Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

PubMed Central

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

2016-01-01

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

Important drug-nutrient interactions.

PubMed

Mason, Pamela

2010-11-01

Drugs have the potential to interact with nutrients potentially leading to reduced therapeutic efficacy of the drug, nutritional risk or increased adverse effects of the drug. Despite significant interest in such interactions going back to over more than 40 years, the occurrence and clinical significance of many drug-nutrient interactions remains unclear. However, interactions involving drugs with a narrow therapeutic margin such as theophylline and digoxin and those that require careful blood monitoring such as warfarin are likely to be those of clinical significance. Drugs can affect nutrition as a result of changes in appetite and taste as well as having an influence on absorption or metabolism of nutrients. Moreover, foods and supplements can also interact with drugs, of which grapefruit juice and St John's wort are key examples. Significant numbers of people take both supplements and medication and are potentially at risk from interactions. Professionals, such as pharmacists, dietitians, nurses and doctors, responsible for the care of patients should therefore check whether supplements are being taken, while for researchers this is an area worthy of significant further study, particularly in the context of increasingly complex drug regimens and the plethora of new drugs.

Data-driven prediction of adverse drug reactions induced by drug drug interactions

DTIC Science & Technology

2017-06-08

currently on the market and for which drug-protein interaction information is available . These predictions are publicly accessible at http://avoid...associated with these ADRs via DDIs. We made the predictions publicly available via internet access. Keywords: Drug-drug interactions, Adverse drug reactions...ˆDeceased Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research

Drug-drug interactions involving lysosomes: mechanisms and potential clinical implications.

PubMed

Logan, Randall; Funk, Ryan S; Axcell, Erick; Krise, Jeffrey P

2012-08-01

Many commercially available, weakly basic drugs have been shown to be lysosomotropic, meaning they are subject to extensive sequestration in lysosomes through an ion trapping-type mechanism. The extent of lysosomal trapping of a drug is an important therapeutic consideration because it can influence both activity and pharmacokinetic disposition. The administration of certain drugs can alter lysosomes such that their accumulation capacity for co-administered and/or secondarily administered drugs is altered. In this review the authors explore what is known regarding the mechanistic basis for drug-drug interactions involving lysosomes. Specifically, the authors address the influence of drugs on lysosomal pH, volume and lipid processing. Many drugs are known to extensively accumulate in lysosomes and significantly alter their structure and function; however, the therapeutic and toxicological implications of this remain controversial. The authors propose that drug-drug interactions involving lysosomes represent an important potential source of variability in drug activity and pharmacokinetics. Most evaluations of drug-drug interactions involving lysosomes have been performed in cultured cells and isolated tissues. More comprehensive in vivo evaluations are needed to fully explore the impact of this drug-drug interaction pathway on therapeutic outcomes.

Grapefruit and drug interactions.

PubMed

2012-12-01

Since the late 1980s, grapefruit juice has been known to affect the metabolism of certain drugs. Several serious adverse effects involving drug interactions with grapefruit juice have been published in detail. The components of grapefruit juice vary considerably depending on the variety, maturity and origin of the fruit, local climatic conditions, and the manufacturing process. No single component accounts for all observed interactions. Other grapefruit products are also occasionally implicated, including preserves, lyophylised grapefruit juice, powdered whole grapefruit, grapefruit seed extract, and zest. Clinical reports of drug interactions with grapefruit juice are supported by pharmacokinetic studies, each usually involving about 10 healthy volunteers, in which the probable clinical consequences were extrapolated from the observed plasma concentrations. Grapefruit juice inhibits CYP3A4, the cytochrome P450 isoenzyme most often involved in drug metabolism. This increases plasma concentrations of the drugs concerned, creating a risk of overdose and dose-dependent adverse effects. Grapefruit juice also inhibits several other cytochrome P450 isoenzymes, but they are less frequently implicated in interactions with clinical consequences. Drugs interacting with grapefruit and inducing serious clinical consequences (confirmed or very probable) include: immunosuppressants, some statins, benzodiazepines, most calcium channel blockers, indinavir and carbamazepine. There are large inter-individual differences in enzyme efficiency. Along with the variable composition of grapefruit juice, this makes it difficult to predict the magnitude and clinical consequences of drug interactions with grapefruit juice in a given patient. There is increasing evidence that transporter proteins such as organic anion transporters and P-glycoprotein are involved in interactions between drugs and grapefruit juice. In practice, numerous drugs interact with grapefruit juice. Although only a few

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

PubMed

Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

2017-05-01

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

Pharmacodynamics and common drug-drug interactions of the third-generation antiepileptic drugs.

PubMed

Stefanović, Srđan; Janković, Slobodan M; Novaković, Milan; Milosavljević, Marko; Folić, Marko

2018-02-01

Anticonvulsants that belong to the third generation are considered as 'newer' antiepileptic drugs, including: eslicarbazepine acetate, lacosamide, perampanel, brivaracetam, rufinamide and stiripentol. Areas covered: This article reviews pharmacodynamics (i.e. mechanisms of action) and clinically relevant drug-drug interactions of the third-generation antiepileptic drugs. Expert opinion: Newer antiepileptic drugs have mechanisms of action which are not shared with the first and the second generation anticonvulsants, like inhibition of neurotransmitters release, blocking receptors for excitatory amino acids and new ways of sodium channel inactivation. New mechanisms of action increase chances of controlling forms of epilepsy resistant to older anticonvulsants. Important advantage of the third-generation anticonvulsants could be their little propensity for interactions with both antiepileptic and other drugs observed until now, making prescribing much easier and safer. However, this may change with new studies specifically designed to discover drug-drug interactions. Although the third-generation antiepileptic drugs enlarged therapeutic palette against epilepsy, 20-30% of patients with epilepsy is still treatment-resistant and need new pharmacological approach. There is great need to explore all molecular targets that may directly or indirectly be involved in generation of seizures, so a number of candidate compounds for even newer anticonvulsants could be generated.

