandra L

2018-06-08

Acute kidney injury (AKI) is a common condition associated with both short-term and long-term consequences including dialysis, chronic kidney disease, and mortality. Although the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database is a powerful tool to examine drug-associated events, to our knowledge, no study has analyzed this database to identify the most common drugs reported with AKI. The objective of this study was to analyze AKI reports and associated medications in the FAERS database. Retrospective pharmacovigilance disproportionality analysis. FAERS database. We queried the FAERS database for reports of AKI from 2004 quarter 1 through 2015 quarter 3. Extracted drugs were assessed using published references and categorized as known, possible, or new potential nephrotoxins. The reporting odds ratio (ROR), a measure of reporting disproportionality, was calculated for the 20 most frequently reported drugs in each category. We retrieved 7,241,385 adverse event reports, of which 193,996 (2.7%) included a report of AKI. Of the AKI reports, 16.5% were known nephrotoxins, 18.6% were possible nephrotoxins, and 64.8% were new potential nephrotoxins. Among the most commonly reported drugs, those with the highest AKI ROR were aprotinin (7,614 reports; ROR 115.70, 95% confidence interval [CI] 110.63-121.01), sodium phosphate (1,687 reports; ROR 55.81, 95% CI 51.78-60.17), furosemide (1,743 reports; ROR 12.61, 95% CI 11.94-13.32), vancomycin (1,270 reports, ROR 12.19, 95% CI 11.45-12.99), and metformin (4,701 reports; ROR 10.65, 95% CI 10.31-11.00). The combined RORs for the 20 most frequently reported drugs with each nephrotoxin classification were 3.71 (95% CI 3.66-3.76) for known nephrotoxins, 2.09 (95% CI 2.06-2.12) for possible nephrotoxins, and 1.55 (95% CI 1.53-1.57) for new potential nephrotoxins. AKI was a common reason for adverse event reporting in the FAERS. Most AKI reports were generated for medications not recognized

The effect of qualifying language on perceptions of drug appeal, drug experience, and estimates of side-effect incidence in DTC advertising.

PubMed

Davis, Joel

2007-01-01

This study examined how the use of qualifying language in direct-to-consumer (DTC) pharmaceutical advertising affects consumers' perceptions of drug appeal, anticipated pleasantness of drug usage, and the expected incidence of side-effect occurrence. A sample of 669 individuals participated in a 2 x 8 complete factorial design. The design manipulated the number of side effects associated with drug use and the type of qualifying language used to describe the side effects. The eight experimental qualifying language cells represented one control condition (no qualifying language), three cells where each of three types of qualifying language were presented individually, and four cells where qualifying language was combined. The results indicate that qualifying language has a profound effect on drug perceptions, especially when used in combination. Drug appeal and the anticipated drug-using experience almost always were more positive in the presence of qualifying language. Qualifying language appears to exert its influence by causing individuals to reduce their estimate of the likelihood of experiencing individual side effects. Policy implications of the research, particularly for evaluation of "fair balance" and the reporting of side effects, are presented.

Drosophila Cancer Models Identify Functional Differences between Ret Fusions.

PubMed

Levinson, Sarah; Cagan, Ross L

2016-09-13

We generated and compared Drosophila models of RET fusions CCDC6-RET and NCOA4-RET. Both RET fusions directed cells to migrate, delaminate, and undergo EMT, and both resulted in lethality when broadly expressed. In all phenotypes examined, NCOA4-RET was more severe than CCDC6-RET, mirroring their effects on patients. A functional screen against the Drosophila kinome and a library of cancer drugs found that CCDC6-RET and NCOA4-RET acted through different signaling networks and displayed distinct drug sensitivities. Combining data from the kinome and drug screens identified the WEE1 inhibitor AZD1775 plus the multi-kinase inhibitor sorafenib as a synergistic drug combination that is specific for NCOA4-RET. Our work emphasizes the importance of identifying and tailoring a patient's treatment to their specific RET fusion isoform and identifies a multi-targeted therapy that may prove effective against tumors containing the NCOA4-RET fusion. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Reference drug programs: effectiveness and policy implications.

PubMed

Schneeweiss, Sebastian

2007-04-01

In the current economic environment, health care systems are constantly struggling to contain rapidly rising costs. Drug costs are targeted by a wide variety of measures. Many jurisdictions have implemented reference drug programs (RDPs) or similar therapeutic substitution programs. This paper summarizes the mechanism and rationale of RDPs and presents evidence of their economic effectiveness and clinical safety. RDPs for pharmaceutical reimbursement are based on the assumption that drugs within specified medication groups are therapeutically equivalent and clinically interchangeable and that a common reimbursement level can thus be established. If the evidence documents that a higher price for a given drug does not buy greater effectiveness or reduced toxicity, then under RDP such extra costs are not covered. RDPs or therapeutic substitutions based on therapeutic equivalence are seen as logical extensions of generic substitution that is based on bioequivalence of drugs. If the goal is to achieve full drug coverage for as many patients as possible in the most efficient manner, then RDPs in combination with prior authorization programs are safer and more effective than simplistic fiscal drug policies, including fixed co-payments, co-insurances, or deductibles. RDPs will reduce spending in the less innovative but largest market, while fully covering all patients. Prior authorization will ensure that patients with a specified indication will benefit from the most innovative therapies with full coverage. In practice, however, not all patients and drugs will fit exactly into one of the two categories. Therefore, a process of medically indicated exemptions that will consider full coverage should accompany an RDP. In the current economic environment, health care systems are constantly struggling to contain rapidly rising costs. Drug costs are targeted by a wide variety of measures. Many jurisdictions have implemented reference drug programs, and others are considering

Reference drug programs: Effectiveness and policy implications☆

PubMed Central

Schneeweiss, Sebastian

2010-01-01

In the current economic environment, health care systems are constantly struggling to contain rapidly rising costs. Drug costs are targeted by a wide variety of measures. Many jurisdictions have implemented reference drug programs (RDPs) or similar therapeutic substitution programs. This paper summarizes the mechanism and rationale of RDPs and presents evidence of their economic effectiveness and clinical safety. RDPs for pharmaceutical reimbursement are based on the assumption that drugs within specified medication groups are therapeutically equivalent and clinically interchangeable and that a common reimbursement level can thus be established. If the evidence documents that a higher price for a given drug does not buy greater effectiveness or reduced toxicity, then under RDP such extra costs are not covered. RDPs or therapeutic substitutions based on therapeutic equivalence are seen as logical extensions of generic substitution that is based on bioequivalence of drugs. If the goal is to achieve full drug coverage for as many patients as possible in the most efficient manner, then RDPs in combination with prior authorization programs are safer and more effective than simplistic fiscal drug policies, including fixed co-payments, co-insurances, or deductibles. RDPs will reduce spending in the less innovative but largest market, while fully covering all patients. Prior authorization will ensure that patients with a specified indication will benefit from the most innovative therapies with full coverage. In practice, however, not all patients and drugs will fit exactly into one of the two categories. Therefore, a process of medically indicated exemptions that will consider full coverage should accompany an RDP. In the current economic environment, health care systems are constantly struggling to contain rapidly rising costs. Drug costs are targeted by a wide variety of measures. Many jurisdictions have implemented reference drug programs, and others are considering

Drug sensitivity profiling identifies potential therapies for lymphoproliferative disorders with overactive JAK/STAT3 signaling

PubMed Central

Kuusanmäki, Heikki; Dufva, Olli; Parri, Elina; van Adrichem, Arjan J.; Rajala, Hanna; Majumder, Muntasir M.; Yadav, Bhagwan; Parsons, Alun; Chan, Wing C.; Wennerberg, Krister; Mustjoki, Satu; Heckman, Caroline A.

2017-01-01

Constitutive JAK/STAT3 signaling contributes to disease progression in many lymphoproliferative disorders. Recent genetic analyses have revealed gain-of-function STAT3 mutations in lymphoid cancers leading to hyperactivation of STAT3, which may represent a potential therapeutic target. Using a functional reporter assay, we screened 306 compounds with selective activity against various target molecules to identify drugs capable of inhibiting the cellular activity of STAT3. Top hits were further validated with additional models including STAT3-mutated natural killer (NK)-cell leukemia/lymphoma cell lines and primary large granular lymphocytic (LGL) leukemia cells to assess their ability to inhibit STAT3 phosphorylation and STAT3 dependent cell viability. We identified JAK, mTOR, Hsp90 and CDK inhibitors as potent inhibitors of both WT and mutant STAT3 activity. The Hsp90 inhibitor luminespib was highly effective at reducing the viability of mutant STAT3 NK cell lines and LGL leukemia patient samples. Luminespib decreased the phosphorylation of mutant STAT3 at Y705, whereas JAK1/JAK2 inhibitor ruxolitinib had reduced efficacy on mutant STAT3 phosphorylation. Additionally, combinations involving Hsp90, JAK and mTOR inhibitors were more effective at reducing cell viability than single agents. Our findings show alternative approaches to inhibit STAT3 activity and suggest Hsp90 as a therapeutic target in lymphoproliferative disorders with constitutively active STAT3. PMID:29228628

A high throughput drug screening assay to identify compounds that promote oligodendrocyte differentiation using acutely dissociated and purified oligodendrocyte precursor cells.

PubMed

Lariosa-Willingham, Karen D; Rosler, Elen S; Tung, Jay S; Dugas, Jason C; Collins, Tassie L; Leonoudakis, Dmitri

2016-09-05

Multiple sclerosis is caused by an autoimmune response resulting in demyelination and neural degeneration. The adult central nervous system has the capacity to remyelinate axons in part through the generation of new oligodendrocytes (OLs). To identify clinical candidate compounds that may promote remyelination, we have developed a high throughput screening (HTS) assay to identify compounds that promote the differentiation of oligodendrocyte precursor cells (OPCs) into OLs. Using acutely dissociated and purified rat OPCs coupled with immunofluorescent image quantification, we have developed an OL differentiation assay. We have validated this assay with a known promoter of differentiation, thyroid hormone, and subsequently used the assay to screen the NIH clinical collection library. We have identified twenty-seven hit compounds which were validated by dose response analysis and the generation of half maximal effective concentration (EC50) values allowed for the ranking of efficacy. The assay identified novel promoters of OL differentiation which we attribute to (1) the incorporation of an OL toxicity pre-screen to allow lowering the concentrations of toxic compounds and (2) the utilization of freshly purified, non-passaged OPCs. These features set our assay apart from other OL differentiation assays used for drug discovery efforts. This acute primary OL-based differentiation assay should be of use to those interested in screening large compound libraries for the identification of drugs for the treatment of MS and other demyelinating diseases.

Integrative relational machine-learning for understanding drug side-effect profiles.

PubMed

Bresso, Emmanuel; Grisoni, Renaud; Marchetti, Gino; Karaboga, Arnaud Sinan; Souchet, Michel; Devignes, Marie-Dominique; Smaïl-Tabbone, Malika

2013-06-26

Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly

Evaluation of commercial multi-drug oral fluid devices to identify 39 new amphetamine-designer drugs.

PubMed

Nieddu, Maria; Burrai, Lucia; Trignano, Claudia; Boatto, Gianpiero

2014-03-01

Recently, the diffusion on the black market of new psychoactive substances not controlled and often sold as 'legal highs', is exponentially increasing in Europe. Generally, the first analysis for these drugs involves an immunoassay screening in urine or plasma. Actually, there is growing interest in the use of oral fluid (OF) as alternative specimen over conventional biological fluids for drug testing, because of the significant advantages, as a non-invasive collection under direct observation without undue embarrassment or invasion of privacy, and a good correlation with plasma analytical data. Few assays have been developed for detection of new psychoactive compounds in biological samples, so it is important to investigate how they may or may not react in pre-existing commercial immunoassays. In this paper, two different multi-drugs oral fluid screen devices (OFDs) (Screen® Multi-Drug OFD and GIMA One Step Multi-Line Screen Test OFD) were evaluated to determine the cross-reactivity of thirty-nine new amphetamine designer drugs, including twelve substances officially recognized as illicit by italian legislation. Cross-reactivity towards most drugs analyzed was <1 in assays targeting amphetamine (AMP) or methamphetamine (MET). Only two (p-methoxyamphetamine and p-methoxymethamphetamine) of all tested amphetamines gave a positive result. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

PubMed

Vilar, Santiago; Hripcsak, George

2017-07-01

Explosion of the availability of big data sources along with the development in computational methods provides a useful framework to study drugs' actions, such as interactions with pharmacological targets and off-targets. Databases related to protein interactions, adverse effects and genomic profiles are available to be used for the construction of computational models. In this article, we focus on the description of biological profiles for drugs that can be used as a system to compare similarity and create methods to predict and analyze drugs' actions. We highlight profiles constructed with different biological data, such as target-protein interactions, gene expression measurements, adverse effects and disease profiles. We focus on the discovery of new targets or pathways for drugs already in the pharmaceutical market, also called drug repurposing, in the interaction with off-targets responsible for adverse reactions and in drug-drug interaction analysis. The current and future applications, strengths and challenges facing all these methods are also discussed. Biological profiles or signatures are an important source of data generation to deeply analyze biological actions with important implications in drug-related studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nanosizing of drugs: Effect on dissolution rate

PubMed Central

Dizaj, S. Maleki; Vazifehasl, Zh.; Salatin, S.; Adibkia, Kh.; Javadzadeh, Y.

2015-01-01

The solubility, bioavailability and dissolution rate of drugs are important parameters for achieving in vivo efficiency. The bioavailability of orally administered drugs depends on their ability to be absorbed via gastrointestinal tract. For drugs belonging to Class II of pharmaceutical classification, the absorption process is limited by drug dissolution rate in gastrointestinal media. Therefore, enhancement of the dissolution rate of these drugs will present improved bioavailability. So far several techniques such as physical and chemical modifications, changing in crystal habits, solid dispersion, complexation, solubilization and liquisolid method have been used to enhance the dissolution rate of poorly water soluble drugs. It seems that improvement of the solubility properties ofpoorly water soluble drugscan translate to an increase in their bioavailability. Nowadays nanotechnology offers various approaches in the area of dissolution enhancement of low aqueous soluble drugs. Nanosizing of drugs in the form of nanoparticles, nanocrystals or nanosuspensions not requiring expensive facilities and equipment or complicated processes may be applied as simple methods to increase the dissolution rate of poorly water soluble drugs. In this article, we attempted to review the effects of nanosizing on improving the dissolution rate of poorly aqueous soluble drugs. According to the reviewed literature, by reduction of drug particle size into nanometer size the total effective surface area is increased and thereby dissolution rate would be enhanced. Additionally, reduction of particle size leads to reduction of the diffusion layer thickness surrounding the drug particles resulting in the increment of the concentration gradient. Each of these process leads to improved bioavailability. PMID:26487886

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii.

PubMed

Shen, Bang; Powell, Robin H; Behnke, Michael S

2017-06-22

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites.

Comprehensive Genomic Profiling Identifies Frequent Drug-Sensitive EGFR Exon 19 Deletions in NSCLC not Identified by Prior Molecular Testing.

PubMed

Schrock, Alexa B; Frampton, Garrett M; Herndon, Dana; Greenbowe, Joel R; Wang, Kai; Lipson, Doron; Yelensky, Roman; Chalmers, Zachary R; Chmielecki, Juliann; Elvin, Julia A; Wollner, Mira; Dvir, Addie; -Gutman, Lior Soussan; Bordoni, Rodolfo; Peled, Nir; Braiteh, Fadi; Raez, Luis; Erlich, Rachel; Ou, Sai-Hong Ignatius; Mohamed, Mohamed; Ross, Jeffrey S; Stephens, Philip J; Ali, Siraj M; Miller, Vincent A

2016-07-01

Reliable detection of drug-sensitive activating EGFR mutations is critical in the care of advanced non-small cell lung cancer (NSCLC), but such testing is commonly performed using a wide variety of platforms, many of which lack rigorous analytic validation. A large pool of NSCLC cases was assayed with well-validated, hybrid capture-based comprehensive genomic profiling (CGP) at the request of the individual treating physicians in the course of clinical care for the purpose of making therapy decisions. From these, 400 cases harboring EGFR exon 19 deletions (Δex19) were identified, and available clinical history was reviewed. Pathology reports were available for 250 consecutive cases with classical EGFR Δex19 (amino acids 743-754) and were reviewed to assess previous non-hybrid capture-based EGFR testing. Twelve of 71 (17%) cases with EGFR testing results available were negative by previous testing, including 8 of 46 (17%) cases for which the same biopsy was analyzed. Independently, five of six (83%) cases harboring C-helical EGFR Δex19 were previously negative. In a subset of these patients with available clinical outcome information, robust benefit from treatment with EGFR inhibitors was observed. CGP identifies drug-sensitive EGFR Δex19 in NSCLC cases that have undergone prior EGFR testing and returned negative results. Given the proven benefit in progression-free survival conferred by EGFR tyrosine kinase inhibitors in patients with these alterations, CGP should be considered in the initial presentation of advanced NSCLC and when previous testing for EGFR mutations or other driver alterations is negative. Clin Cancer Res; 22(13); 3281-5. ©2016 AACR. ©2016 American Association for Cancer Research.

Drug interactions between hormonal contraceptives and psychotropic drugs: a systematic review.

PubMed

Berry-Bibee, Erin N; Kim, Myong-Jin; Simmons, Katharine B; Tepper, Naomi K; Riley, Halley E M; Pagano, H Pamela; Curtis, Kathryn M

2016-12-01

To examine whether the co-administration of hormonal contraceptives (HC) and psychotropic drugs commonly used to treat anxiety and/or depression results in safety or efficacy concerns for either drug. We searched PubMed and Cochrane libraries for clinical or pharmacokinetic (PK) studies that examined co-administration of any HC with psychotropic drugs [selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), oral benzodiazepines, bupropion, mirtazapine, trazadone, buspirone, hydroxyzine, monoamine oxidase inhibitors (MAOIs), or atypical antipsychotics] in reproductive aged women. Of 555 articles identified, 22 articles (18 studies) met inclusion criteria. We identified 5 studies on SSRIs, four on TCAs, one on bupropion, three on atypical antipsychotics and five on oral benzodiazepines. No articles met inclusion criteria for SNRIs, mirtazapine, trazadone, buspirone, hydroxyzine or MAOIs. Overall, clinical studies did not demonstrate differences in unintended pregnancy rates when HCs were administered with and without psychotropic drugs or in psychotropic drug treatment outcomes when psychotropic drugs were administered with and without HCs. PK studies did not demonstrate changes in drug exposure related to contraceptive safety, contraceptive effectiveness or psychotropic drug effectiveness for most classes of psychotropic drugs. However, limited PK data raise concern for HCs increasing systemic exposure of amitriptyline and imipramine (both TCAs), theoretically posing safety concerns. Limited quality and quantity evidence on use of psychotropic drugs and HCs suggests low concern for clinically significant interactions, though no data exist specifically for non-oral formulations of HC. Given the high frequency of use for both HCs and psychotropic drugs among reproductive-age women in the US, this review highlights a need for further research in this area. Copyright © 2016 Elsevier Inc

Automated identification of molecular effects of drugs (AIMED)

PubMed Central

Fathiamini, Safa; Johnson, Amber M; Zeng, Jia; Araya, Alejandro; Holla, Vijaykumar; Bailey, Ann M; Litzenburger, Beate C; Sanchez, Nora S; Khotskaya, Yekaterina; Xu, Hua; Meric-Bernstam, Funda; Bernstam, Elmer V

2016-01-01

Introduction Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technologies to support targeted therapies. To this end, we have developed a system for Automated Identification of Molecular Effects of Drugs, to help biomedical scientists curate this literature to facilitate decision support. Objectives To create an automated system to identify assertions in the literature concerning drugs targeting genes with therapeutic implications and characterize the challenges inherent in automating this process in rapidly evolving domains. Methods We used subject-predicate-object triples (semantic predications) and co-occurrence relations generated by applying the SemRep Natural Language Processing system to MEDLINE abstracts and ClinicalTrials.gov descriptions. We applied customized semantic queries to find drugs targeting genes of interest. The results were manually reviewed by a team of experts. Results Compared to a manually curated set of relationships, recall, precision, and F2 were 0.39, 0.21, and 0.33, respectively, which represents a 3- to 4-fold improvement over a publically available set of predications (SemMedDB) alone. Upon review of ostensibly false positive results, 26% were considered relevant additions to the reference set, and an additional 61% were considered to be relevant for review. Adding co-occurrence data improved results for drugs in early development, but not their better-established counterparts. Conclusions Precision medicine poses unique challenges for biomedical informatics systems that help domain experts find answers to their research questions. Further research is required to improve the performance of such systems, particularly for drugs in development. PMID:27107438

Adverse Effects of Common Drugs: Dietary Supplements.

PubMed

Felix, Todd Matthew; Karpa, Kelly Dowhower; Lewis, Peter R

2015-09-01

Dietary supplement-induced adverse effects often resolve quickly after discontinuation of the offending product, especially in younger patients. The potential for unwanted outcomes can be amplified in elderly patients or those taking multiple prescription drugs, especially where interactions exist with drugs metabolized by cytochrome P450 enzymes. Attributing injury or illness to a specific supplement can be challenging, especially in light of multi-ingredient products, product variability, and variability in reporting, as well as the vast underreporting of adverse drug reactions. Clinicians prescribing a new drug or evaluating a patient with a new symptom complex should inquire about use of herbal and dietary supplements as part of a comprehensive evaluation. Clinicians should report suspected supplement-related adverse effects to the local or state health department, as well as the Food and Drug Administration's MedWatch program (available at https://www.safetyreporting.hhs.gov). Clinicians should consider discussing suspected adverse effects involving drugs, herbal products, or dietary supplements with their community- and hospital-based pharmacists, and explore patient management options with medical or clinical toxicology subspecialists. Written permission from the American Academy of Family Physicians is required for reproduction of this material in whole or in part in any form or medium.

Therapeutic effects of drug-nutrient interactions in the elderly.

PubMed

Roe, D A

1985-02-01

The elderly are the major drug users both because they need specific prescription drugs for control of chronic diseases and because they make excessive use of over-the-counter (OTC) drugs. Therapeutic drugs that are required may be discontinued because the individuals suffer side effects or because the drug is ineffective. Adverse drug reactions in the elderly may result from drug overuse or misuse, slowed drug metabolism or elimination secondary to aging or to age-related chronic disease, intake of alcohol, food-drug incompatibilities, or nutrient-drug interactions. The timing of drug intake in relation to food intake is an important determinant of therapeutic efficacy in the elderly. Food-drug interactions in the gastrointestinal tract may reduce drug absorption. Enteral formula feeding may also interfere with drug absorption. Conversely, absorption of certain drugs (e.g., thiazides) may be promoted by meal-induced slowing of gastric emptying time. Therapeutic diet prescription can influence drug responses in the elderly because the protein composition of the diet influences the rate of drug metabolism. Nutrient depletion secondary to the effect of drugs may be recognized as an important and often avoidable type of adverse drug reaction.

Integrative relational machine-learning for understanding drug side-effect profiles

PubMed Central

2013-01-01

Background Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. Results In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Conclusions Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for

THE EFFECTIVENESS OF COMPULSORY DRUG TREATMENT: A SYSTEMATIC REVIEW

PubMed Central

Werb, D; Kamarulzaman, A; Meacham, MC; Rafful, C; Fisher, B; Strathdee, SA; Wood, E

2016-01-01

Background Despite widespread implementation of compulsory treatment modalities for drug dependence, there has been no systematic evaluation of the scientific evidence on the effectiveness of compulsory drug treatment. Methods We conducted a systematic review of studies assessing the outcomes of compulsory treatment. We conducted a search in duplicate of all relevant peer-reviewed scientific literature evaluating compulsory treatment modalities. The following academic databases were searched: PubMed, PAIS International, Proquest, PsycINFO, Web of Science, Soc Abstracts, JSTOR, EBSCO/Academic Search Complete, REDALYC, SciELO Brazil. We also searched the Internet, and article reference lists, from database inception to July 15th, 2015. Eligibility criteria are as follows: peer-reviewed scientific studies presenting original data. Primary outcome of interest was post-treatment drug use. Secondary outcome of interest was post-treatment criminal recidivism. Results Of an initial 430 potential studies identified, nine quantitative studies met the inclusion criteria. Studies evaluated compulsory treatment options including drug detention facilities, short (i.e. 21-day) and long-term (i.e., 6 months) inpatient treatment, community-based treatment, group-based outpatient treatment, and prison-based treatment. Three studies (33%) reported no significant impacts of compulsory treatment compared with control interventions. Two studies (22%) found equivocal results but did not compare against a control condition. Two studies (22%) observed negative impacts of compulsory treatment on criminal recidivism. Two studies (22%) observed positive impacts of compulsory inpatient treatment on criminal recidivism and drug use. Conclusion There is limited scientific literature evaluating compulsory drug treatment. Evidence does not, on the whole, suggest improved outcomes related to compulsory treatment approaches, with some studies suggesting potential harms. Given the potential for human

A review of illicit psychoactive drug use in elective surgery patients: Detection, effects, and policy.

PubMed

Selvaggi, Gennaro; Spagnolo, Antonio G; Elander, Anna

2017-12-01

Limited information is present in literature regarding detection of illicit drug users visiting physicians when planning elective surgery; also, there is no update manuscript that is illustrating the effects of illicit drugs use that require reconstructive surgery interventions. Aims of this manuscript are: 1) to summarize existing knowledge, and give surgeons information how to detect patients who might possible use illicit drugs; 2) to review the effects of illicit drug use that specifically require reconstructive surgery interventions; 3) to assess on existing policies on asymptomatic illicit drug users when planning elective surgery. Studies were identified by searching systematically in the electronic databases PubMed, Medline, The Cochrane Library and SveMed+. Because of the nature of research questions to be investigated (drug policy and surgery), a "systematic review" was not possible. In spite of some existing policies to detect illicit drug use in specific situations such as workplaces or acute trauma patients, there is a lack of data and lack of information, and subsequently no policy has ever been made, for detection and management of illicit drug use asymptomatic patients requesting or referred for plastic surgery interventions. This manuscript poses questions for further ethical evaluations and future policy. Copyright © 2017 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Systematic Analysis of Cell Cycle Effects of Common Drugs Leads to the Discovery of a Suppressive Interaction between Gemfibrozil and Fluoxetine

PubMed Central

Hoose, Scott A.; Duran, Camille; Malik, Indranil; Eslamfam, Shabnam; Shasserre, Samantha C.; Downing, S. Sabina; Hoover, Evelyn M.; Dowd, Katherine E.; Smith, Roger; Polymenis, Michael

2012-01-01

Screening chemical libraries to identify compounds that affect overall cell proliferation is common. However, in most cases, it is not known whether the compounds tested alter the timing of particular cell cycle transitions. Here, we evaluated an FDA-approved drug library to identify pharmaceuticals that alter cell cycle progression in yeast, using DNA content measurements by flow cytometry. This approach revealed strong cell cycle effects of several commonly used pharmaceuticals. We show that the antilipemic gemfibrozil delays initiation of DNA replication, while cells treated with the antidepressant fluoxetine severely delay progression through mitosis. Based on their effects on cell cycle progression, we also examined cell proliferation in the presence of both compounds. We discovered a strong suppressive interaction between gemfibrozil and fluoxetine. Combinations of interest among diverse pharmaceuticals are difficult to identify, due to the daunting number of possible combinations that must be evaluated. The novel interaction between gemfibrozil and fluoxetine suggests that identifying and combining drugs that show cell cycle effects might streamline identification of drug combinations with a pronounced impact on cell proliferation. PMID:22567160

Systematic analysis of cell cycle effects of common drugs leads to the discovery of a suppressive interaction between gemfibrozil and fluoxetine.

PubMed

Hoose, Scott A; Duran, Camille; Malik, Indranil; Eslamfam, Shabnam; Shasserre, Samantha C; Downing, S Sabina; Hoover, Evelyn M; Dowd, Katherine E; Smith, Roger; Polymenis, Michael

2012-01-01

Screening chemical libraries to identify compounds that affect overall cell proliferation is common. However, in most cases, it is not known whether the compounds tested alter the timing of particular cell cycle transitions. Here, we evaluated an FDA-approved drug library to identify pharmaceuticals that alter cell cycle progression in yeast, using DNA content measurements by flow cytometry. This approach revealed strong cell cycle effects of several commonly used pharmaceuticals. We show that the antilipemic gemfibrozil delays initiation of DNA replication, while cells treated with the antidepressant fluoxetine severely delay progression through mitosis. Based on their effects on cell cycle progression, we also examined cell proliferation in the presence of both compounds. We discovered a strong suppressive interaction between gemfibrozil and fluoxetine. Combinations of interest among diverse pharmaceuticals are difficult to identify, due to the daunting number of possible combinations that must be evaluated. The novel interaction between gemfibrozil and fluoxetine suggests that identifying and combining drugs that show cell cycle effects might streamline identification of drug combinations with a pronounced impact on cell proliferation.

Food-drug interactions.

PubMed

Schmidt, Lars E; Dalhoff, Kim

2002-01-01

Interactions between food and drugs may inadvertently reduce or increase the drug effect. The majority of clinically relevant food-drug interactions are caused by food-induced changes in the bioavailability of the drug. Since the bioavailability and clinical effect of most drugs are correlated, the bioavailability is an important pharmacokinetic effect parameter. However, in order to evaluate the clinical relevance of a food-drug interaction, the impact of food intake on the clinical effect of the drug has to be quantified as well. As a result of quality review in healthcare systems, healthcare providers are increasingly required to develop methods for identifying and preventing adverse food-drug interactions. In this review of original literature, we have tried to provide both pharmacokinetic and clinical effect parameters of clinically relevant food-drug interactions. The most important interactions are those associated with a high risk of treatment failure arising from a significantly reduced bioavailability in the fed state. Such interactions are frequently caused by chelation with components in food (as occurs with alendronic acid, clodronic acid, didanosine, etidronic acid, penicillamine and tetracycline) or dairy products (ciprofloxacin and norfloxacin), or by other direct interactions between the drug and certain food components (avitriptan, indinavir, itraconazole solution, levodopa, melphalan, mercaptopurine and perindopril). In addition, the physiological response to food intake, in particular gastric acid secretion, may reduce the bioavailability of certain drugs (ampicillin, azithromycin capsules, didanosine, erythromycin stearate or enteric coated, and isoniazid). For other drugs, concomitant food intake may result in an increase in drug bioavailability either because of a food-induced increase in drug solubility (albendazole, atovaquone, griseofulvin, isotretinoin, lovastatin, mefloquine, saquinavir and tacrolimus) or because of the secretion of

Using a drug facts box to communicate drug benefits and harms: two randomized trials.

PubMed

Schwartz, Lisa M; Woloshin, Steven; Welch, H Gilbert

2009-04-21

Direct-to-consumer prescription drug ads typically fail to provide fundamental information that consumers need to make informed decisions: data on how well the drug works. To see whether providing consumers with a drug facts box-a table quantifying outcomes with and without the drug-improves knowledge and affects judgments about prescription medications. Two randomized, controlled trials conducted between October 2006 and April 2007: a symptom drug box trial using direct-to-consumer ads for a histamine-2 blocker and a proton-pump inhibitor to treat heartburn, and a prevention drug box trial using direct-to-consumer ads for a statin and clopidogrel to prevent cardiovascular events. National sample of U.S. adults identified by random-digit dialing. Adults age 35 to 70 years who completed a mailed survey; the final samples comprised 231 participants with completed surveys in the symptom drug box trial (49% response rate) and 219 in the prevention drug box trial (46% response rate). In both trials, the control group received 2 actual drug ads (including both the front page and brief summary). The drug box group received the same ads, except that the brief summary was replaced by a drug facts box. Choice between drugs (primary outcome of the symptom drug box trial) and accurate perceptions of drug benefits and side effects (primary outcome of the prevention drug box trial). In the symptom drug box trial, 70% of the drug box group and 8% of the control group correctly identified the PPI as being "a lot more effective" than the histamine-2 blocker (P < 0.001), and 80% and 38% correctly recognized that the side effects of the 2 drugs were similar (P < 0.001). When asked what they would do if they had bothersome heartburn and could have either drug for free, 68% of the drug box group and 31% of the control group chose the proton-pump inhibitor, the superior drug (P < 0.001). In the prevention drug box trial, the drug box improved consumers' knowledge of the benefits and

[Effects of the new comprehensive system for designating illegal drug components on the abuse of designer drugs and future problems based on an online questionnaire].

PubMed

Morino, Taichi; Okazaki, Mitsuhiro; Toda, Takaki; Yokoyama, Takashi

2015-12-01

Recently, the abuse of designer drugs has become a social problem. Designer drugs are created by modifying part of the chemical structure of drugs that have already been categorized as illegal, thereby creating a different chemical compound in order to evade Pharmaceutical Affairs Law regulations. The new comprehensive system for designating illegal drug components has been in effect since March 2013, and many designer drugs can now be regulated. We conducted an online questionnaire survey of people with a history of designer drug use to elucidate the effects of the new system on the abuse of designer drugs and to identify potential future problems. Over half the subjects obtained designer drugs only before the new system was implemented. Awareness of the system was significantly lower among subjects who obtained designer drugs for the first time after its introduction than those who obtained the drugs only before its implementation. Due to the new system, all methods of acquiring designer drugs saw decreases in activity. However, the ratio of the acquisition of designer drugs via the Internet increased. Since over 50% of the subjects never obtained designer drugs after the new system was introduced, goals that aimed to make drug procurement more difficult were achieved. However, awareness of the new system among subjects who obtained designer drugs after the new system was introduced was significantly low. Therefore, fostering greater public awareness of the new system is necessary. The results of the questionnaire also suggested that acquiring designer drugs through the Internet has hardly been affected by the new system. We strongly hope that there will be a greater push to restrict the sale of designer drugs on the Internet in the near future.

Drug Court Effectiveness: A Matched Cohort Study in the Dane County Drug Treatment Court

ERIC Educational Resources Information Center

Brown, Randall

2011-01-01

Drug treatment courts (DTCs) are widely viewed as effective diversion programs for drug-involved offenders; however, previous studies frequently used flawed comparison groups. In the current study, the author compared rates of recidivism for drug court participants to rates for a traditionally adjudicated comparison group matched on potentially…

A dictionary to identify small molecules and drugs in free text.

PubMed

Hettne, Kristina M; Stierum, Rob H; Schuemie, Martijn J; Hendriksen, Peter J M; Schijvenaars, Bob J A; Mulligen, Erik M van; Kleinjans, Jos; Kors, Jan A

2009-11-15

From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers. We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated corpus, and conclude the following: (i) each of the different processing steps increase precision with a minor loss of recall; (ii) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (iii) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (iv) the performance of a dictionary based on ChemIDplus alone is comparable to the performance of the combined dictionary. The combined dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web site http://www.biosemantics.org/chemlist.

Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.

PubMed

Vilar, Santiago; Hripcsak, George

2016-01-01

Drug-target identification is crucial to discover novel applications for existing drugs and provide more insights about mechanisms of biological actions, such as adverse drug effects (ADEs). Computational methods along with the integration of current big data sources provide a useful framework for drug-target and drug-adverse effect discovery. In this article, we propose a method based on the integration of 3D chemical similarity, target and adverse effect data to generate a drug-target-adverse effect predictor along with a simple leveraging system to improve identification of drug-targets and drug-adverse effects. In the first step, we generated a system for multiple drug-target identification based on the application of 3D drug similarity into a large target dataset extracted from the ChEMBL. Next, we developed a target-adverse effect predictor combining targets from ChEMBL with phenotypic information provided by SIDER data source. Both modules were linked to generate a final predictor that establishes hypothesis about new drug-target-adverse effect candidates. Additionally, we showed that leveraging drug-target candidates with phenotypic data is very useful to improve the identification of drug-targets. The integration of phenotypic data into drug-target candidates yielded up to twofold precision improvement. In the opposite direction, leveraging drug-phenotype candidates with target data also yielded a significant enhancement in the performance. The modeling described in the current study is simple and efficient and has applications at large scale in drug repurposing and drug safety through the identification of mechanism of action of biological effects.

Effects of Drugs

MedlinePlus

... Used Drugs in the Past Drug Use Prevention Phone Numbers and Websites Search ... who aren't yet born. Drug use can hurt the body and the brain, sometimes forever. Drug use can also lead to addiction, a long-lasting brain disease in which people ...

Nanomaterials potentiating standard chemotherapy drugs' effect

NASA Astrophysics Data System (ADS)

Kazantsev, S. O.; Korovin, M. S.

2017-09-01

Application of antitumor chemotherapeutic drugs is hindered by a number of barriers, multidrug resistance that makes effective drug deposition inside cancer cells difficult is among them. Recent research shows that potential efficiency of anticancer drugs can be increased with nanoparticles. This review is devoted to the application of nanoparticles for cancer treatment. Various types of nanoparticles currently used in medicine are reviewed. The nanoparticles that have been used for cancer therapy and targeted drug delivery to damaged sites of organism are described. Also, the possibility of nanoparticles application for cancer diagnosis that could help early detection of tumors is discussed. Our investigations of antitumor activity of low-dimensional nanostructures based on aluminum oxides and hydroxides are briefly reviewed.

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

Disentangling incentives effects of insurance coverage from adverse selection in the case of drug expenditure: a finite mixture approach.

PubMed

Munkin, Murat K; Trivedi, Pravin K

2010-09-01

This paper takes a finite mixture approach to model heterogeneity in incentive and selection effects of drug coverage on total drug expenditure among the Medicare elderly US population. Evidence is found that the positive drug expenditures of the elderly population can be decomposed into two groups different in the identified selection effects and interpreted as relatively healthy with lower average expenditures and relatively unhealthy with higher average expenditures, accounting for approximately 25 and 75% of the population, respectively. Adverse selection into drug insurance appears to be strong for the higher expenditure component and weak for the lower expenditure group. Copyright (c) 2010 John Wiley & Sons, Ltd.

Fractured families: parental perspectives of the effects of adolescent drug abuse on family life.

PubMed

Jackson, Debra; Usher, Kim; O'Brien, Louise

Drug use in young people has serious ramifications for health and well-being of young people and their families and continues to be an area of major concern for health workers. Though the task of dealing with drug-related problems falls on families, particularly parents, very little literature has explored parental experiences of managing drug use within the context of family life. Eighteen parents of drug-abusing young people were recruited into this qualitative study that aimed to develop understandings into the effects of adolescent drug use on family life. Findings revealed that the experience of having a drug-abusing adolescent family member had a profound effect on other members of the immediate family. Family relationships were fractured and split as a result of the on-going destructive and damaging behaviour of the drug-abusing young person. Five themes were identified that captured the concept of fractured families. These are: betrayal and loss of trust: 'You had to have the doors locked'; abuse, threats and violence: 'there were holes in the wall'; sibling anger and resentment: 'Better off now with him gone'; isolated, disgraced and humiliated: 'You are on your own with it'; and, feeling blamed: 'You are not a good parent'. Implications for practice and further research are drawn from the findings of this paper.

A genome-wide RNAi screen identifies potential drug targets in a C. elegans model of α1-antitrypsin deficiency.

PubMed

O'Reilly, Linda P; Long, Olivia S; Cobanoglu, Murat C; Benson, Joshua A; Luke, Cliff J; Miedel, Mark T; Hale, Pamela; Perlmutter, David H; Bahar, Ivet; Silverman, Gary A; Pak, Stephen C

2014-10-01

α1-Antitrypsin deficiency (ATD) is a common genetic disorder that can lead to end-stage liver and lung disease. Although liver transplantation remains the only therapy currently available, manipulation of the proteostasis network (PN) by small molecule therapeutics offers great promise. To accelerate the drug-discovery process for this disease, we first developed a semi-automated high-throughput/content-genome-wide RNAi screen to identify PN modifiers affecting the accumulation of the α1-antitrypsin Z mutant (ATZ) in a Caenorhabditis elegans model of ATD. We identified 104 PN modifiers, and these genes were used in a computational strategy to identify human ortholog-ligand pairs. Based on rigorous selection criteria, we identified four FDA-approved drugs directed against four different PN targets that decreased the accumulation of ATZ in C. elegans. We also tested one of the compounds in a mammalian cell line with similar results. This methodology also proved useful in confirming drug targets in vivo, and predicting the success of combination therapy. We propose that small animal models of genetic disorders combined with genome-wide RNAi screening and computational methods can be used to rapidly, economically and strategically prime the preclinical discovery pipeline for rare and neglected diseases with limited therapeutic options. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mechanistic models enable the rational use of in vitro drug-target binding kinetics for better drug effects in patients.

PubMed

de Witte, Wilhelmus E A; Wong, Yin Cheong; Nederpelt, Indira; Heitman, Laura H; Danhof, Meindert; van der Graaf, Piet H; Gilissen, Ron A H J; de Lange, Elizabeth C M

2016-01-01

Drug-target binding kinetics are major determinants of the time course of drug action for several drugs, as clearly described for the irreversible binders omeprazole and aspirin. This supports the increasing interest to incorporate newly developed high-throughput assays for drug-target binding kinetics in drug discovery. A meaningful application of in vitro drug-target binding kinetics in drug discovery requires insight into the relation between in vivo drug effect and in vitro measured drug-target binding kinetics. In this review, the authors discuss both the relation between in vitro and in vivo measured binding kinetics and the relation between in vivo binding kinetics, target occupancy and effect profiles. More scientific evidence is required for the rational selection and development of drug-candidates on the basis of in vitro estimates of drug-target binding kinetics. To elucidate the value of in vitro binding kinetics measurements, it is necessary to obtain information on system-specific properties which influence the kinetics of target occupancy and drug effect. Mathematical integration of this information enables the identification of drug-specific properties which lead to optimal target occupancy and drug effect in patients.

Shotgun ecotoxicoproteomics of Daphnia pulex: biochemical effects of the anticancer drug tamoxifen.

PubMed

Borgatta, Myriam; Hernandez, Céline; Decosterd, Laurent Arthur; Chèvre, Nathalie; Waridel, Patrice

2015-01-02

Among pollutants released into the environment by human activities, residues of pharmaceuticals are an increasing matter of concern because of their potential impact on ecosystems. The aim of this study was to analyze differences of protein expression resulting from acute (2 days) and middle-term (7 days) exposure of aquatic microcrustacean Daphnia pulex to the anticancer drug tamoxifen. Using a liquid chromatography-mass spectrometry shotgun approach, about 4000 proteins could be identified, providing the largest proteomics data set of D. pulex published up to now. Considering both time points and tested concentrations, 189 proteins showed a significant fold change. The identity of regulated proteins suggested a decrease in translation, an increase in protein degradation and changes in carbohydrate and lipid metabolism as the major effects of the drug. Besides these impacted processes, which reflect a general stress response of the organism, some other regulated proteins play a role in Daphnia reproduction. These latter results are in accordance with our previous observations of the impact of tamoxifen on D. pulex reproduction and illustrate the potential of ecotoxicoproteomics to unravel links between xenobiotic effects at the biochemical and organismal levels. Data are available via ProteomeXchange with identifier PXD001257.

“High On My Own Supply”: Correlates of Drug Dealing among Heterosexually-identified Methamphetamine Users

PubMed Central

Semple, Shirley J.; Strathdee, Steffanie A.; Volkmann, Tyson; Zians, Jim; Patterson, Thomas L.

2011-01-01

Although rates of methamphetamine use continue to increase throughout the United States, little is known about the individuals who sell methamphetamine at the street level. This exploratory study examined the prevalence and correlates of drug-dealing behavior in a sample of 404 heterosexually-identified methamphetamine users who were participants in a sexual risk reduction intervention in San Diego, CA. Twenty-nine percent of participants (N = 116) reported “dealing” methamphetamine in the past two months. In a multivariate logistic regression, methamphetamine dealing was associated with being male (OR = 1.99; 95% CI 1.16 – 3.39), younger age (OR = 1.87 per year; 95% CI 1.10 – 3.17), more frequent use of methamphetamine (OR = 2.69; 95% CI 1.59 – 4.57), injecting methamphetamine (OR = 3.10; 95% CI 1.79 – 5.37), and higher hostility scores (OR = 1.07 per unit increase; 95% CI 1.01 – 1.13). These characteristics, particularly intensity of drug use and hostility, may be associated with greater resistance to drug treatment and lower success in treatment programs. PMID:21999496

Effectiveness of a Risk Screener in Identifying Hepatitis C Virus in a Primary Care Setting

PubMed Central

Litwin, Alain H.; Smith, Bryce D.; Koppelman, Elisa A.; McKee, M. Diane; Christiansen, Cindy L.; Gifford, Allen L.; Weinbaum, Cindy M.; Southern, William N.

2012-01-01

Objectives. We evaluated an intervention designed to identify patients at risk for hepatitis C virus (HCV) through a risk screener used by primary care providers. Methods. A clinical reminder sticker prompted physicians at 3 urban clinics to screen patients for 12 risk factors and order HCV testing if any risks were present. Risk factor data were collected from the sticker; demographic and testing data were extracted from electronic medical records. We used the t test, χ2 test, and rank-sum test to compare patients who had and had not been screened and developed an analytic model to identify the incremental value of each element of the screener. Results. Among screened patients, 27.8% (n = 902) were identified as having at least 1 risk factor. Of screened patients with risk factors, 55.4% (n = 500) were tested for HCV. Our analysis showed that 7 elements (injection drug use, intranasal drug use, elevated alanine aminotransferase, transfusions before 1992, ≥ 20 lifetime sex partners, maternal HCV, existing liver disease) accounted for all HCV infections identified. Conclusions. A brief risk screener with a paper-based clinical reminder was effective in increasing HCV testing in a primary care setting. PMID:22994166

The effect of grapefruit juice on drug disposition

USDA-ARS?s Scientific Manuscript database

Since their initial discovery in 1989, grapefruit juice-drug interactions have received extensive interest from the scientific, medical, regulatory, and lay communities. Although knowledge regarding the effects of grapefruit juice on drug disposition continues to expand, the list of drugs studied in...

Popping the balloon effect: assessing drug law enforcement in terms of displacement, diffusion, and the containment hypothesis.

PubMed

Windle, James; Farrell, Graham

2012-01-01

The "balloon effect" is an often used but rather dismissive representation of the effects of drug law enforcement. It implies a hydraulic displacement model and an impervious illicit drug trade. This paper reviews theoretical and empirical developments in policing and crime prevention. Based on this, 10 types of displacement are identified and four arguments developed: (1) Displacement is less extensive and harmful than often contended; (2) Where displacement may occur it preferably should be exploited as a policy tool to delay the illicit drug industry and deflect it to less harmful locations and forms; (3) The opposite of displacement occurs, termed a diffusion of drug control benefits, wherein law enforcement has benefits that extend further than envisaged, and has 10 types mirroring those of displacement; (4) The net impact of drug law enforcement is often underestimated, and a containment hypothesis may offer a more accurate framework for evaluation.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

PubMed Central

Shen, Bang; Powell, Robin H.; Behnke, Michael S.

2017-01-01

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites. PMID:28671645

Suicide Risk in College Students: The Effects of Internet Addiction and Drug Use

ERIC Educational Resources Information Center

Genctanirim Kurt, Dilek

2015-01-01

This study aims to identify the factors in suicide risk among college students by examining the direct and indirect effects of drug use, internet addiction, gender, and alcohol use on suicide risk. The sample of the study is composed of 975 students studying at different faculties of Ahi Evran University during the academic year 2011-2012. They…

Obesity and Pediatric Drug Development.

PubMed

Vaughns, Janelle D; Conklin, Laurie S; Long, Ying; Zheng, Panli; Faruque, Fahim; Green, Dionna J; van den Anker, John N; Burckart, Gilbert J

2018-05-01

There is a lack of dosing guidelines for use in obese children. Moreover, the impact of obesity on drug safety and clinical outcomes is poorly defined. The paucity of information needed for the safe and effective use of drugs in obese patients remains a problem, even after drug approval. To assess the current incorporation of obesity as a covariate in pediatric drug development, the pediatric medical and clinical pharmacology reviews under the Food and Drug Administration (FDA) Amendments Act of 2007 and the FDA Safety and Innovation Act (FDASIA) of 2012 were reviewed for obesity studies. FDA labels were also reviewed for statements addressing obesity in pediatric patients. Forty-five drugs studied in pediatric patients under the FDA Amendments Act were found to have statements and key words in the medical and clinical pharmacology reviews and labels related to obesity. Forty-four products were identified similarly with pediatric studies under FDASIA. Of the 89 product labels identified, none provided dosing information related to obesity. The effect of body mass index on drug pharmacokinetics was mentioned in only 4 labels. We conclude that there is little information presently available to provide guidance related to dosing in obese pediatric patients. Moving forward, regulators, clinicians, and the pharmaceutical industry should consider situations in drug development in which the inclusion of obese patients in pediatric trials is necessary to facilitate the safe and effective use of new drug products in the obese pediatric population. © 2018, The American College of Clinical Pharmacology.

The anti-hepatitis drug use effect and inventory management optimization from the perspective of hospital drug supply chain.

PubMed

Liu, Zhanyu

2017-09-01

By analyzing the current hospital anti hepatitis drug use, dosage, indications and drug resistance, this article studied the drug inventory management and cost optimization. The author used drug utilization evaluation method, analyzed the amount and kind distribution of anti hepatitis drugs and made dynamic monitoring of inventory. At the same time, the author puts forward an effective scheme of drug classification management, uses the ABC classification method to classify the drugs according to the average daily dose of drugs, and implements the automatic replenishment plan. The design of pharmaceutical services supply chain includes drug procurement platform, warehouse management system and connect to the hospital system through data exchange. Through the statistical analysis of drug inventory, we put forward the countermeasures of drug logistics optimization. The results showed that drug replenishment plan can effectively improve drugs inventory efficiency.

Content and Usability Evaluation of Patient Oriented Drug-Drug Interaction Websites.

PubMed

Adam, Terrence J; Vang, Joseph

Drug-Drug Interactions (DDI) are an important source of preventable adverse drug events and a common reason for hospitalization among patients on multiple drug therapy regimens. DDI information systems are important patient safety tools with the capacity to identify and warn health professionals of clinically significant DDI risk. While substantial research has been completed on DDI information systems in professional settings such as community, hospital, and independent pharmacies; there has been limited research on DDI systems offered through online websites directly for use by ambulatory patients. The focus of this project is to test patient oriented website capacity to correctly identify drug interactions among well established and clinically significant medication combinations and convey clinical risk data to patients. The patient education capability was assessed by evaluating website Information Capacity, Patient Usability and Readability. The study results indicate that the majority of websites identified which met the inclusion and exclusion criteria operated similarly, but vary in risk severity assessment and are not optimally patient oriented to effectively deliver risk information. The limited quality of information and complex medical term content complicate DDI risk data conveyance and the sites may not provide optimal information delivery to allow medication consumers to understand and manage their medication regimens.

A Weighty Matter: Heaviness Influences the Evaluation of Disease Severity, Drug Effectiveness, and Side Effects

PubMed Central

Kaspar, Kai

2013-01-01

Peoples' perception of diseases and pharmaceutical drugs is a critical issue in health research. Beliefs about disease severity influence the compliance with recommendations for convalescence and the motivation to perform proper health-behavior. The estimated effectiveness of drugs and severity of side effects influence medication adherence and contribute to placebo effects. The present paper closes the gap between these effects and the concept of embodied cognition from a metaphor-enriched perspective. In five studies, we demonstrate that the bodily sensation of weight influences our evaluations of diseases and drugs. The experience of heaviness enhanced the estimated seriousness of diseases and the estimated effectiveness of drugs. The perceived seriousness of drug side effects was also affected by weight but only when drug effectiveness was not attended to. Moreover, the incidental sensation of weight shows a novel effect when evaluating weight-related drugs. The results are in line with the idea of embodied metaphors and reveal important boundary conditions which contribute to a better understanding of the underlying mechanisms. PMID:24244302

Nephrotoxic effects of designer drugs: synthetic is not better!

PubMed

Luciano, Randy L; Perazella, Mark A

2014-06-01

Designer drugs are synthetic, psychoactive substances with similar structures and activity to existing scheduled drugs or controlled chemical compounds. The use of these drugs is not generally considered illegal and they cannot be detected using standard toxicology tests--essentially they are considered to be 'legal highs'. Over the past several years, increasing numbers of designer drugs have become available. These drugs are classified as amphetamine derivatives, phenylpiperazine derivatives, synthetic cathinones, synthetic cannabinoids, phencyclidine derivatives and synthetic opioids. Although euphoria is the desired effect, neuropsychiatric and cardiac manifestations are frequently observed in individuals using these drugs at high doses or using drugs that are contaminated with other substances. Some designer drugs are also associated with adverse renal effects, including acute kidney injury from pigment nephropathy, acute tubular necrosis, obstructive nephropathy and hyponatraemia. The misuse of these drugs should be recognized and clinicians made aware of the potential for acute nephrotoxicity as the health burden of these compounds increases.

Integrating virtual screening and biochemical experimental approach to identify potential anti-cancer agents from drug databank.

PubMed

Deka, Suman Jyoti; Roy, Ashalata; Manna, Debasis; Trivedi, Vishal

2018-06-01

Chemical libraries constitute a reservoir of pharmacophoric molecules to identify potent anti-cancer agents. Virtual screening of heterocyclic compound library in conjugation with the agonist-competition assay, toxicity-carcinogenicity analysis, and string-based structural searches enabled us to identify several drugs as potential anti-cancer agents targeting protein kinase C (PKC) as a target. Molecular modeling study indicates that Cinnarizine fits well within the PKC C2 domain and exhibits extensive interaction with the protein residues. Molecular dynamics simulation of PKC-Cinnarizine complex at different temperatures (300, 325, 350, 375, and 400[Formula: see text]K) confirms that Cinnarizine fits nicely into the C2 domain and forms a stable complex. The drug Cinnarizine was found to bind PKC with a dissociation constant Kd of [Formula: see text]M. The breast cancer cells stimulated with Cinnarizine causes translocation of PKC-[Formula: see text] to the plasma membrane as revealed by immunoblotting and immunofluorescence studies. Cinnarizine also dose dependently reduced the viability of MDAMB-231 and MCF-7 breast cancer cells with an IC[Formula: see text] of [Formula: see text] and [Formula: see text]g/mL, respectively. It is due to the disturbance of cell cycle of breast cancer cells with reduction of S-phase and accumulation of cells in G1-phase. It disturbs mitochondrial membrane potentials to release cytochrome C into the cytosol and activates caspase-3 to induce apoptosis in cancer cells. The cell death was due to induction of apoptosis involving mitochondrial pathway. Hence, the current study has assigned an additional role to Cinnarizine as an activator of PKC and potentials of the approach to identify new molecules for anti-cancer therapy. Thus, in silico screening along with biochemical experimentation is a robust approach to assign additional roles to the drugs present in the databank for anti-cancer therapy.

Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

PubMed Central

Song, Min

2016-01-01

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

Is Neural Processing of Negative Stimuli Altered in Addiction Independent of Drug Effects? Findings From Drug-Naïve Youth with Internet Gaming Disorder.

PubMed

Yip, Sarah W; Gross, James J; Chawla, Megha; Ma, Shan-Shan; Shi, Xing-Hui; Liu, Lu; Yao, Yuan-Wei; Zhu, Lei; Worhunsky, Patrick D; Zhang, Jintao

2018-05-01

Difficulties in emotion regulation are commonly reported among individuals with alcohol and drug addictions and contribute to the acquisition and maintenance of addictive behaviors. Alterations in neural processing of negative affective stimuli have further been demonstrated among individuals with addictions. However, it is unclear whether these alterations are a general feature of addictions or are a result of prolonged exposure to drugs of abuse. To test the hypothesis of altered negative affect processing independent of drug effects, this study assessed neural function among drug-naïve youth with a behavioral addiction-Internet gaming disorder (IGD). Fifty-six young adults (28 with IGD, 28 matched controls) participated in fMRI scanning during performance of a well-validated emotion regulation task. Between-group differences in neural activity during task performance were assessed using a whole-brain, mixed-effects ANOVA with correction for multiple comparisons at currently recommended thresholds (voxel-level p<0.001, pFWE<0.05). Compared to controls, youth with IGD exhibited significantly blunted neural responses within distributed subcortical and cortical regions including the striatum, insula, lateral prefrontal cortex and anterior cingulate in response to negative affective cues, as well as during emotion regulation. Independent component analysis (ICA) further identified between-group differences in engagement of a fronto-cingulo-parietal network, involving decreased engagement in IGD youth relative to controls. Study findings are largely consistent with those from prior neuroimaging studies in substance-use disorders, thus raising the possibility that neural processing of negative affect may be blunted across drug and behavioral addictions independent of acute or chronic drug effects.

Drug labeling and exposure in neonates.

PubMed

Laughon, Matthew M; Avant, Debbie; Tripathi, Nidhi; Hornik, Christoph P; Cohen-Wolkowiez, Michael; Clark, Reese H; Smith, P Brian; Rodriguez, William

2014-02-01

Federal legislation has led to a notable increase in pediatric studies submitted to the Food and Drug Administration (FDA), resulting in new pediatric information in product labeling. However, approximately 50% of drug labels still have insufficient information on safety, efficacy, or dosing in children. Neonatal information in labeling is even scarcer because neonates comprise a vulnerable subpopulation for which end-point development is lagging and studies are more challenging. To quantify progress made in neonatal studies and neonatal information in product labeling as a result of recent legislation. We identified a cohort of drug studies between 1997 and 2010 that included neonates as a result of pediatric legislation using information available on the FDA website. We determined what studies were published in the medical literature, the legislation responsible for the studies, and the resulting neonatal labeling changes. We then examined the use of these drugs in a cohort of neonates admitted to 290 neonatal intensive care units (NICUs) (the Pediatrix Data Warehouse) in the United States from 2005 to 2010. Infants exposed to a drug studied in neonates as identified by the FDA website. Number of drug studies with neonates and rate of exposure per 1000 admissions among infants admitted to an NICU. In a review of the FDA databases, we identified 28 drugs studied in neonates and 24 related labeling changes. Forty-one studies encompassed the 28 drugs, and 31 (76%) of these were published. Eleven (46%) of the 24 neonatal labeling changes established safety and effectiveness. In a review of a cohort of 446,335 hospitalized infants, we identified 399 drugs used and 1,525,739 drug exposures in the first 28 postnatal days. Thirteen (46%) of the 28 drugs studied in neonates were not used in NICUs; 8 (29%) were used in fewer than 60 neonates. Of the drugs studied, ranitidine was used most often (15,627 neonates, 35 exposures per 1000 admissions). Few drug labeling changes

An attention-based effective neural model for drug-drug interactions extraction.

PubMed

Zheng, Wei; Lin, Hongfei; Luo, Ling; Zhao, Zhehuan; Li, Zhengguang; Zhang, Yijia; Yang, Zhihao; Wang, Jian

2017-10-10

Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory. In this study, we propose an effective model that classifies DDIs from the literature by combining an attention mechanism and a recurrent neural network with long short-term memory (LSTM) units. In our approach, first, a candidate-drug-oriented input attention acting on word-embedding vectors automatically learns which words are more influential for a given drug pair. Next, the inputs merging the position- and POS-embedding vectors are passed to a bidirectional LSTM layer whose outputs at the last time step represent the high-level semantic information of the whole sentence. Finally, a softmax layer performs DDI classification. Experimental results from the DDIExtraction 2013 corpus show that our system performs the best with respect to detection and classification (84.0% and 77.3%, respectively) compared with other state-of-the-art methods. In particular, for the Medline-2013 dataset with long and complex sentences, our F-score far exceeds those of top-ranking systems by 12.6%. Our approach effectively improves the performance of DDI classification tasks. Experimental analysis demonstrates that our model performs better with respect to recognizing not only close-range but also long-range patterns among words, especially for long, complex and compound sentences.

Cost-effectiveness analysis of microdose clinical trials in drug development.

PubMed

Yamane, Naoe; Igarashi, Ataru; Kusama, Makiko; Maeda, Kazuya; Ikeda, Toshihiko; Sugiyama, Yuichi

2013-01-01

Microdose (MD) clinical trials have been introduced to obtain human pharmacokinetic data early in drug development. Here we assessed the cost-effectiveness of microdose integrated drug development in a hypothetical model, as there was no such quantitative research that weighed the additional effectiveness against the additional time and/or cost. First, we calculated the cost and effectiveness (i.e., success rate) of 3 types of MD integrated drug development strategies: liquid chromatography-tandem mass spectrometry, accelerator mass spectrometry, and positron emission tomography. Then, we analyzed the cost-effectiveness of 9 hypothetical scenarios where 100 drug candidates entering into a non-clinical toxicity study were selected by different methods as the conventional scenario without MD. In the base-case, where 70 drug candidates were selected without MD and 30 selected evenly by one of the three MD methods, incremental cost-effectiveness ratio per one additional drug approved was JPY 12.7 billion (US$ 0.159 billion), whereas the average cost-effectiveness ratio of the conventional strategy was JPY 24.4 billion, which we set as a threshold. Integrating MD in the conventional drug development was cost-effective in this model. This quantitative analytical model which allows various modifications according to each company's conditions, would be helpful for guiding decisions early in clinical development.

Prevalent new-user cohort designs for comparative drug effect studies by time-conditional propensity scores.

PubMed

Suissa, Samy; Moodie, Erica E M; Dell'Aniello, Sophie

2017-04-01

Studies of the real-world comparative effectiveness of drugs conducted using computerized healthcare databases typically involve an incident new-user cohort design for head-to-head comparisons between two medications, using exclusively treatment-naïve patients. However, the desired contrast often involves one new drug compared with an older drug, of which many users of the new drug may have switched from, seriously restricting the scope of incident new-user studies. We introduce prevalent new-user cohort designs for head-to-head comparative drug effect studies, where incident new users are scarce. We define time-based and prescription-based exposure sets to compute time-conditional propensity scores of initiating the newer drug and to identify matched subjects receiving the comparator drug. We illustrate this approach using data from the UK's Clinical Practice Research Datalink to evaluate whether the newer glucagon-like peptide-1 receptor agonists (GLP-1 analogs) used to treat type 2 diabetes increase the risk of heart failure, in comparison with the older similarly indicated sulfonylureas. Of the 170 031 users of antidiabetic agents from 2000 onwards, 79 682 used sulfonylureas (first use 2000), while 6196 used GLP-1 analogs (first use 2007), 75% of which had previously used a sulfonylurea. After matching each GLP-1 analog user to a sulfonylurea user on the time-conditional propensity scores from prescription-based exposure sets, the hazard ratio of heart failure with GLP-1 use was 0.73 (95%CI: 0.57-0.93). The proposed prevalent new-user cohort design for comparative drug effects studies allows the use of all or most patients exposed to the newer drug, thus permitting a more comprehensive assessment of a new drug's safety. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Identifying Some Factors That Might Predispose Drug Abuse among Learners in a South African Township School

ERIC Educational Resources Information Center

Grobler, R.; Khatite, M.

2012-01-01

This study inquires into some of the factors that might predispose the use and abuse of drugs among secondary school learners in a township school. The objective of this research is to identify these factors and to offer a few suggestions on how the abuse may be prevented. A quantitative research strategy is used and a document analysis technique…

Consistency of psychotropic drug-drug interactions listed in drug monographs.

PubMed

Liu, Xinyue; Hatton, Randy C; Zhu, Yanmin; Hincapie-Castillo, Juan M; Bussing, Regina; Barnicoat, Marie; Winterstein, Almut G

With an increasing prevalence of psychotropic polypharmacy, clinicians depend on drug-drug interaction (DDI) references to ensure safe regimens, but the consistency of such information is frequently questioned. To evaluate the consistency of psychotropic DDIs documented in Clinical Pharmacology (CP), Micromedex (MM), and Lexicomp (LC) and summarize consistent psychotropic DDIs. In May 2016, we extracted severe or major psychotropic DDIs for 102 psychotropic drugs, including central nervous system (CNS) stimulants, antidepressants, an antimanic agent (lithium), antipsychotics, anticonvulsants, and anxiolytics-sedatives-hypnotics from CP, MM, and LC. We then summarized the psychotropic DDIs that were included in all 3 references and with evidence quality of "excellent" or "good" based on MM. We identified 1496, 938, and 1006 unique severe or major psychotropic DDIs from CP, MM, and LC, respectively. Common adverse effects related to psychotropic DDIs include increased or decreased effectiveness, CNS depression, neurotoxicity, QT prolongation, serotonin syndrome, and multiple adverse effects. Among these interactions, only 371 psychotropic DDIs were documented in all 3 references, 59 of which had "excellent" or "good" quality of evidence based on MM. The consistency of psychotropic DDI documentation across CP, MM, and LC is poor. DDI documentations need standards that would encourage consistency among drug information references. The list of the 59 DDIs may be useful in the assessment of psychotropic polypharmacy and highlighting DDI alerts in clinical practice. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Computer listing of the effects of drugs on laboratory data

PubMed Central

Young, D. S.; Thomas, D. W.; Friedman, R. B.

1972-01-01

A listing of approximately 10000 effects of drugs on tests performed in clinical laboratories has been developed in a time-shared computer. The list contains a directory for matching proprietary and generic names of drugs and an explanation for the mode of action of the drug on each test. Each entry is supported by a bibliographical reference that contains the author's names, and the title of the article and journal. It is possible to search for specific `character strings' (word or words, number, etc) to obtain all the effects of a particular drug, or all drugs that affect a particular test, or even to search for a specific explanation for an effect. The system is undergoing trial in the Department's own computer to permit of automatic correlation of the effects of drugs with laboratory data from patients in one hospital ward. PMID:4648544

Drugs and human performance fact sheets

DOT National Transportation Integrated Search

2004-03-01

A panel of international experts on drug-impaired driving met in Seattle during August 2000 to review developments in the field of drugs and human performance over the last 10 years; to identify the specific effects that both illicit and prescription...

Drugs and human performance fact sheets.

DOT National Transportation Integrated Search

2014-04-01

A panel of international experts on drug-impaired driving met in Seattle during August 2000 to review developments in the field of drugs and human performance over the last 10 years; to identify the specific effects that both illicit and prescription...

Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways

PubMed Central

Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka

2013-01-01

Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery

Effects of antithyroid drugs on radioiodine treatment: systematic review and meta-analysis of randomised controlled trials.

PubMed

Walter, Martin A; Briel, Matthias; Christ-Crain, Mirjam; Bonnema, Steen J; Connell, John; Cooper, David S; Bucher, Heiner C; Müller-Brand, Jan; Müller, Beat

2007-03-10

To determine the effect of adjunctive antithyroid drugs on the risk of treatment failure, hypothyroidism, and adverse events after radioiodine treatment. Meta-analysis. Electronic databases (Cochrane central register of controlled trials, Medline, Embase) searched to August 2006 and contact with experts. Review methods Three reviewers independently assessed trial eligibility and quality. Pooled relative risks for treatment failure and hypothyroidism after radioiodine treatment with and without adjunctive antithyroid drugs were calculated with a random effects model. We identified 14 relevant randomised controlled trials with a total of 1306 participants. Adjunctive antithyroid medication was associated with an increased risk of treatment failure (relative risk 1.28, 95% confidence interval 1.07 to 1.52; P=0.006) and a reduced risk for hypothyroidism (0.68, 0.53 to 0.87; P=0.006) after radioiodine treatment. We found no difference in summary estimates for the different antithyroid drugs or for whether antithyroid drugs were given before or after radioiodine treatment. Antithyroid drugs potentially increase rates of failure and reduce rates of hypothyroidism if they are given in the week before or after radioiodine treatment, respectively.

Use of a single alcohol screening question to identify other drug use.

PubMed

Smith, Peter C; Cheng, Debbie M; Allensworth-Davies, Donald; Winter, Michael R; Saitz, Richard

2014-06-01

People who consume unhealthy amounts of alcohol are more likely to use illicit drugs. We tested the ability of a screening test for unhealthy alcohol use to simultaneously detect drug use. Adult English speaking patients (n=286) were enrolled from a primary care waiting room. They were asked the screening question for unhealthy alcohol use "How many times in the past year have you had X or more drinks in a day?", where X is 5 for men and 4 for women, and a response of one or more is considered positive. A standard diagnostic interview was used to determine current (past year) drug use or a drug use disorder (abuse or dependence). Oral fluid testing was also used to detect recent use of common drugs of abuse. The single screening question for unhealthy alcohol use was 67.6% sensitive (95% confidence interval [CI], 50.2-82.0%) and 64.7% specific (95% CI, 58.4-70.6%) for the detection of a drug use disorder. It was similarly insensitive for drug use detected by oral fluid testing and/or self-report. Although a patient with a drug use disorder has twice the odds of screening positive for unhealthy alcohol use compared to one without a drug use disorder, suggesting patients who screen positive for alcohol should be asked about drug use, a single screening question for unhealthy alcohol use was not sensitive or specific for the detection of other drug use or drug use disorders in a sample of primary care patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Clinically significant drug-drug interactions involving opioid analgesics used for pain treatment in patients with cancer: a systematic review.

PubMed

Kotlinska-Lemieszek, Aleksandra; Klepstad, Pål; Haugen, Dagny Faksvåg

2015-01-01

Opioids are the most frequently used drugs to treat pain in cancer patients. In some patients, however, opioids can cause adverse effects and drug-drug interactions. No advice concerning the combination of opioids and other drugs is given in the current European guidelines. To identify studies that report clinically significant drug-drug interactions involving opioids used for pain treatment in adult cancer patients. Systematic review with searches in Embase, MEDLINE, and Cochrane Central Register of Controlled Trials from the start of the databases (Embase from 1980) through January 2014. In addition, reference lists of relevant full-text papers were hand-searched. Of 901 retrieved papers, 112 were considered as potentially eligible. After full-text reading, 17 were included in the final analysis, together with 15 papers identified through hand-searching of reference lists. All of the 32 included publications were case reports or case series. Clinical manifestations of drug-drug interactions involving opioids were grouped as follows: 1) sedation and respiratory depression, 2) other central nervous system symptoms, 3) impairment of pain control and/or opioid withdrawal, and 4) other symptoms. The most common mechanisms eliciting drug-drug interactions were alteration of opioid metabolism by inhibiting the activity of cytochrome P450 3A4 and pharmacodynamic interactions due to the combined effect on opioid, dopaminergic, cholinergic, and serotonergic activity in the central nervous system. Evidence for drug-drug interactions associated with opioids used for pain treatment in cancer patients is very limited. Still, the cases identified in this systematic review give some important suggestions for clinical practice. Physicians prescribing opioids should recognize the risk of drug-drug interactions and if possible avoid polypharmacy.

Exploring drug-target interaction networks of illicit drugs.

PubMed

Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

2013-01-01

Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network

Exploring drug-target interaction networks of illicit drugs

PubMed Central

2013-01-01

Background Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. Results In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. Conclusions This study presents the first systematic

Drug Intervention Response Predictions with PARADIGM (DIRPP) identifies drug resistant cancer cell lines and pathway mechanisms of resistance.

PubMed

Brubaker, Douglas; Difeo, Analisa; Chen, Yanwen; Pearl, Taylor; Zhai, Kaide; Bebek, Gurkan; Chance, Mark; Barnholtz-Sloan, Jill

2014-01-01

The revolution in sequencing techniques in the past decade has provided an extensive picture of the molecular mechanisms behind complex diseases such as cancer. The Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Project (CGP) have provided an unprecedented opportunity to examine copy number, gene expression, and mutational information for over 1000 cell lines of multiple tumor types alongside IC50 values for over 150 different drugs and drug related compounds. We present a novel pipeline called DIRPP, Drug Intervention Response Predictions with PARADIGM7, which predicts a cell line's response to a drug intervention from molecular data. PARADIGM (Pathway Recognition Algorithm using Data Integration on Genomic Models) is a probabilistic graphical model used to infer patient specific genetic activity by integrating copy number and gene expression data into a factor graph model of a cellular network. We evaluated the performance of DIRPP on endometrial, ovarian, and breast cancer related cell lines from the CCLE and CGP for nine drugs. The pipeline is sensitive enough to predict the response of a cell line with accuracy and precision across datasets as high as 80 and 88% respectively. We then classify drugs by the specific pathway mechanisms governing drug response. This classification allows us to compare drugs by cellular response mechanisms rather than simply by their specific gene targets. This pipeline represents a novel approach for predicting clinical drug response and generating novel candidates for drug repurposing and repositioning.

Recombinant yeast screen for new inhibitors of human acetyl-CoA carboxylase 2 identifies potential drugs to treat obesity

PubMed Central

Marjanovic, Jasmina; Chalupska, Dominika; Patenode, Caroline; Coster, Adam; Arnold, Evan; Ye, Alice; Anesi, George; Lu, Ying; Okun, Ilya; Tkachenko, Sergey; Haselkorn, Robert; Gornicki, Piotr

2010-01-01

Acetyl-CoA carboxylase (ACC) is a key enzyme of fatty acid metabolism with multiple isozymes often expressed in different eukaryotic cellular compartments. ACC-made malonyl-CoA serves as a precursor for fatty acids; it also regulates fatty acid oxidation and feeding behavior in animals. ACC provides an important target for new drugs to treat human diseases. We have developed an inexpensive nonradioactive high-throughput screening system to identify new ACC inhibitors. The screen uses yeast gene-replacement strains depending for growth on cloned human ACC1 and ACC2. In “proof of concept” experiments, growth of such strains was inhibited by compounds known to target human ACCs. The screen is sensitive and robust. Medium-size chemical libraries yielded new specific inhibitors of human ACC2. The target of the best of these inhibitors was confirmed with in vitro enzymatic assays. This compound is a new drug chemotype inhibiting human ACC2 with 2.8 μM IC50 and having no effect on human ACC1 at 100 μM. PMID:20439761

The Effects of Obesity on Drug Metabolism in Children.

PubMed

Oeser, Steffen G; Rougee, Luc R A; Collier, Abby C

2015-01-01

Obesity in children is a significant clinical concern. There are many anecdotes and case studies regarding specific reactions of obese children to medications including therapeutic failure, adverse drug reactions and/or requirements for higher weight-adjusted dosing. There isis, however, a lack of basic and clinical data dissecting the mechanisms of these effects on pharmaceutical efficacy and safety. At present it is unknown how much of the difference in drug disposition in obese children can be attributed to obesity, to maturation or to an interaction between the two. Since a major determinant of drug disposition is hepatic metabolism, here we review how obesity alters hepatic drug disposition in children. Basic as well as clinical data summarizing the current knowledge of biochemical, physiological and clinical effects of pediatric obesity on drug disposition are considered. We conclude that there is a dire need for increased research into the direct effects of obesity on absorption, distribution, metabolism and excretion, as well as changes to pharmacokinetic parameters such as bioavailability and clearance. Increased effort in this area may elucidate the effects of obesity on clinical drug disposition with sufficient detail to provide better dosing guidelines where needed for children.

What is wrong with orphan drug policies?

PubMed

Côté, André; Keating, Bernard

2012-12-01

The effects of orphan drug policies raise serious concerns among payer organizations and lead to often-tragic disappointment for patients who are denied much anticipated drug reimbursements. We evaluate the effects of orphan drug policies on the basis of this concern for real accessibility to drugs. We highlight two unforeseen effects of orphan drug policies: 1) they provide unique business opportunities for manufacturers and 2) drugs approved through these policies are often inaccessible because of their high price. We identify six causes of this emergence of effects. The first four are the direct result of incentives included in orphan drug policies. The fifth cause is the "off-label" use of orphan drugs. These emergent effects have several implications: 1) they raise doubts about the equity of access to drugs, 2) they highlight the limitations of the cohort paradigm in medicine, and c) they force third-party payers to make drugs accessible even when the prices of drugs are believed to be disproportionate to the clinical effects obtained. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Effects of the great recession on drugs consumption in Spain.

PubMed

Martin Bassols, Nicolau; Vall Castelló, Judit

2016-09-01

This paper presents evidence on how the consumption of legal and illegal drugs has changed in response to the Great Recession in Spain. We use a large scale survey from 2005 to 2011 to analyze the association between changes in local economic conditions and drug consumption among individuals aged 15-64. Although Spain was one of the countries hardest hit by the economic downturn, the crisis was unevenly felt across the country. Therefore, we exploit this difference in unemployment rates across provinces to identify the effects of business cycle variations on the consumption of legal and illegal drugs. To the best of our knowledge, this is the first study to find a relation between the deterioration of local economic conditions and a strong increase in the consumption of marihuana and cocaine. We also report a decrease in alcohol consumption but a significant escalation in abusive smoking behavior (smoking every day). We believe that these findings are important not only for the potential negative implications at the individual level but also for the costs to society as a whole. Copyright © 2016 Elsevier B.V. All rights reserved.

Changing effects of direct-to-consumer broadcast drug advertising information sources on prescription drug requests.

PubMed

Lee, Annisa Lai

2009-06-01

This study tracks the changes of the effects of 4 information sources for direct-to-consumer drug advertising on patients' requests for prescription drugs from physicians since the inception of the "Guidance for Industry about Consumer-directed Broadcast Advertisements." The Guidance advises pharmaceuticals to use four information sources for consumers to seek further information to supplement broadcast drug advertisements: small-print information, the Internet, a toll-free number, and health-care providers (nurses, doctors, and pharmacists). Logistic models were created by using survey data collected by the Food and Drug Administration in 1999 and 2002. Results show that throughout the years, health-care providers remain the most used and strongest means associated with patients' direct requests for nonspecific and specific prescription drugs from doctors. The small-print information source gains power and changes from an indirect means associated with patients' discussing drugs with health-care providers to a direct means associated with patients' asking about nonspecific and specific drugs from their doctors. The Internet is not directly related to drug requests, but the effect of its association with patients seeking information from health-care providers grew 11-fold over the course of the study. The toll-free number lost its power altogether for both direct request for a prescription drug and further discussion with health-care providers. Patient demographics will be considered for specific policy implications.

Drug Labeling and Exposure in Neonates

PubMed Central

Laughon, Matthew M.; Avant, Debbie; Tripathi, Nidhi; Hornik, Christoph P.; Cohen-Wolkowiez, Michael; Clark, Reese H.; Smith, P. Brian; Rodriguez, William

2014-01-01

Importance Federal legislation has led to a notable increase in pediatric studies submitted to the Food and Drug Administration (FDA), resulting in new pediatric information in product labeling. However, approximately 50% of drug labels still have insufficient information on safety, efficacy, or dosing in children. Neonatal information in labeling is even scarcer because neonates comprise a vulnerable subpopulation for which end point development is lagging and studies are more challenging. Objective To quantify progress made in neonatal studies and neonatal information in product labeling as result of recent legislation. Design 1. Cohort of neonatal drug studies; and 2. Cohort of infants exposed to these drugs.. Setting 1. Neonatal drug studies: FDA website; 2. National review: infants admitted to a neonatal intensive care unit (NICU) Participants 1) We identified drug studies between 1997 and 2010 that included neonates as a result of pediatric legislation using information available on the FDA website. We determined what studies were published in the medical literature, the legislation responsible for the studies, and the resulting neonatal labeling changes. 2) We then examined the use of these drugs in neonates admitted to 290 NICUs (the Pediatrix Data Warehouse) in the United States from 2005–2010. Exposures Infants exposed to a drug studied in neonates as identified by the FDA website Main outcome measures Number of drug studies with neonates and rate of exposure per 1000 admission among infants admitted to a NICU Results In a review of the FDA databases, we identified 28 drugs studied in neonates and 24 related labeling changes. Forty-one studies encompassed the 28 drugs, and 31 (76%) of these were published. Eleven (46%) of the 24 neonatal labeling changes established safety and effectiveness. In a review of a cohort of 446,335 hospitalized infants, we identified 399 drugs used and 1,525,739 drug exposures in the first 28 postnatal days. Thirteen (46%) of

Attention tasks as skills performance measures of drug effects.

PubMed

Moskowitz, H

1984-01-01

Both empirical epidemiological data on the causes of traffic accidents and conceptual models of skilled human performance stress the central role of perception and cognition. This paper examines the effects of drugs on two major components of cognitive perceptual performance, namely, concentrated attention or vigilance and divided attention. It is demonstrated that these two types of attention tasks are differentially affected by various drugs, so that sometimes one and sometimes another of these tasks is impaired. Various experimental paradigms to investigate these two attention functions are presented. It is demonstrated that attention tasks are frequently highly sensitive to drug effects, suggesting the importance of examining these functions when investigating the effects of drugs on skills performance.

Effect of generic drug competition on the price of prescription drugs in Ontario.

PubMed Central

Lexchin, J

1993-01-01

OBJECTIVE: To analyse the potential effect of generic drug competition on prices in Ontario to assess the costs and benefits associated with Bill C-22 (An Act to amend the Patent Act). DESIGN: Comparison of the cost of the least and most expensive versions of all products sold by more than one manufacturer in 1991. The number of brand-name and generic drug companies marketing each of the products was recorded. RESULTS: Of 1599 products 437 (27.3%) were made by more than one company. Almost half (44.6%) of the 437 were sold by two companies. The more companies that sold a drug the greater the difference in price between the least and most expensive versions. Similarly, as the proportion of generic drug companies in competition increased, the greater the price difference. When competition was between generic drug companies only, the price spread was smaller than when it was between brand-name drug companies only. CONCLUSIONS: Generic drug competition can result in savings to the Ontario Drug Benefit Plan. A more in-depth analysis of the potential savings is necessary to fully assess the costs and benefits associated with Bill C-22. PMID:8439888

Can surveillance systems identify and avert adverse drug events? A prospective evaluation of a commercial application.

PubMed

Jha, Ashish K; Laguette, Julia; Seger, Andrew; Bates, David W

2008-01-01

Computerized monitors can effectively detect and potentially prevent adverse drug events (ADEs). Most monitors have been developed in large academic hospitals and are not readily usable in other settings. We assessed the ability of a commercial program to identify and prevent ADEs in a community hospital. and Measurement We prospectively evaluated the commercial application in a community-based hospital. We examined the frequency and types of alerts produced, how often they were associated with ADEs and potential ADEs, and the potential financial impact of monitoring for ADEs. Among 2,407 patients screened, the application generated 516 high priority alerts. We were able to review 266 alerts at the time they were generated and among these, 30 (11.3%) were considered substantially important to warrant contacting the physician caring for the patient. These 30 alerts were associated with 4 ADEs and 11 potential ADEs. In all 15 cases, the responsible physician was unaware of the event, leading to a change in clinical care in 14 cases. Overall, 23% of high priority alerts were associated with an ADE (95% confidence interval [CI] 12% to 34%) and another 15% were associated with a potential ADE (95% CI 6% to 24%). Active surveillance used approximately 1.5 hours of pharmacist time daily. A commercially available, computer-based ADE detection tool was effective at identifying ADEs. When used as part of an active surveillance program, it can have an impact on preventing or ameliorating ADEs.

Psychiatric side effects of antihypertensive drugs other than reserpine.

PubMed

Paykel, E S; Fleminger, R; Watson, J P

1982-02-01

The psychiatric side effects of the major antihypertensive drugs other than reserpine are reviewed, including centrally acting drugs such as methyldopa and clonidine, peripheral adrenergic drugs such as guanethidine, beta-adrenoceptor blockers such as propranolol, and diuretics. Problems with differential diagnosis and with the interpretation of case reports make assessment of psychiatric side effects difficult. Sedation and sleep disturbances are the most common side effects, occurring with methyldopa, clonidine, and propranolol. Only methyldopa is clearly associated with depression. Other reported effects are toxic confusional states and psychotic reactions. These are rare, however, and no clear patterns of development have been recognized.

Literature-based prediction of novel drug indications considering relationships between entities.

PubMed

Jang, Giup; Lee, Taekeon; Lee, Byung Mun; Yoon, Youngmi

2017-06-27

There have been many attempts to identify and develop new uses for existing drugs, which is known as drug repositioning. Among these efforts, text mining is an effective means of discovering novel knowledge from a large amount of literature data. We identify a gene regulation by a drug and a phenotype based on the biomedical literature. Drugs or phenotypes can activate or inhibit gene regulation. We calculate the therapeutic possibility that a drug acts on a phenotype by means of these two types of regulation. We assume that a drug treats a phenotype if the genes regulated by the phenotype are inversely correlated with the genes regulated by the drug. Based on this hypothesis, we identify drug-phenotype associations with therapeutic possibility. To validate the drug-phenotype associations predicted by our method, we make an enrichment comparison with known drug-phenotype associations. We also identify candidate drugs for drug repositioning from novel associations and thus reveal that our method is a novel approach to drug repositioning.

Nephrotoxic Effects of Common and Emerging Drugs of Abuse

PubMed Central

Pendergraft, William F.; Herlitz, Leal C.; Thornley-Brown, Denyse; Rosner, Mitchell

2014-01-01

The kidneys can be injured in diverse ways by many drugs, both legal and illegal. Novel associations and descriptions of nephrotoxic effects of common and emerging drugs of abuse have appeared over the past several years. Anabolic androgenic steroids, illicitly used by athletes and others for decades to increase muscle mass and decrease body fat, are emerging as podocyte toxins given recent descriptions of severe forms of FSGS in long-term abusers. Synthetic cannabinoids, a new group of compounds with marijuana-like effects, recently became popular as recreational drugs and have been associated with an atypical form of AKI. 3,4-Methylenedioxymethamphetamine, commonly known as ecstasy, is a widely used synthetic recreational drug with mood-enhancing properties and a constellation of toxicities that can result in death. These toxic effects include hyperthermia, hypotonic hyponatremia due to its arginine vasopressin secretagogue–like effects, rhabdomyolysis, and cardiovascular collapse. Cocaine, a serotonin-norepinephrine-dopamine reuptake inhibitor that serves as an illegal stimulant, appetite suppressant, and anesthetic, also causes vasoconstriction and rhabdomyolysis. Recent adulteration of much of the world’s supply of cocaine with levamisole, an antihelminthic agent with attributes similar to but distinct from those of cocaine, appears to have spawned a new type of ANCA-associated systemic vasculitis. This review discusses the nephrotoxic effects of these common and emerging drugs of abuse, of which both community and health care providers should become aware given their widespread abuse. Future investigation into pathogenetic mechanisms associated with these drugs is critical and may provide a window into ways to lessen and even prevent the nephrotoxic effects of these drugs of abuse and perhaps allow a deeper understanding of the nephrotoxicities themselves. PMID:25035273

Factors influencing neonatal therapeutic effect of anti-MRSA drugs.

PubMed

Hayashi, H; Matsuzaki, T; Saito, A; Shimizu, M; Matsumoto, Y

2005-07-01

Factors influencing the neonatal therapeutic effect of anti-MRSA (methicillin-resistant Staphylococcus aureus) drugs are investigated. This study took place over a two-year period from April 1998 to March 2000. We calculated the non-adjusted odds ratio for each influential factor to determine the therapeutic effect of anti-MRSA drugs. Significant factors for therapeutic effect were found to be platelet count, urea nitrogen, creatinine, and CRP, each measured before starting administration of anti-MRSA drugs; whether blood drug concentration was measured; and whether pneumonia or septicemia was present. There was a tendency where a better therapeutic effect was gained when the total protein and albumin values were high. We applied multivariate logistic regression analysis to these factors, and found the following independent significant factors: CRP (odds ratio (OR) = 1.582), albumin (OR = 3.079), Cre (OR -0.213), whether blood drug concentration was measured (OR = 3.767), and presence of pneumonia or septicemia (OR = 0.216). This result suggests that consideration should be given to these five important factors when treating MRSA patients.

The drug discovery portal: a computational platform for identifying drug leads from academia.

PubMed

Clark, Rachel L; Johnston, Blair F; Mackay, Simon P; Breslin, Catherine J; Robertson, Murray N; Sutcliffe, Oliver B; Dufton, Mark J; Harvey, Alan L

2010-05-01

The Drug Discovery Portal (DDP) is a research initiative based at the University of Strathclyde in Glasgow, Scotland. It was initiated in 2007 by a group of researchers with expertise in virtual screening. Academic research groups in the university working in drug discovery programmes estimated there was a historical collection of physical compounds going back 50 years that had never been adequately catalogued. This invaluable resource has been harnessed to form the basis of the DDP library, and has attracted a high-percentage uptake from the Universities and Research Groups internationally. Its unique attributes include the diversity of the academic database, sourced from synthetic, medicinal and phytochemists working an academic laboratories and the ability to link biologists with appropriate chemical expertise through a target-matching virtual screening approach, and has resulted in seven emerging hit development programmes between international contributors.

Significant drug-nutrient interactions.

PubMed

Kirk, J K

1995-04-01

Many nutrients substantially interfere with pharmacotherapeutic goals. The presence of certain nutrients in the gastrointestinal tract affects the bioavailability and disposition of many oral medications. Drug-nutrient interactions can also have positive effects that result in increased drug absorption or reduced gastrointestinal irritation. Knowing the significant drug-nutrient interactions can help the clinician identify the nutrients to avoid with certain medications, as well as the therapeutic agents that should be administered with food. This information can be used to educate patients and optimize pharmacotherapy.

The Effects of Childhood Exposure to Drug Users and Religion on Drug Use in Adolescence and Young Adulthood

ERIC Educational Resources Information Center

Jang, Sung Joon; Johnson, Byron R.

2011-01-01

Previous research finds drug-using peers and religiosity to be key predictors of drug use among youth, but the effects of childhood exposure to drug users and religion on later drug use have been understudied. The authors hypothesize a child's exposure to parental drug use and religious upbringing have a causal influence on drug use in youth…

'Designer drugs'. Recognizing and managing their toxic effects.

PubMed

Sternbach, G L; Varon, J

1992-06-01

"Adam," "Eve," "ecstasy," "China white." Illicit street drugs such as these are called designer drugs because they are designed to elicit certain effects and to bypass legal classification. Unfortunately, use and abuse of such substances can lead to serious medical problems and even death. Drs Sternbach and Varon describe the best-known compounds and discuss clinical characteristics and management of designer drug intoxication.

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.

Nephrotoxic effects of common and emerging drugs of abuse.

PubMed

Pendergraft, William F; Herlitz, Leal C; Thornley-Brown, Denyse; Rosner, Mitchell; Niles, John L

2014-11-07

The kidneys can be injured in diverse ways by many drugs, both legal and illegal. Novel associations and descriptions of nephrotoxic effects of common and emerging drugs of abuse have appeared over the past several years. Anabolic androgenic steroids, illicitly used by athletes and others for decades to increase muscle mass and decrease body fat, are emerging as podocyte toxins given recent descriptions of severe forms of FSGS in long-term abusers. Synthetic cannabinoids, a new group of compounds with marijuana-like effects, recently became popular as recreational drugs and have been associated with an atypical form of AKI. 3,4-Methylenedioxymethamphetamine, commonly known as ecstasy, is a widely used synthetic recreational drug with mood-enhancing properties and a constellation of toxicities that can result in death. These toxic effects include hyperthermia, hypotonic hyponatremia due to its arginine vasopressin secretagogue-like effects, rhabdomyolysis, and cardiovascular collapse. Cocaine, a serotonin-norepinephrine-dopamine reuptake inhibitor that serves as an illegal stimulant, appetite suppressant, and anesthetic, also causes vasoconstriction and rhabdomyolysis. Recent adulteration of much of the world's supply of cocaine with levamisole, an antihelminthic agent with attributes similar to but distinct from those of cocaine, appears to have spawned a new type of ANCA-associated systemic vasculitis. This review discusses the nephrotoxic effects of these common and emerging drugs of abuse, of which both community and health care providers should become aware given their widespread abuse. Future investigation into pathogenetic mechanisms associated with these drugs is critical and may provide a window into ways to lessen and even prevent the nephrotoxic effects of these drugs of abuse and perhaps allow a deeper understanding of the nephrotoxicities themselves. Copyright © 2014 by the American Society of Nephrology.

Brain serotonin, psychoactive drugs, and effects on reproduction.

PubMed

Ayala, María Elena

2009-12-01

Serotonin, a biogenic amine, is present in significant amounts in many structures of the CNS. It is involved in regulation of a wide variety of physiological functions, such as sensory and motor functions, memory, mood, and secretion of hormones including reproductive hormones. It has also been implicated in the etiology of a range of psychiatric disorders such as anxiety, depression, and eating disorders, along with other conditions such as obesity and migraine. While some drugs that affect serotonin, such as fenfluramine and fluoxetine, have been successfully used in treatment of a range of psychiatric diseases, others, such as the amphetamine analogues MDMA and METH, are potent psychostimulant drugs of abuse. Alterations in serotonergic neurons caused by many of these drugs are well characterized; however, little is known about the reproductive consequences of such alterations. This review evaluates the effects of drugs such as MDMA, pCA, fenfluramine, and fluoxetine on serotonergic transmission in the brain, examines the relationships of these drug effects with the neuroendocrine mechanisms modulating reproductive events such as gonadotropin secretion, ovulation, spermatogenesis, and sexual behavior in animal models, and discusses possible reproductive implications of these drugs in humans.

Bone effects of biologic drugs in rheumatoid arthritis.

PubMed

Corrado, Addolorata; Neve, Anna; Maruotti, Nicola; Cantatore, Francesco Paolo

2013-01-01

Biologic agents used in the treatment of rheumatoid arthritis (RA) are able to reduce both disease activity and radiographic progression of joint disease. These drugs are directed against several proinflammatory cytokines (TNF α , IL-6, and IL-1) which are involved both in the pathogenesis of chronic inflammation and progression of joint structural damage and in systemic and local bone loss typically observed in RA. However, the role of biologic drugs in preventing bone loss in clinical practice has not yet clearly assessed. Many clinical studies showed a trend to a positive effect of biologic agents in preventing systemic bone loss observed in RA. Although the suppression of inflammation is the main goal in the treatment of RA and the anti-inflammatory effects of biologic drugs exert a positive effect on bone metabolism, the exact relationship between the prevention of bone loss and control of inflammation has not been clearly established, and if the available biologic drugs against TNF α , IL-1, and IL-6 can exert their effect on systemic and local bone loss also through a direct mechanism on bone cell metabolism is still to be clearly defined.

Brief interventions for illicit drug use among peripartum women.

PubMed

Farr, Sherry L; Hutchings, Yalonda L; Ondersma, Steven J; Creanga, Andreea A

2014-10-01

We review the evidence and identify limitations of the current literature on the effectiveness of brief interventions (≤5 intervention sessions) on illicit drug use, treatment enrollment/retention, and pregnancy outcomes among pregnant and postpartum women; and consider this evidence in the context of the broader brief intervention literature. Among 4 published studies identified via systematic review and meeting a priori quality criteria, we found limited, yet promising evidence of the benefit of brief interventions to reduce illicit drug use among postpartum women. Two of the 4 randomized controlled trials tested similar computer-delivered single-session interventions; both demonstrate effects on postpartum drug use. Neither of the 2 randomized controlled trials that assessed treatment use found differences between intervention and control groups. Studies examining brief interventions for smoking and alcohol use among pregnant women, and for illicit drug use in the general adult population, have shown small but statistically significant results of the effectiveness of such interventions. Larger studies, those that examine the effect of assessment alone on illicit drug use, and those that use technology-delivered brief interventions are needed to assess the effectiveness of brief interventions for drug use in the peripartum period. Published by Elsevier Inc.

High-Throughput Flow Cytometry Identifies Small-Molecule Inhibitors for Drug Repurposing in T-ALL.

PubMed

Perez, Dominique R; Nickl, Christian K; Waller, Anna; Delgado-Martin, Cristina; Woods, Travis; Sharma, Nitesh D; Hermiston, Michelle L; Loh, Mignon L; Hunger, Stephen P; Winter, Stuart S; Chigaev, Alexandre; Edwards, Bruce; Sklar, Larry A; Matlawska-Wasowska, Ksenia

2018-05-01

Kinase inhibitors have dramatically increased patient survival in a multitude of cancers, including hematological malignancies. However, kinase inhibitors have not yet been integrated into current clinical trials for patients with T-cell-lineage acute lymphoblastic leukemia (T-ALL). In this study, we used a high-throughput flow cytometry (HTFC) approach to test a collection of small-molecule inhibitors, including 26 FDA-approved tyrosine kinase inhibitors in a panel of T-ALL cell lines and patient-derived xenografts. Because hypoxia is known to cause resistance to chemotherapy, we developed a synthetic niche that mimics the low oxygen levels found in leukemic bone marrow to evaluate the effects of hypoxia on the tested inhibitors. Drug sensitivity screening was performed using the Agilent BioCel automated liquid handling system integrated with the HyperCyt HT flow cytometry platform, and the uptake of propidium iodide was used as an indication of cell viability. The HTFC dose-response testing identified several compounds that were efficacious in both normal and hypoxic conditions. This study shows that some clinically approved kinase inhibitors target T-ALL in the hypoxic niche of the bone marrow.

The effects of drugs on human models of emotional processing: an account of antidepressant drug treatment.

PubMed

Pringle, Abbie; Harmer, Catherine J

2015-12-01

Human models of emotional processing suggest that the direct effect of successful antidepressant drug treatment may be to modify biases in the processing of emotional information. Negative biases in emotional processing are documented in depression, and single or short-term dosing with conventional antidepressant drugs reverses these biases in depressed patients prior to any subjective change in mood. Antidepressant drug treatments also modulate emotional processing in healthy volunteers, which allows the consideration of the psychological effects of these drugs without the confound of changes in mood. As such, human models of emotional processing may prove to be useful for testing the efficacy of novel treatments and for matching treatments to individual patients or subgroups of patients.

Evaluation of accuracy of IHI Trigger Tool in identifying adverse drug events: a prospective observational study.

PubMed

das Dores Graciano Silva, Maria; Martins, Maria Auxiliadora Parreiras; de Gouvêa Viana, Luciana; Passaglia, Luiz Guilherme; de Menezes, Renata Rezende; de Queiroz Oliveira, João Antonio; da Silva, Jose Luiz Padilha; Ribeiro, Antonio Luiz Pinho

2018-06-06

Adverse drug events (ADEs) can seriously compromise the safety and quality of care provided to hospitalized patients, requiring the adoption of accurate methods to monitor them. We sought to prospectively evaluate the accuracy of the triggers proposed by the Institute for Healthcare Improvement (IHI) for identifying ADEs. A prospective study was conducted in a public university hospital, in 2015, with patients ≥18 years. Triggers proposed by IHI and clinical alterations suspected to be ADEs were searched daily. The number of days in which the patient was hospitalized was considered as unit of measure to evaluate the accuracy of each trigger. Three hundred patients were included in this study. Mean age was 56.3 years (standard deviation (SD) 16.0), and 154 (51.3%) were female. The frequency of patients with ADEs was 24.7% and with at least one trigger was 53.3%. From those patients who had at least one trigger, the most frequent triggers were antiemetics (57.5%) and "abrupt medication stop" (31.8%). Triggers' sensitivity ranged from 0.3 to11.8 % and the positive predictive value ranged from 1.2 to 27.3%. Specificity and negative predictive value were greater than 86%. Most patients identified by the presence of triggers did not have ADEs (64.4%). No triggers were identified in 40 (38.5%) ADEs. IHI Trigger Tool did not show good accuracy in detecting ADEs in this prospective study. The adoption of combined strategies could enhance effectiveness in identifying patient safety flaws. Further discussion might contribute to improve trigger usefulness in clinical practice. This article is protected by copyright. All rights reserved.

Effects of antithyroid drugs on radioiodine treatment: systematic review and meta-analysis of randomised controlled trials

PubMed Central

Briel, Matthias; Christ-Crain, Mirjam; Bonnema, Steen J; Connell, John; Cooper, David S; Bucher, Heiner C; Müller-Brand, Jan; Müller, Beat

2007-01-01

Objective To determine the effect of adjunctive antithyroid drugs on the risk of treatment failure, hypothyroidism, and adverse events after radioiodine treatment. Design Meta-analysis. Data sources Electronic databases (Cochrane central register of controlled trials, Medline, Embase) searched to August 2006 and contact with experts. Review methods Three reviewers independently assessed trial eligibility and quality. Pooled relative risks for treatment failure and hypothyroidism after radioiodine treatment with and without adjunctive antithyroid drugs were calculated with a random effects model. Results We identified 14 relevant randomised controlled trials with a total of 1306 participants. Adjunctive antithyroid medication was associated with an increased risk of treatment failure (relative risk 1.28, 95% confidence interval 1.07 to 1.52; P=0.006) and a reduced risk for hypothyroidism (0.68, 0.53 to 0.87; P=0.006) after radioiodine treatment. We found no difference in summary estimates for the different antithyroid drugs or for whether antithyroid drugs were given before or after radioiodine treatment. Conclusions Antithyroid drugs potentially increase rates of failure and reduce rates of hypothyroidism if they are given in the week before or after radioiodine treatment, respectively. PMID:17309884

Are mass-media campaigns effective in preventing drug use? A Cochrane systematic review and meta-analysis

PubMed Central

Allara, Elias; Ferri, Marica; Bo, Alessandra; Gasparrini, Antonio; Faggiano, Fabrizio

2015-01-01

Objective To determine whether there is evidence that mass-media campaigns can be effective in reducing illicit drug consumption and the intent to consume. Design Systematic review of randomised and non-randomised studies. Methods We searched four electronic databases (MEDLINE, EMBASE, ProQuest Dissertations & Theses A&I and CENTRAL) and further explored seven additional resources to obtain both published and unpublished materials. We appraised the quality of included studies using standardised tools. We carried out meta-analyses of randomised controlled trials and a pooled analysis of interrupted time-series and controlled before-and-after studies. Results We identified 19 studies comprising 184 811 participants. Pooled analyses and narrative synthesis provided mixed evidence of effectiveness. Eight interventions evaluated with randomised controlled trials leaned towards no evidence of an effect, both on drug use (standardised mean difference (SMD) −0.02; 95% CI −0.15 to 0.12) and the intention to use drugs (SMD −0.07; 95% CI −0.19 to 0.04). Four campaigns provided some evidence of beneficial effects in preventing drug use and two interventions provided evidence of iatrogenic effects. Conclusions Studies were considerably heterogeneous in type of mass-media intervention, outcome measures, underlying theory, comparison groups and design. Such factors can contribute to explaining the observed variability in results. Owing to the risk of adverse effects, caution is needed in disseminating mass-media campaigns tackling drug use. Large studies conducted with appropriate methodology are warranted to consolidate the evidence base. PMID:26338836

Impact of pharmaceutical cocrystals: the effects on drug pharmacokinetics.

PubMed

Shan, Ning; Perry, Miranda L; Weyna, David R; Zaworotko, Michael J

2014-09-01

Pharmaceutical cocrystallization has emerged in the past decade as a new strategy to enhance the clinical performance of orally administered drugs. A pharmaceutical cocrystal is a multi-component crystalline material in which the active pharmaceutical ingredient is in a stoichiometric ratio with a second compound that is generally a solid under ambient conditions. The resulting cocrystal exhibits different solid-state thermodynamics, leading to changes in physicochemical properties that offer the potential to significantly modify drug pharmacokinetics. The impact of cocrystallization upon drug pharmacokinetics has not yet been well delineated. Herein, we compile previously published data to address two salient questions: what effect does cocrystallization impart upon physicochemical properties of a drug substance and to what degree can those effects impact its pharmacokinetics. Cocrystals can impact various aspects of drug pharmacokinetics, including, but not limited to, drug absorption. The diversity of solid forms offered through cocrystallization can facilitate drastic changes in solubility and pharmacokinetics. Therefore, it is unsurprising that cocrystal screening is now a routine step in early-stage drug development. With the increasing recognition of pharmaceutical cocrystals from clinical, regulatory and legal perspectives, the systematic commercialization of cocrystal containing drug products is just a matter of time.

75 FR 10413 - New Animal Drug Applications; Confirmation of Effective Date

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-08

.... FDA-2009-N-0436] New Animal Drug Applications; Confirmation of Effective Date AGENCY: Food and Drug Administration, HHS. ACTION: Direct final rule; confirmation of effective date. SUMMARY: The Food and Drug Administration (FDA) is confirming the effective date of March 8, 2010, for the final rule that appeared in the...

Effect of PEGylation on drug entry into lipid bilayer.

PubMed

Rissanen, Sami; Kumorek, Marta; Martinez-Seara, Hector; Li, Yen-Chin; Jamróz, Dorota; Bunker, Alex; Nowakowska, Maria; Vattulainen, Ilpo; Kepczynski, Mariusz; Róg, Tomasz

2014-01-09

Poly(ethylene glycol) (PEG) is a polymer commonly used for functionalization of drug molecules to increase their bloodstream lifetime, hence efficacy. However, the interactions between the PEGylated drugs and biomembranes are not clearly understood. In this study, we employed atomic-scale molecular dynamics (MD) simulations to consider the behavior of two drug molecules functionalized with PEG (tetraphenylporphyrin used in cancer phototherapy and biochanin A belonging to the isoflavone family) in the presence of a lipid bilayer. The commonly held view is that functionalization of a drug molecule with a polymer acts as an entropic barrier, inhibiting the penetration of the drug molecule through a cell membrane. Our results indicate that in the bloodstream there is an additional source of electrostatic repulsive interactions between the PEGylated drugs and the lipid bilayer. Both the PEG chain and lipids can bind Na(+) ions, thus effectively becoming positively charged molecules. This leads to an extra repulsive effect resulting from the presence of salt in the bloodstream. Thus, our study sheds further light on the role of PEG in drug delivery.

21 CFR 350.60 - Guidelines for effectiveness testing of antiperspirant drug products.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 5 2011-04-01 2011-04-01 false Guidelines for effectiveness testing of antiperspirant drug products. 350.60 Section 350.60 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... Drug Administration is providing guidelines that manufacturers may use in testing for effectiveness...

21 CFR 350.60 - Guidelines for effectiveness testing of antiperspirant drug products.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 5 2014-04-01 2014-04-01 false Guidelines for effectiveness testing of antiperspirant drug products. 350.60 Section 350.60 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... Drug Administration is providing guidelines that manufacturers may use in testing for effectiveness...

21 CFR 350.60 - Guidelines for effectiveness testing of antiperspirant drug products.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 5 2012-04-01 2012-04-01 false Guidelines for effectiveness testing of antiperspirant drug products. 350.60 Section 350.60 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... Drug Administration is providing guidelines that manufacturers may use in testing for effectiveness...

21 CFR 350.60 - Guidelines for effectiveness testing of antiperspirant drug products.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 5 2013-04-01 2013-04-01 false Guidelines for effectiveness testing of antiperspirant drug products. 350.60 Section 350.60 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... Drug Administration is providing guidelines that manufacturers may use in testing for effectiveness...

Antipsychotic Drug Side Effects for Persons with Intellectual Disability

ERIC Educational Resources Information Center

Matson, Johnny L.; Mahan, Sara

2010-01-01

Antipsychotic drugs are the most frequently prescribed of the psychotropic drugs among the intellectually disabled (ID) population. Given their widespread use, efforts to systematically assess and report side effects are warranted. Specific scaling methods such as the "Matson Evaluation of Side Effects" ("MEDS"), the "Abnormal Inventory Movement…

HIV and the criminalisation of drug use among people who inject drugs: a systematic review.

PubMed

DeBeck, Kora; Cheng, Tessa; Montaner, Julio S; Beyrer, Chris; Elliott, Richard; Sherman, Susan; Wood, Evan; Baral, Stefan

2017-08-01

Mounting evidence suggests that laws and policies prohibiting illegal drug use could have a central role in shaping health outcomes among people who inject drugs (PWID). To date, no systematic review has characterised the influence of laws and legal frameworks prohibiting drug use on HIV prevention and treatment. Consistent with PRISMA guidelines, we did a systematic review of peer-reviewed scientific evidence describing the association between criminalisation of drug use and HIV prevention and treatment-related outcomes among PWID. We searched MEDLINE, Embase, SCOPUS, PsycINFO, Sociological Abstracts, CINAHL, Web of Science, and other sources. To be included in our review, a study had to meet the following eligibility criteria: be published in a peer-reviewed journal or presented as a peer-reviewed abstract at a scientific conference; examine, through any study design, the association between an a-priori set of indicators related to the criminalisation of drugs and HIV prevention or treatment among PWID; provide sufficient details on the methods followed to allow critical assessment of quality; be published or presented between Jan 1, 2006, and Dec 31, 2014; and be published in the English language. We identified 106 eligible studies comprising 29 longitudinal, 49 cross-sectional, 22 qualitative, two mixed methods, four mathematical modelling studies, and no randomised controlled trials. 120 criminalisation indicators were identified (range 1-3 per study) and 150 HIV indicators were identified (1-5 per study). The most common criminalisation indicators were incarceration (n=38) and street-level policing (n=39), while the most frequent HIV prevention and treatment indicators were syringe sharing (n=35) and prevalence of HIV infection among PWID (n=28). Among the 106 studies included in this review, 85 (80%) suggested that drug criminalisation has a negative effect on HIV prevention and treatment, 10 (9%) suggested no association, five (5%) suggested a beneficial

Herb-drug, food-drug, nutrient-drug, and drug-drug interactions: mechanisms involved and their medical implications.

PubMed

Sørensen, Janina Maria

2002-06-01

Adverse drug reactions (ADRs) and iatrogenic diseases have been identified as significant factors responsible for patient morbidity and mortality. Significant studies on drug metabolism in humans have been published during the last few years, offering a deeper comprehension of the mechanisms underlying adverse drug reactions and interactions. More understanding of these mechanisms, and of recent advances in laboratory technology, can help to evaluate potential drug interactions when drugs are prescribed concurrently. Increasing knowledge of interindividual variation in drug breakdown capacity and recent findings concerning the influence of environment, diet, nutrients, and herbal products can be used to reduce ADRs and iatrogenic diseases. Reviewed data suggest that drug treatment should be increasingly custom tailored to suit the individual patient and that appropriately co-prescribed diet and herbal remedies, could increase drug efficacy and lessen drug toxicity. This review focuses mainly on recently published research material. The cytochrome p450 enzymes, their role in metabolism, and their mechanisms of action are reviewed, and their role in drug-drug interactions are discussed. Drug-food and drug-herb interactions have garnered attention. Interdisciplinary communication among medical herbalists, medical doctors, and dietetic experts needs to be improved and encouraged. Internet resources for obtaining current information regarding drug-drug, drug-herb, and drug-nutrient interactions are provided.

Systemic analysis of genome-wide expression profiles identified potential therapeutic targets of demethylation drugs for glioblastoma.

PubMed

Ning, Tongbo; Cui, Hao; Sun, Feng; Zou, Jidian

2017-09-05

Glioblastoma represents one of the most aggressive malignant brain tumors with high morbidity and motility. Demethylation drugs have been developed for its treatment with little efficacy has been observed. The purpose of this study was to screen therapeutic targets of demethylation drugs or bioactive molecules for glioblastoma through systemic bioinformatics analysis. We firstly downloaded genome-wide expression profiles from the Gene Expression Omnibus (GEO) and conducted the primary analysis through R software, mainly including preprocessing of raw microarray data, transformation between probe ID and gene symbol and identification of differential expression genes (DEGs). Secondly, functional enrichment analysis was conducted via the Database for Annotation, Visualization and Integrated Discovery (DAVID) to explore biological processes involved in the development of glioblastoma. Thirdly, we constructed protein-protein interaction (PPI) network of interested genes and conducted cross analysis for multi datasets to obtain potential therapeutic targets for glioblastoma. Finally, we further confirmed the therapeutic targets through real-time RT-PCR. As a result, biological processes that related to cancer development, amino metabolism, immune response and etc. were found to be significantly enriched in genes that differential expression in glioblastoma and regulated by 5'aza-dC. Besides, network and cross analysis identified ACAT2, UFC1 and CYB5R1 as novel therapeutic targets of demethylation drugs which also confirmed by real time RT-PCR. In conclusions, our study identified several biological processes and genes that involved in the development of glioblastoma and regulated by 5'aza-dC, which would be helpful for the treatment of glioblastoma. Copyright © 2017 Elsevier B.V. All rights reserved.

[Do pediatricians identify adverse drug reactions even when they do not report them?

PubMed

Morales-Ríos, Olga; Jasso-Gutiérrez, Luis; Garduño-Espinosa, Juan; Olivar-López, Víctor; Muñoz-Hernández, Onofre

Spontaneous notification depends on the ability of pediatricians to identify adverse drug reactions (ADRs) along with their habit of reporting these incidents. During the years 2008 and 2009, the frequency of reports of ADRs to the Electronic Program of Pharmacovigilance (SISFAR) in the Hospital Infantil of Mexico Federico Gomez (HIMFG) was low (0.44% and 0.20%, respectively). Because of the above, the ability of pediatricians from the Emergency Department (ED) to identify ADRs using the clinical chart review was evaluated in 2010 in this study. A descriptive, observational, cross-sectional retrospective study was conducted in the ED from March 1 to August 31. ADRs were classified and quantified as "ADRs identified by pediatricians" when there was evidence in the clinical chart that pediatricians associated a clinical sign, symptom and laboratory value with an ADR. The numbers of notifications reported in SISFAR were quantified. Descriptive analysis was done using SPSS v.18. Considering patients who were admitted to the ED, the frequency of ADRs was 21.8%. The frequency of ADRs identified by physicians in clinical charts was 86%. The pharmacist detected 14% of ADRs. The frequency of ADRs reported by physicians was 6.1%. Although identification of ADRs in the clinical charts by pediatricians was high, it is possible that some ADRs were undetected. Because underreporting was very high, it is necessary to take actions to improve the reporting process. Copyright © 2015. Publicado por Masson Doyma México S.A.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

PubMed

Perez-Lopez, Áron R; Szalay, Kristóf Z; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-11

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

NASA Astrophysics Data System (ADS)

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

PubMed Central

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-01-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates. PMID:25960144

Pharmacogenetics of drug-metabolizing enzymes: implications for a safer and more effective drug therapy

PubMed Central

Ingelman-Sundberg, Magnus; Rodriguez-Antona, Cristina

2005-01-01

The majority of phase I- and phase II-dependent drug metabolism is carried out by polymorphic enzymes which can cause abolished, quantitatively or qualitatively decreased or enhanced drug metabolism. Several examples exist where subjects carrying certain alleles do not benefit from drug therapy due to ultrarapid metabolism caused by multiple genes or by induction of gene expression or, alternatively, suffer from adverse effects of the drug treatment due to the presence of defective alleles. It is likely that future predictive genotyping for such enzymes might benefit 15–25% of drug treatments, and thereby allow prevention of adverse drug reactions and causalities, and thus improve the health of a significant fraction of the patients. However, it will take time before this will be a reality within the clinic. We describe some important aspects in the field with emphasis on cytochrome P450 and discuss also polymorphic aspects of foetal expression of CYP3A5 and CYP3A7. PMID:16096104

Calcium channel blockers: spectrum of side effects and drug interactions.

PubMed

Hedner, T

1986-01-01

Calcium antagonists are a chemically heterogenous group of agents with potent cardiovascular effects which are beneficial in the treatment of angina pectoris, arterial hypertension and cardiac arrhythmias. The main side effects for the group are dose-dependent and the result of the main action or actions of the calcium antagonists, i.e. vasodilatation, negative inotropic effects and antiarrhythmic effects. Pronounced hypotension is reported for the main calcium antagonist drugs; verapamil, diltiazem and nifedipine. While conduction disturbances and bradycardia are seen more often after verapamil and diltiazem, tachycardia, headache and flush are more frequent after nifedipine. Constipation is relatively frequent after verapamil while nifedipine is reported to induce diarrhea in som patients. Idiosyncratic side effects are rare but have been reported from the skin, mouth, musculoskeletal system, the liver and the central nervous system. These side effects include urticarial rashes, gingival hyperplasia, arthralgia, hepathotoxicity and transistory mental confusion or akathisia. Verapamil, diltiazem and possibly also nifedipine have been reported to increase serum digoxin concentrations but the clinical relevance of these drug interactions are not clear. Furthermore, verapamil and diltiazem may potentiate the effects of beta-adrenergic blocking drugs and verapamil may also potentiate the effects of neuromuscular blocking drugs. It is concluded that side effects after calcium antagonist drugs are mostly trivial and transient although they may sometimes be relatively common. Clinically relevant drug interactions are few. Judged from the point of efficacy and safety, calcium antagonists will have a major place in the future pharmacotherapy of several cardiovascular disorders.

Preventing, Identifying, and Treating Prescription Drug Misuse Among Active-Duty Service Members

PubMed Central

Pacula, Rosalie Liccardo; Hunter, Sarah B.; Ober, Allison J.; Osilla, Karen Chan; Vardavas, Raffaele; Blanchard, Janice C.; DeVries, David; Drabo, Emmanuel F.; Leuschner, Kristin J.; Stewart, Warren; Walters, Jennifer

2017-01-01

Abstract Prescription drug misuse (PDM) is of critical concern for the military because of its potential impact on military readiness, the health and well-being of military personnel, and associated health care costs. The purpose of this study is to summarize insights gleaned from a series of activities that the RAND Corporation undertook for the Deputy Assistant Secretary of Defense for Readiness to address this important health and military readiness issue. The authors completed a review of U.S. Department of Defense policies and a comprehensive literature review of clinical guidelines and the empirical literature on the prevention and treatment of PDM and conducted individual face-to-face interviews with 66 health and behavioral health care providers at nine medical treatment facilities across three regions within the contiguous United States to identify best practices in the prevention, identification, and treatment of PDM and the extent to which those practices are known and followed. The study also presents the framework of an analytic tool that, once informed by data available to the military but not available to the authors, can assist the military in predicting future trends in PDM based on current demographics of active-duty service members and rates of injury and prescribing of prescription drugs. The findings from this work led the authors to formulate a set of key insights that they believe might improve the rapid identification and treatment of service members dealing with PDM, thereby improving future force readiness. PMID:29057158

A unified frame of predicting side effects of drugs by using linear neighborhood similarity.

PubMed

Zhang, Wen; Yue, Xiang; Liu, Feng; Chen, Yanlin; Tu, Shikui; Zhang, Xining

2017-12-14

Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame.

Molecularly targeted drug combinations demonstrate selective effectiveness for myeloid- and lymphoid-derived hematologic malignancies

PubMed Central

Eide, Christopher A.; Kaempf, Andy; Khanna, Vishesh; Savage, Samantha L.; Rofelty, Angela; English, Isabel; Ho, Hibery; Pandya, Ravi; Bolosky, William J.; Poon, Hoifung; Deininger, Michael W.; Collins, Robert; Swords, Ronan T.; Watts, Justin; Pollyea, Daniel A.; Medeiros, Bruno C.; Traer, Elie; Tognon, Cristina E.; Mori, Motomi; Druker, Brian J.; Tyner, Jeffrey W.

2017-01-01

Translating the genetic and epigenetic heterogeneity underlying human cancers into therapeutic strategies is an ongoing challenge. Large-scale sequencing efforts have uncovered a spectrum of mutations in many hematologic malignancies, including acute myeloid leukemia (AML), suggesting that combinations of agents will be required to treat these diseases effectively. Combinatorial approaches will also be critical for combating the emergence of genetically heterogeneous subclones, rescue signals in the microenvironment, and tumor-intrinsic feedback pathways that all contribute to disease relapse. To identify novel and effective drug combinations, we performed ex vivo sensitivity profiling of 122 primary patient samples from a variety of hematologic malignancies against a panel of 48 drug combinations. The combinations were designed as drug pairs that target nonoverlapping biological pathways and comprise drugs from different classes, preferably with Food and Drug Administration approval. A combination ratio (CR) was derived for each drug pair, and CRs were evaluated with respect to diagnostic categories as well as against genetic, cytogenetic, and cellular phenotypes of specimens from the two largest disease categories: AML and chronic lymphocytic leukemia (CLL). Nearly all tested combinations involving a BCL2 inhibitor showed additional benefit in patients with myeloid malignancies, whereas select combinations involving PI3K, CSF1R, or bromodomain inhibitors showed preferential benefit in lymphoid malignancies. Expanded analyses of patients with AML and CLL revealed specific patterns of ex vivo drug combination efficacy that were associated with select genetic, cytogenetic, and phenotypic disease subsets, warranting further evaluation. These findings highlight the heuristic value of an integrated functional genomic approach to the identification of novel treatment strategies for hematologic malignancies. PMID:28784769

Prime-, Stress- and Cue-Induced Reinstatement of Extinguished Drug-Reinforced Responding in Rats: Cocaine as the Prototypical Drug of Abuse

PubMed Central

Beardsley, Patrick M.; Shelton, Keith L.

2012-01-01

This unit describes the testing of rats in prime-, footshock- and cue-induced reinstatement procedures. Evaluating rats in these procedures enables the assessment of treatments on behavior thought to model drug relapse precipitated by re-contact with an abused drug (prime-induced), induced by stress (footshock-induced), or by stimuli previously associated with drug administration (cue-induced). For instance, levels of reinstatement under the effects of test compound administration could be compared to levels under vehicle administration to help identify potential treatments for drug relapse, or reinstatement levels of different rat strains could be compared to identify potential genetic determinants of perseverative drug-seeking behavior. Cocaine is used as a prototypical drug of abuse, and relapse to its use serves as the model in this unit, but other self-administered drugs could readily be substituted with little modification to the procedures. PMID:23093352

Effect of safety issues with HIV drugs on the approval process of other drugs in the same class: an analysis of European Public Assessment Reports.

PubMed

Arnardottir, Arna H; Haaijer-Ruskamp, Flora M; Straus, Sabine M J; de Graeff, Pieter A; Mol, Peter G M

2011-11-01

Knowledge on the safety of new medicines is limited at the time of market entry. Nearly half of all drugs used to treat HIV registered in the EU required ≥1 Direct Healthcare Professional Communication (DHPC) in the past 10 years for safety issues identified post-approval. The aim was to evaluate the extent to which regulators and industry have addressed the risk of safety issues for HIV drugs based on prior experience with other drugs in the same class and whether doing so impacts development time of these drugs. HIV drugs receiving ≥1 DHPC in the Netherlands between January 1999 and December 2008 were identified. Each drug with a DHPC ('index' drug) was paired with subsequently approved HIV drug(s) in the same class (Anatomical Therapeutic Chemical [ATC] 4th level) ['follow-on' drugs]. Characteristics of safety issues were extracted from the DHPCs of the 'index' drugs. European Public Assessment Reports (EPARs) were reviewed regarding whether the safety issues had been considered during development and approval. Consideration of previously identified safety issues in 'follow-on' drug applications was assessed regarding attention paid to adverse drug reaction (ADR) symptoms in pre-marketing studies, Summary of Product Characteristics (SmPC) and postmarketing commitments, and whether size of the safety population was in accordance with Regulatory guidelines. 'Index' drugs were also paired with drugs in the same class already on the market ('older' drugs). For 'older' drugs, we identified whether the safety issue led to appropriate changes in the current SmPC (January 2011) compared with the SmPC at the time of marketing authorization. Clinical development time was assessed using time from first patent application to market authorization as proxy, and comparison was made between 'index' and 'follow-on' drugs. For 9 (43%) of the 21 centrally authorized HIV drugs, 11 serious safety issues that required a DHPC were identified. Two drugs were excluded from our

Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

PubMed

Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

2015-12-01

Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Effectiveness of a Clinical Skills Workshop for drug-dosage calculation in a nursing program.

PubMed

Grugnetti, Anna Maria; Bagnasco, Annamaria; Rosa, Francesca; Sasso, Loredana

2014-04-01

Mathematical and calculation skills are widely acknowledged as being key nursing competences if patients are to receive care that is both effective and safe. Indeed, weaknesses in mathematical competence may lead to the administration of miscalculated drug doses, which in turn may harm or endanger patients' lives. However, little attention has been given to identifying appropriate teaching and learning strategies that will effectively facilitate the development of these skills in nurses. One such approach may be simulation. To evaluate the effectiveness of a Clinical Skills Workshop on drug administration that focused on improving the drug-dosage calculation skills of second-year nursing students, with a view to promoting safety in drugs administration. A descriptive pre-post test design. Educational. Simulation center. The sample population included 77 nursing students from a Northern Italian University who attended a 30-hour Clinical Skills Workshop over a period of two weeks. The workshop covered integrated teaching strategies and innovative drug-calculation methodologies which have been described to improve psychomotor skills and build cognitive abilities through a greater understanding of mathematics linked to clinical practice. Study results showed a significant improvement between the pre- and the post-test phases, after the intervention. Pre-test scores ranged between 0 and 25 out of a maximum of 30 points, with a mean score of 15.96 (SD 4.85), and a median score of 17. Post-test scores ranged between 15 and 30 out of 30, with a mean score of 25.2 (SD 3.63) and a median score of 26 (p<0.001). Our study shows that Clinical Skills Workshops may be tailored to include teaching techniques that encourage the development of drug-dosage calculation skills, and that training strategies implemented during a Clinical skills Workshop can enhance students' comprehension of mathematical calculations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Expression of Genes for Drug Transporters in the Human Female Genital Tract and Modulatory Effect of Antiretroviral Drugs.

PubMed

Hijazi, Karolin; Cuppone, Anna M; Smith, Kieron; Stincarelli, Maria A; Ekeruche-Makinde, Julia; De Falco, Giulia; Hold, Georgina L; Shattock, Robin; Kelly, Charles G; Pozzi, Gianni; Iannelli, Francesco

2015-01-01

Anti-retroviral (ARV) -based microbicides are one of the strategies pursued to prevent HIV-1 transmission. Delivery of ARV drugs to subepithelial CD4+ T cells at concentrations for protection is likely determined by drug transporters expressed in the cervicovaginal epithelium. To define the role of drug transporters in mucosal disposition of topically applied ARV-based microbicides, these must be tested in epithelial cell line-based biopharmaceutical assays factoring the effect of relevant drug transporters. We have characterised gene expression of influx and efflux drug transporters in a panel of cervicovaginal cell lines and compared this to expression in cervicovaginal tissue. We also investigated the effect of dapivirine, darunavir and tenofovir, currently at advanced stages of microbicides development, on expression of drug transporters in cell lines. Expression of efflux ABC transporters in cervical tissue was best represented in HeLa, Ect1/E6E7 and End1/E6E7 cell lines. Expression of influx OCT and ENT transporters in ectocervix matched expression in Hela while expression of influx SLCO transporters in vagina was best reflected in VK2/E6E7 cell line. Stimulation with darunavir and dapivirine upregulated MRP transporters, including MRP5 involved in transport of tenofovir. Dapivirine also significantly downregulated tenofovir substrate MRP4 in cervical cell lines. Treatment with darunavir and dapivirine showed no significant effect on expression of BCRP, MRP2 and P-glycoprotein implicated in efflux of different ARV drugs. Darunavir strongly induced expression in most cell lines of CNT3 involved in cell uptake of nucleotide/nucleoside analogue reverse transcriptase inhibitors and SLCO drug transporters involved in cell uptake of protease inhibitors. This study provides insight into the suitability of cervicovaginal cell lines for assessment of ARV drugs in transport kinetics studies. The modulatory effect of darunavir and dapivirine on expression of drug

Expression of Genes for Drug Transporters in the Human Female Genital Tract and Modulatory Effect of Antiretroviral Drugs

PubMed Central

Hijazi, Karolin; Cuppone, Anna M.; Smith, Kieron; Stincarelli, Maria A.; Ekeruche-Makinde, Julia; De Falco, Giulia; Hold, Georgina L.; Shattock, Robin; Kelly, Charles G.; Pozzi, Gianni; Iannelli, Francesco

2015-01-01

Anti-retroviral (ARV) –based microbicides are one of the strategies pursued to prevent HIV-1 transmission. Delivery of ARV drugs to subepithelial CD4+ T cells at concentrations for protection is likely determined by drug transporters expressed in the cervicovaginal epithelium. To define the role of drug transporters in mucosal disposition of topically applied ARV-based microbicides, these must be tested in epithelial cell line-based biopharmaceutical assays factoring the effect of relevant drug transporters. We have characterised gene expression of influx and efflux drug transporters in a panel of cervicovaginal cell lines and compared this to expression in cervicovaginal tissue. We also investigated the effect of dapivirine, darunavir and tenofovir, currently at advanced stages of microbicides development, on expression of drug transporters in cell lines. Expression of efflux ABC transporters in cervical tissue was best represented in HeLa, Ect1/E6E7 and End1/E6E7 cell lines. Expression of influx OCT and ENT transporters in ectocervix matched expression in Hela while expression of influx SLCO transporters in vagina was best reflected in VK2/E6E7 cell line. Stimulation with darunavir and dapivirine upregulated MRP transporters, including MRP5 involved in transport of tenofovir. Dapivirine also significantly downregulated tenofovir substrate MRP4 in cervical cell lines. Treatment with darunavir and dapivirine showed no significant effect on expression of BCRP, MRP2 and P-glycoprotein implicated in efflux of different ARV drugs. Darunavir strongly induced expression in most cell lines of CNT3 involved in cell uptake of nucleotide/nucleoside analogue reverse transcriptase inhibitors and SLCO drug transporters involved in cell uptake of protease inhibitors. This study provides insight into the suitability of cervicovaginal cell lines for assessment of ARV drugs in transport kinetics studies. The modulatory effect of darunavir and dapivirine on expression of drug

A staged screening of registered drugs highlights remyelinating drug candidates for clinical trials

NASA Astrophysics Data System (ADS)

Eleuteri, C.; Olla, S.; Veroni, C.; Umeton, R.; Mechelli, R.; Romano, S.; Buscarinu, Mc.; Ferrari, F.; Calò, G.; Ristori, G.; Salvetti, M.; Agresti, C.

2017-04-01

There is no treatment for the myelin loss in multiple sclerosis, ultimately resulting in the axonal degeneration that leads to the progressive phase of the disease. We established a multi-tiered platform for the sequential screening of drugs that could be repurposed as remyelinating agents. We screened a library of 2,000 compounds (mainly Food and Drug Administration (FDA)-approved compounds and natural products) for cellular metabolic activity on mouse oligodendrocyte precursors (OPC), identifying 42 molecules with significant stimulating effects. We then characterized the effects of these compounds on OPC proliferation and differentiation in mouse glial cultures, and on myelination and remyelination in organotypic cultures. Three molecules, edaravone, 5-methyl-7-methoxyisoflavone and lovastatin, gave positive results in all screening tiers. We validated the results by retesting independent stocks of the compounds, analyzing their purity, and performing dose-response curves. To identify the chemical features that may be modified to enhance the compounds’ activity, we tested chemical analogs and identified, for edaravone, the functional groups that may be essential for its activity. Among the selected remyelinating candidates, edaravone appears to be of strong interest, also considering that this drug has been approved as a neuroprotective agent for acute ischemic stroke and amyotrophic lateral sclerosis in Japan.

A staged screening of registered drugs highlights remyelinating drug candidates for clinical trials

PubMed Central

Eleuteri, C.; Olla, S.; Veroni, C.; Umeton, R.; Mechelli, R.; Romano, S.; Buscarinu, MC.; Ferrari, F.; Calò, G.; Ristori, G.; Salvetti, M.; Agresti, C.

2017-01-01

There is no treatment for the myelin loss in multiple sclerosis, ultimately resulting in the axonal degeneration that leads to the progressive phase of the disease. We established a multi-tiered platform for the sequential screening of drugs that could be repurposed as remyelinating agents. We screened a library of 2,000 compounds (mainly Food and Drug Administration (FDA)-approved compounds and natural products) for cellular metabolic activity on mouse oligodendrocyte precursors (OPC), identifying 42 molecules with significant stimulating effects. We then characterized the effects of these compounds on OPC proliferation and differentiation in mouse glial cultures, and on myelination and remyelination in organotypic cultures. Three molecules, edaravone, 5-methyl-7-methoxyisoflavone and lovastatin, gave positive results in all screening tiers. We validated the results by retesting independent stocks of the compounds, analyzing their purity, and performing dose-response curves. To identify the chemical features that may be modified to enhance the compounds’ activity, we tested chemical analogs and identified, for edaravone, the functional groups that may be essential for its activity. Among the selected remyelinating candidates, edaravone appears to be of strong interest, also considering that this drug has been approved as a neuroprotective agent for acute ischemic stroke and amyotrophic lateral sclerosis in Japan. PMID:28387380

Structural and functional screening in human induced-pluripotent stem cell-derived cardiomyocytes accurately identifies cardiotoxicity of multiple drug types

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

Doherty, Kimberly R., E-mail: kimberly.doherty@quintiles.com; Talbert, Dominique R.; Trusk, Patricia B.

Safety pharmacology studies that evaluate new drug entities for potential cardiac liability remain a critical component of drug development. Current studies have shown that in vitro tests utilizing human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CM) may be beneficial for preclinical risk evaluation. We recently demonstrated that an in vitro multi-parameter test panel assessing overall cardiac health and function could accurately reflect the associated clinical cardiotoxicity of 4 FDA-approved targeted oncology agents using hiPS-CM. The present studies expand upon this initial observation to assess whether this in vitro screen could detect cardiotoxicity across multiple drug classes with known clinical cardiac risks.more » Thus, 24 drugs were examined for their effect on both structural (viability, reactive oxygen species generation, lipid formation, troponin secretion) and functional (beating activity) endpoints in hiPS-CM. Using this screen, the cardiac-safe drugs showed no effects on any of the tests in our panel. However, 16 of 18 compounds with known clinical cardiac risk showed drug-induced changes in hiPS-CM by at least one method. Moreover, when taking into account the Cmax values, these 16 compounds could be further classified depending on whether the effects were structural, functional, or both. Overall, the most sensitive test assessed cardiac beating using the xCELLigence platform (88.9%) while the structural endpoints provided additional insight into the mechanism of cardiotoxicity for several drugs. These studies show that a multi-parameter approach examining both cardiac cell health and function in hiPS-CM provides a comprehensive and robust assessment that can aid in the determination of potential cardiac liability. - Highlights: • 24 drugs were tested for cardiac liability using an in vitro multi-parameter screen. • Changes in beating activity were the most sensitive in predicting cardiac risk. • Structural effects add in

Drug-conjugated polymers as gene carriers for synergistic therapeutic effect.

PubMed

Pofali, P A; Singh, B; Dandekar, P; Jain, R D; Maharjan, S; Choi, Y J; Arote, R B; Cho, C S

2016-05-01

The ability to safely and effectively transfer gene into cells is the fundamental goal of gene delivery. In spite of the best efforts of researchers around the world, gene therapy has limited success. This may be because of several limitations of delivering gene which is one of the greatest technical challenges in the modern medicine. To address these issues, many efforts have been made to bind drugs and genes together by polymers for co-delivery to achieve synergistic effect. Usually, binding interaction of drugs with polymers is either physical or chemical. In case of drug-polymer physical interaction, the efficiency of drugs generally decreases because of separation of drugs from polymers in vivo whenever it comes in contact with charged biofluid/s or cells. While chemical interaction of drug-polymer overcomes the aforementioned obstacle, several problems such as steric hindrance, solubility, and biodegradability hinder it to develop as gene carrier. Considering these benefits and pitfalls, the objective of this review is to discuss the possible extent of drug-conjugated polymers as safe and efficient gene delivery carriers for achieving synergistic effect to combat various genetic disorders. © 2015 Wiley Periodicals, Inc.

Cardiovascular effects of anti-diabetes drugs

PubMed Central

Younk, Lisa M.; Lamos, Elizabeth M.

2016-01-01

Introduction Cardiovascular disease remains the major contributor to morbidity and mortality in diabetes. From the need to reduce cardiovascular risk in diabetes and to ensure that such risk is not exacerbated by drug treatments, governmental regulators and drug manufacturers have focused on clinical trials evaluating cardiovascular outcomes. Areas covered Findings from mechanistic and clinical trials of biguanides, sulfonylureas, thiazolidinediones, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium-glucose transporter 2 (SGLT-2) inhibitors will be reviewed. These drug classes will be compared within the context of available cardiovascular outcomes data. Clinical implications of new study regulations will be examined. Expert opinion Recent cardiovascular studies provide a more comprehensive evaluation of specific anti-diabetes therapy in individuals with high cardiovascular risk. Long-term effects of anti-hyperglycemic agents in patients with lower cardiovascular risk are still speculative. Historical data supports continued use of metformin as a first-line agent. DPP-4 inhibitors and GLP-1 receptor agonists appear to have neutral effects on cardiovascular outcomes. The significantly decreased cardiovascular risk associated with empagliflozin SGLT-2 inhibitor therapy is impressive and may change how practitioners prescribe add-on therapy to metformin. PMID:27268470

Drug effects on drug targets: inhibition of enzymes by neuroleptics, antimycotics, antibiotics and other drugs on human pathogenic amoebas and their anti-proliferative effects.

PubMed

Ondarza, Raúl N

2007-11-01

This paper reviews the inhibition of various enzymes by neuroleptics, anti-mycotics, antibiotics and other drugs on three species of human pathogenic amoebas, mainly Entamoeba histolytica, Acanthamoeba polyphaga and Naegleria fowleri, and their antiproliferative effects. A recent patent registered by Philip relates to the combination of an antibacterial formulation and antifungal agent for producing a therapeutically effective quantity of an antimicrobial that is suitable for suppressing or treating fungal growth. The rationale behind this patent focused on essential and valid targets with a description of the main pathogenic characteristics of these amoebas. The study of new targets, such as trypanothione and trypanothione reductase, and the drug effects of selected agents were arranged into six main groups: A) Inhibition of disulfide reducing enzymes by neuroleptics, antimycotics and antibiotics; B) Comparative evaluation of the efficacies of several drugs with antiproliferative activities; C) Inhibition of the enzymes for the synthesis of trypanothione, such as ornithine decarboxylase, spermidine synthase and trypanothione synthetase; D) Inhibition of the glycolytic enzyme PPi-dependent phosphofructokinase (PFK) from Entamoeba and Naegleria by pyrophosphate analogues, different from the host enzyme; E) Inhibition of enzymes secreted by these parasites to invade the human host, for example cysteine proteinases; and F) Inhibition of encystment pathways and cyst-wall assembly proteins.

Neuroprotective Effects of Drug-Induced Therapeutic Hypothermia in Central Nervous System Diseases.

PubMed

Ma, Junwei; Wang, Yibin; Wang, Zhong; Li, Haiying; Wang, Zhimin; Chen, Gang

2017-01-01

This review article focuses on the neuroprotective effect of drug-induced hypothermia in cerebrovascular diseases and discusses its related side effects. A systematic literature search was performed using Pubmed and Embase electronic databases for a retrospective analysis. Experimental studies have shown that drug-induced hypothermia alleviates brain damage and plays a neuroprotective role, thereby reducing mortality and ameliorating neurological deficits. Therefore, drug-induced hypothermia has an important research value and is worth further consideration in the clinical setting. However, drug-induced hypothermia is also associated with side effects, such as ventricular tachycardia, ventricular fibrillation, suppressed immune function, infection, electrolyte imbalance, glucose metabolism disorders, and skeletal muscle tremor. Existing drugs with cooling effects belong to the following categories: (1) dopamine receptor agonists; (2) cannabis; (3) opioid receptors; (4) vanilloid receptors; (5) vasopressins (potent neurotensin receptor agonists); (6) thyroid drugs; (7) adenosine drugs; and (8) purine drugs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Screening of a Drug Library Identifies Inhibitors of Cell Intoxication by CNF1.

PubMed

Mahtal, Nassim; Brewee, Clémence; Pichard, Sylvain; Visvikis, Orane; Cintrat, Jean-Christophe; Barbier, Julien; Lemichez, Emmanuel; Gillet, Daniel

2018-04-06

Cytotoxic necrotizing factor 1 (CNF1) is a toxin produced by pathogenic strains of Escherichia coli responsible for extra-intestinal infections. CNF1 deamidates Rac1, thereby triggering its permanent activation and worsening inflammatory reactions. Activated Rac1 is prone to proteasomal degradation. There is no targeted therapy against CNF1, despite its clinical relevance. In this work we developed a fluorescent cell-based immunoassay to screen for inhibitors of CNF1-induced Rac1 degradation among 1120 mostly approved drugs. Eleven compounds were found to prevent CNF1-induced Rac1 degradation, and five also showed a protective effect against CNF1-induced multinucleation. Finally, lasalocid, monensin, bepridil, and amodiaquine protected cells from both diphtheria toxin and CNF1 challenges. These data highlight the potential for drug repurposing to fight several bacterial infections and Rac1-based diseases. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The longitudinal effect of drug use on productivity status of nonmetropolitan african american young adults.

PubMed

Roldós, María Isabel

2014-01-01

The purpose of this study was to investigate the longitudinal effect of marijuana and heavy alcohol use on the productivity status of nonmetropolitan African American young adults. This analysis was based on secondary data from the Family and Community Health Study. For alcohol, the study evaluated the effects on productivity status for individuals with heavy alcohol use trajectories from adolescence into young adulthood while marijuana effects were evaluated during the period when adolescents are more likely to have initiated usage (14-16 years of age). Productivity status was measured when study participants were between 18 and 21 years, for both alcohol and marijuana. Multivariate logistic regression models were used to test the association between subjects' drug use and productivity. Bivariate analysis of the effects of marijuana use indicate that marijuana users by age 16 are 35% less likely to be productive at age 21 than those who have not initiated marijuana use (p < .005). After controlling for individual, community, and family factors, the multivariate logistic models for alcohol and marijuana use suggest that early adolescence drug use (marijuana and heavy alcohol use) do not have an impact on productivity status during early adulthood. Analyzing and understanding the different drug use trajectories in relation to a productivity outcome is important for policies and research geared to preventing drug use and in identifying its relation with micro- and macro-level labor market outcomes. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A genome-wide RNAi screen identifies novel targets of neratinib sensitivity leading to neratinib and paclitaxel combination drug treatments.

PubMed

Seyhan, Attila A; Varadarajan, Usha; Choe, Sung; Liu, Yan; McGraw, John; Woods, Matthew; Murray, Stuart; Eckert, Amy; Liu, Wei; Ryan, Terence E

2011-06-01

ErbB2 is frequently activated in tumors, and influences a wide array of cellular functions, including proliferation, apoptosis, cell motility and adhesion. HKI-272 (neratinib) is a small molecule pan-kinase inhibitor of the ErbB family of receptor tyrosine kinases, and shows strong antiproliferative activity in ErbB2-overexpressing breast cancer cells. We undertook a genome-wide pooled lentiviral RNAi screen to identify synthetic lethal or enhancer (synthetic modulator screen) genes that interact with neratinib in a human breast cancer cell line (SKBR-3). These genes upon knockdown would modulate cell viability in the presence of subeffective concentrations of neratinib. We discovered a diverse set of genes whose depletion selectively impaired or enhanced the viability of SKBR-3 cells in the presence of neratinib. We observed diverse pathways including EGFR, hypoxia, cAMP, and protein ubiquitination that, when co-treated with RNAi and neratinib, resulted in arrest of cell proliferation. Examining the changes of these genes and their protein products also led to a rationale for clinically relevant drug combination treatments. Treatment of cells with either paclitaxel or cytarabine in combination with neratinib resulted in a strong antiproliferative effect. The identification of novel mediators of cellular response to neratinib and the development of potential drug combination treatments have expanded our understanding of neratinib's mode-of-action for the development of more effective therapeutic regimens. Notably, our findings support a paclitaxel and neratinib phase III clinical trial in breast cancer patients.

Predicting drug court outcome among amphetamine-using participants.

PubMed

Wu, Lora J; Altshuler, Sandra J; Short, Robert A; Roll, John M

2012-06-01

Amphetamine use and abuse carry with it substantial social costs. Although there is a perception that amphetamine users are more difficult to treat than other substance users, drug courts have been used to effectively address drug-related crimes and hold the potential to lessen the impact of amphetamine abuse through efficacious treatment and rehabilitation. The objective of this study was to identify predictors of drug court outcome among amphetamine-using participants. A drug court database was obtained (N = 540) and amphetamine-using participants (n= 341) identified. Multivariate binary regression models run for the amphetamine-using participants identified being employed and being a parent as predictive of successful completion of the program, whereas being sanctioned to jail during the program was inversely related to program completion. Copyright © 2012 Elsevier Inc. All rights reserved.

Using human genetics to predict the effects and side-effects of drugs.

PubMed

Stender, Stefan; Tybjærg-Hansen, Anne

2016-04-01

'Genetic proxies' are increasingly being used to predict the effects of drugs. We present an up-to-date overview of the use of human genetics to predict effects and adverse effects of lipid-targeting drugs. LDL cholesterol lowering variants in HMG-Coenzyme A reductase and Niemann-Pick C1-like protein 1, the targets for statins and ezetimibe, protect against ischemic heart disease (IHD). However, HMG-Coenzyme A reductase and Niemann-Pick C1-Like Protein 1-variants also increase the risk of type 2 diabetes and gallstone disease, respectively. Mutations in proprotein convertase subtilisin kexin 9 (PCSK9), apolipoprotein B, and microsomal triglyceride transfer protein cause low LDL cholesterol and protect against IHD. In addition, mutations in apolipoprotein B and microsomal triglyceride transfer protein cause hepatic steatosis, in concordance with drugs that inhibit these targets. Both mutations in PCSK9 and PCSK9-inhibition seem without adverse effects. Mutations in APOC3 cause low triglycerides and protect against IHD, and recent pharmacological APOC3-inhibition reported major reductions in plasma triglycerides. Human genetics support that low lipoprotein(a) protects against IHD, without adverse effects, and the first trial of lipoprotein(a) inhibition reduced lipoprotein(a) up to 78%. Recent genetic studies have confirmed the efficacy of statins and ezetimibe in protecting against IHD. Results from human genetics support that several lipid-lowering drugs currently under development are likely to prove efficacious in protecting against IHD, without major adverse effects.

Threshold virus dynamics with impulsive antiretroviral drug effects

PubMed Central

Lou, Jie; Lou, Yijun; Wu, Jianhong

2013-01-01

The purposes of this paper are twofold: to develop a rigorous approach to analyze the threshold behaviors of nonlinear virus dynamics models with impulsive drug effects and to examine the feasibility of virus clearance following the Manuals of National AIDS Free Antiviral Treatment in China. An impulsive system of differential equations is developed to describe the within-host virus dynamics of both wild-type and drug-resistant strains when a combination of antiretroviral drugs is used to induce instantaneous drug effects at a sequence of dosing times equally spaced while drug concentrations decay exponentially after the dosing time. Threshold parameters are derived using the basic reproduction number of periodic epidemic models, and are used to depict virus clearance/persistence scenarios using the theory of asymptotic periodic systems and the persistence theory of discrete dynamical systems. Numerical simulations using model systems parametrized in terms of the antiretroviral therapy recommended in the aforementioned Manuals illustrate the theoretical threshold virus dynamics, and examine conditions under which the impulsive antiretroviral therapy leads to treatment success. In particular, our results show that only the drug-resistant strain can dominate (the first-line treatment program guided by the Manuals) or both strains may be rapidly eliminated (the second-line treatment program), thus the work indicates the importance of implementing the second-line treatment program as soon as possible. PMID:21987085

Effect of privatization of the drug distribution system on drug prices in Malaysia.

PubMed

Babar, Z D; Izham, M I M

2009-08-01

Previous studies on anti-infective and cardiovascular drugs have shown extraordinary price increases following privatization of the Malaysian drug distribution system. Therefore, it was felt that there was a need to undertake a full-scale study to evaluate the effect of privatization of the Malaysian drug distribution system on drug prices. To compare pre-privatization drug prices with post-privatization drug prices, and to compare the prices with international reference prices (IRPs). Five hundred and sixty-four drugs were listed in price lists for 1994, 1995-1996, 1997-2000 and 2001-2003. The 1994 data were taken as the pre-privatization prices, and all other lists were considered to be post-privatization prices. The pre-privatization prices (1994) were compared with those in 1995-1996. The prices in 1995-1996 were compared with those in 1997-2000, and the 1997-2000 prices were compared with those in 2001-2003. Furthermore, the 2001-2003 prices were compared with the median IRPs taken from Management Sciences for Health. The prices increased by 10.42% in 1995-1996, decreased by 3.37% in 1997-2000, and increased by 64.04% in 2001-2003. The increase in prices does not follow any pricing formula but is influenced by free market principles. The commonly used generic drugs showed enormously higher prices compared with the IRPs. Some of the prices increased several hundred-fold compared with the previous year, showing that no pricing formula has been followed. Increasing prices over the years may lead to higher expenditures and a hurdle to drug accessibility. A rational pricing structure is needed for transparent pricing, and government involvement and the formation of a medicine pricing policy seems vital.

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions.

PubMed

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel; Wilkinson, Mark D

2013-04-05

The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this prototype was limited to a single knowledge domain

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions

PubMed Central

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel

2013-01-01

Background The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. Objective The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. Methods We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. Results A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. Conclusions The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this

Computerized EEG analysis for studying the effect of drugs on the central nervous system.

PubMed

Rosadini, G; Cavazza, B; Rodriguez, G; Sannita, W G; Siccardi, A

1977-11-01

Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.

Prediction of Effective Drug Combinations by an Improved Naïve Bayesian Algorithm.

PubMed

Bai, Li-Yue; Dai, Hao; Xu, Qin; Junaid, Muhammad; Peng, Shao-Liang; Zhu, Xiaolei; Xiong, Yi; Wei, Dong-Qing

2018-02-05

Drug combinatorial therapy is a promising strategy for combating complex diseases due to its fewer side effects, lower toxicity and better efficacy. However, it is not feasible to determine all the effective drug combinations in the vast space of possible combinations given the increasing number of approved drugs in the market, since the experimental methods for identification of effective drug combinations are both labor- and time-consuming. In this study, we conducted systematic analysis of various types of features to characterize pairs of drugs. These features included information about the targets of the drugs, the pathway in which the target protein of a drug was involved in, side effects of drugs, metabolic enzymes of the drugs, and drug transporters. The latter two features (metabolic enzymes and drug transporters) were related to the metabolism and transportation properties of drugs, which were not analyzed or used in previous studies. Then, we devised a novel improved naïve Bayesian algorithm to construct classification models to predict effective drug combinations by using the individual types of features mentioned above. Our results indicated that the performance of our proposed method was indeed better than the naïve Bayesian algorithm and other conventional classification algorithms such as support vector machine and K-nearest neighbor.

Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections.

PubMed

Don, Rob; Ioset, Jean-Robert

2014-01-01

The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.

Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.

PubMed

Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

2015-01-01

As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.

Effectiveness, safety and cost of drug substitution in hypertension

PubMed Central

Johnston, Atholl; Stafylas, Panagiotis; Stergiou, George S

2010-01-01

Cost-containment measures in healthcare provision include the implementation of therapeutic and generic drug substitution strategies in patients whose condition is already well controlled with pharmacotherapy. Treatment for hypertension is frequently targeted for such measures. However, drug acquisition costs are only part of the cost-effectiveness equation, and a variety of other factors need to be taken into account when assessing the impact of switching antihypertensives. From the clinical perspective, considerations include maintenance of an appropriate medication dose during the switching process; drug equivalence in terms of clinical effectiveness; and safety issues, including the diverse adverse-event profiles of available alternative drugs, differences in the ‘inactive’ components of drug formulations and the quality of generic formulations. Patients' adherence to and persistence with therapy may be negatively influenced by switching, which will also impact on treatment effectiveness. From the economic perspective, the costs that are likely to be incurred by switching antihypertensives include those for additional clinic visits and laboratory tests, and for hospitalization if required to address problems arising from adverse events or poorly controlled hypertension. Indirect costs and the impact on patients' quality of life also require assessment. Substitution strategies for antihypertensives have not been tested in large outcome trials and there is little available clinical or economic evidence on which to base decisions to switch drugs. Although the cost of treatment should always be considered, careful assessment of the human and economic costs and benefits of antihypertensive drug substitution is required before this practice is recommended. PMID:20716230

Effectiveness, safety and cost of drug substitution in hypertension.

PubMed

Johnston, Atholl; Stafylas, Panagiotis; Stergiou, George S

2010-09-01

Cost-containment measures in healthcare provision include the implementation of therapeutic and generic drug substitution strategies in patients whose condition is already well controlled with pharmacotherapy. Treatment for hypertension is frequently targeted for such measures. However, drug acquisition costs are only part of the cost-effectiveness equation, and a variety of other factors need to be taken into account when assessing the impact of switching antihypertensives. From the clinical perspective, considerations include maintenance of an appropriate medication dose during the switching process; drug equivalence in terms of clinical effectiveness; and safety issues, including the diverse adverse-event profiles of available alternative drugs, differences in the 'inactive' components of drug formulations and the quality of generic formulations. Patients' adherence to and persistence with therapy may be negatively influenced by switching, which will also impact on treatment effectiveness. From the economic perspective, the costs that are likely to be incurred by switching antihypertensives include those for additional clinic visits and laboratory tests, and for hospitalization if required to address problems arising from adverse events or poorly controlled hypertension. Indirect costs and the impact on patients' quality of life also require assessment. Substitution strategies for antihypertensives have not been tested in large outcome trials and there is little available clinical or economic evidence on which to base decisions to switch drugs. Although the cost of treatment should always be considered, careful assessment of the human and economic costs and benefits of antihypertensive drug substitution is required before this practice is recommended.

Effects of atypical antipsychotic drugs on QT interval in patients with mental disorders

PubMed Central

Aronow, Wilbert S.

2018-01-01

Background Drug-induced QT prolongation is associated with higher risk of cardiac arrhythmias and cardiovascular mortality. We investigated the effects of atypical antipsychotic drugs on QT interval in children and adults with mental disorders. Methods We conducted random-effects direct frequentist meta-analyses of aggregate data from randomized controlled trials (RCT) and appraised the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Our search in PubMed, EMBASE, the Cochrane Library, clinicaltrials.gov, and PharmaPendium up to October 2017 identified studies that examined aripiprazole, quetiapine, risperidone, olanzapine, ziprasidone and brexpiprazole. Results Low quality evidence suggests that aripiprazole (four meta-analyses and twelve RCTs), brexpiprazole (one systematic review and four RCTs) or olanzapine (five meta-analyses and twenty RCTs) do not increase QT interval. Low quality evidence suggests that ziprasidone (five meta-analyses and 11 RCTs) increases QT interval and the rates of QT prolongation while risperidone (four meta-analyses, 70 RCTs) and quetiapine (two meta-analyses and seven RCTs) are associated with QT prolongation and greater odds of torsades de pointes ventricular tachycardia especially in cases of drug overdose. Conclusions The main conclusion of our study is that in people with mental disorders and under treatment with atypical antipsychotic drugs, in order to avoid QT prolongation and reduce the risk of ventricular tachycardia clinicians may recommend aripiprazole, brexpiprazole or olanzapine in licensed doses. Long-term comparative safety needs to be established. PMID:29862236

Drugs and Pregnancy: The Effects of Nonmedical Use of Drugs on Pregnancy, Childbirth, and Neonates. National Institute on Drug Abuse Research Issues 5.

ERIC Educational Resources Information Center

Ferguson, Patricia, Ed.; And Others

The National Institute on Drug Abuse presents this report as the fifth in a series intended to summarize the empirical research findings and major theoretical approaches relating to the the issues of drug use and abuse. Included in this volume are summaries of the major research findings concerning the effects of nonmedical drug use on pregnancy.…

Analgesic Effects of Toad Cake and Toad-cake-containing Herbal Drugs

PubMed Central

Inoue, Eiji; Shimizu, Yasuharu; Masui, Ryo; Usui, Tomomi; Sudoh, Keiichi

2014-01-01

Objectives: This study was conducted to clarify the analgesic effect of toad cake and toad-cake-containing herbal drugs. Methods: We counted the writhing response of mice after the intraperitoneal administration of acetic acid as a nociceptive pain model and the withdrawal response after the plantar surface stimulation of the hind paw induced by partial sciatic nerve ligation of the mice as a neuropathic pain model to investigate the analgesic effect of toad cake and toad-cake-containing herbal drugs. A co-treatment study with serotonin biosynthesis inhibitory drug 4-chloro- DL-phenylalanine methyl ester hydrochloride (PCPA), the catecholamine biosynthesis inhibitory drug α-methyl- DL-tyrosine methyl ester hydrochloride (AMPT) or the opioid receptor antagonist naloxone hydrochloride was also conducted. Results: Analgesic effects in a mouse model of nociceptive pain and neuropathic pain were shown by oral administration of toad cake and toad-cake-containing herbal drugs. The effects of toad cake and toad-cake-containing herbal drugs disappeared upon co-treatment with PCPA, but not with AMPT or naloxone in the nociceptive pain model; the analgesic effect of toad-cake-containing herbal drugs also disappeared upon co-treatment with PCPA in the neuropathic pain model. Conclusion: Toad cake and toad-cake-containing herbal drugs have potential for the treatments of nociceptive pain and of neuropathic pain, such as post-herpetic neuralgia, trigeminal neuralgia, diabetic neuralgia, and postoperative or posttraumatic pain, by activation of the central serotonin nervous system. PMID:25780693

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins.

PubMed

Banfi, Cristina; Baetta, Roberta; Gianazza, Erica; Tremoli, Elena

2017-06-01

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drug-Drug Interactions, Effectiveness, and Safety of Hormonal Contraceptives in Women Living with HIV.

PubMed

Scarsi, Kimberly K; Darin, Kristin M; Chappell, Catherine A; Nitz, Stephanie M; Lamorde, Mohammed

2016-11-01

Family planning options, including hormonal contraceptives, are essential for improving reproductive health among the more than 17 million women living with HIV worldwide. For these women, prevention of unintended pregnancy decreases maternal and child mortality, as well as reduces the risk of perinatal HIV transmission. Similarly, treatment of HIV with antiretroviral therapy (ART) is essential for reducing morbidity and mortality among HIV-positive individuals, as well as preventing HIV transmission between sexual partners or from mother to child. Importantly, despite the benefits of hormonal contraceptives, barriers to effective family planning methods exist for HIV-positive women. Specifically, drug-drug interactions can occur between some antiretroviral medications and some hormonal contraceptives, which may influence both contraceptive efficacy and tolerability. In addition, safety concerns have been raised about the impact of hormonal contraceptives on HIV disease progression, tolerability, and the risk of female-to-male HIV transmission. This review article summarizes the potential for drug-drug interactions, tolerability, and contraceptive effectiveness when hormonal contraceptives are combined with ART. In addition, the evidence surrounding the influence of hormonal contraceptives on HIV transmission and HIV disease progression in women living with HIV are summarized.

Radiotherapy and "new" drugs-new side effects?

PubMed Central

2011-01-01

Background and purpose Targeted drugs have augmented the cancer treatment armamentarium. Based on the molecular specificity, it was initially believed that these drugs had significantly less side effects. However, currently it is accepted that all of these agents have their specific side effects. Based on the given multimodal approach, special emphasis has to be placed on putative interactions of conventional cytostatic drugs, targeted agents and other modalities. The interaction of targeted drugs with radiation harbours special risks, since the awareness for interactions and even synergistic toxicities is lacking. At present, only limited is data available regarding combinations of targeted drugs and radiotherapy. This review gives an overview on the current knowledge on such combined treatments. Materials and methods Using the following MESH headings and combinations of these terms pubmed database was searched: Radiotherapy AND cetuximab/trastuzumab/panitumumab/nimotuzumab, bevacizumab, sunitinib/sorafenib/lapatinib/gefitinib/erlotinib/sirolimus, thalidomide/lenalidomide as well as erythropoietin. For citation crosscheck the ISI web of science database was used employing the same search terms. Results Several classes of targeted substances may be distinguished: Small molecules including kinase inhibitors and specific inhibitors, antibodies, and anti-angiogenic agents. Combination of these agents with radiotherapy may lead to specific toxicities or negatively influence the efficacy of RT. Though there is only little information on the interaction of molecular targeted radiation and radiotherapy in clinical settings, several critical incidents are reported. Conclusions The addition of molecular targeted drugs to conventional radiotherapy outside of approved regimens or clinical trials warrants a careful consideration especially when used in conjunction in hypo-fractionated regimens. Clinical trials are urgently needed in order to address the open question in regard

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database.

PubMed

Ma, Chifeng; Chen, Hung-I; Flores, Mario; Huang, Yufei; Chen, Yidong

2013-01-01

Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions. Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects. BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased. The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates.

Kinome expression profiling of human neuroblastoma tumors identifies potential drug targets for ultra high-risk patients.

PubMed

Russo, Roberta; Cimmino, Flora; Pezone, Lucia; Manna, Francesco; Avitabile, Marianna; Langella, Concetta; Koster, Jan; Casale, Fiorina; Raia, Maddalena; Viola, Giampietro; Fischer, Matthias; Iolascon, Achille; Capasso, Mario

2017-10-01

Neuroblastoma (NBL) accounts for >7% of malignancies in patients younger than 15 years. Low- and intermediate-risk patients exhibit excellent or good prognosis after treatment, whereas for high-risk (HR) patients, the estimated 5-year survival rates is still <40%. The ability to stratify HR patients that will not respond to standard treatment strategies is critical for informed treatment decisions. In this study, we have generated a specific kinome gene signature, named Kinome-27, which is able to identify a subset of HR-NBL tumors, named ultra-HR NBL, with highly aggressive clinical behavior that not adequately respond to standard treatments. We have demonstrated that NBL cell lines expressing the same kinome signature of ultra-HR tumors (ultra-HR-like cell lines) may be selectively targeted by the use of two drugs [suberoylanilide hydroxamic acid (SAHA) and Radicicol], and that the synergic combination of these drugs is able to block the ultra-HR-like cells in G2/M phase of cell cycle. The use of our signature in clinical practice will allow identifying patients with negative outcome, which would benefit from new and more personalized treatments. Preclinical in vivo studies are needed to consolidate the SAHA and Radicicol treatment in ultra-HR NBL patients. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

New old challenges in tuberculosis: potentially effective nanotechnologies in drug delivery.

PubMed

Sosnik, Alejandro; Carcaboso, Angel M; Glisoni, Romina J; Moretton, Marcela A; Chiappetta, Diego A

2010-03-18

Tuberculosis (TB) is the second most deadly infectious disease. Despite potentially curative pharmacotherapies being available for over 50 years, the length of the treatment and the pill burden can hamper patient lifestyle. Thus, low compliance and adherence to administration schedules remain the main reasons for therapeutic failure and contribute to the development of multi-drug-resistant (MDR) strains. Pediatric patients constitute a high risk population. Most of the first-line drugs are not commercially available in pediatric form. The design of novel antibiotics attempts to overcome drug resistance, to shorten the treatment course and to reduce drug interactions with antiretroviral therapies. On the other hand, the existing anti-TB drugs are still effective. Overcoming technological drawbacks of these therapeutic agents as well as improving the effectiveness of the drug by targeting the infection reservoirs remains the central aims of Pharmaceutical Technology. In this framework, nanotechnologies appear as one of the most promising approaches for the development of more effective and compliant medicines. The present review thoroughly overviews the state-of-the-art in the development of nano-based drug delivery systems for encapsulation and release of anti-TB drugs and discusses the challenges that are faced in the development of a more effective, compliant and also affordable TB pharmacotherapy. Copyright 2009 Elsevier B.V. All rights reserved.

Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database.

PubMed

Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

2016-11-01

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.