Potentially harmful drug-drug interactions in the elderly: a review.

PubMed

Hines, Lisa E; Murphy, John E

2011-12-01

Elderly patients are vulnerable to drug interactions because of age-related physiologic changes, an increased risk for disease associated with aging, and the consequent increase in medication use. The purpose of this narrative review was to describe findings from rigorously designed observational cohort and case-control studies that have assessed specific drug interactions in elderly patients. The PubMed and International Pharmaceutical Abstracts databases were searched for studies published in English over the past 10 years (December 2000-December 2010) using relevant Medical Subject Headings terms (aged; aged, 80 and over; and drug interactions) and search terms (drug interaction and elderly). Search strategies were saved and repeated through September 2011 to ensure that the most recent relevant published articles were identified. Additional articles were found using a search of review articles and reference lists of the identified studies. Studies were included if they were observational cohort or case-control studies that reported specific adverse drug interactions, included patients aged ≥65 years, and evaluated clinically meaningful end points. Studies were excluded if they used less rigorous observational designs, assessed pharmacokinetic/pharmacodynamic properties, evaluated drug-nutrient or drug-disease interactions or interactions of drug combinations used for therapeutic benefit (eg, dual antiplatelet therapy), or had inconclusive evidence. Seventeen studies met the inclusion criteria. Sixteen studies reported an elevated risk for hospitalization in older adults associated with adverse drug interactions. The drug interactions included: angiotensin-converting enzyme (ACE) inhibitors and potassium-sparing diuretics, ACE inhibitors or angiotensin receptor blockers and sulfamethoxazole/trimethoprim, benzodiazepines or zolpidem and interacting medications, calcium channel blockers and macrolide antibiotics, digoxin and macrolide antibiotics, lithium and

6-mercaptopurine and daunorubicin double drug liposomes-preparation, drug-drug interaction and characterization.

PubMed

Agrawal, Vineet; Paul, Manash K; Mukhopadhyay, Anup K

2005-01-01

This article addresses and investigates the dual incorporation of daunorubicin (DR) and 6-mercaptopurine (6-MP) in liposomes for better chemotherapy. These drugs are potential candidates for interaction due to the quinone (H acceptor) and hydroxyl (H donor) groups on DR and 6-MP, respectively. Interactions between the two drugs in solution were monitored by UV/Vis and fluorescence spectroscopy. Interaction between the two drugs inside the liposomes was evaluated by HPLC (for 6-MP) and by fluorescence spectroscopy (for daunorubicin) after phospholipase-mediated liposome lysis. Our results provide evidence for the lack of interaction between the two drugs in solution and in liposomes. The entrapment efficiencies of 6-MP in the neutral Phosphatidyl choline (PC):Cholesterol (Chol):: 2:1 and anionic PC:Chol:Cardiolipin (CL) :: 4:5:1 single and double drug liposomes were found to be 0.4% and 1.5% (on average), respectively. The entrapment efficiencies of DR in the neutral and anionic double drug liposomes were found to be 55% and 31%, respectively. The corresponding entrapment of daunorubicin in the single drug liposomes was found to be 62% on average. Our thin layer chromatography (TLC) and transmission electron microscopy (TEM) results suggest stability of lipid and liposomes, thus pointing plausible existence of double drug liposomes. Cytotoxicity experiments were performed by using both single drug and double drug liposomes. By comparing the results of phase contrast and fluorescence microscopy, it was observed that the double drug liposomes were internalized in the jurkat and Hut78 (highly resistant cell line) leukemia cells as viewed by the fluorescence of daunorubicin. The cytotoxicity was dose dependent and had shown a synergistic effect when double drug liposome was used.

Projections for antiinfective drug shortages and time to actual resolution.

PubMed

McLaughlin, Milena M; Pentoney, Zachary; Skoglund, Erik; Scheetz, Marc H

2014-12-01

The results of a national study of projected versus actual times to resolution of temporary U.S. shortages of antiinfective drugs are presented. Descriptive data on antiinfective drug shortages, including differences between manufacturer-estimated and actual times to shortage resolution, were collected over a one-year period via regular monitoring of the websites of ASHP and the Food and Drug Administration. Inventory data from one large hospital in the Midwest were collected in order to characterize realized shortages (i.e., those for which mitigation was required). During the study period, there were 47 transient shortages of antiinfective medications involving 381 unique products or formulations, of which 40% (n = 19) were emergent shortages. Generic-only and brand-only medications accounted for 53% (n = 25) and 21% (n = 10) of the evaluated shortages, respectively; the median shortage duration was 40 days (interquartile range [IQR], 22-91 days). The reasons for shortages most frequently cited by manufacturers were product or formulation discontinuation (21%), increased demand (12%), and raw material shortfalls (8%). Some shortages were resolved sooner than originally projected, but overall, actual shortage durations exceeded manufacturer-projected durations by a median of 17 days (IQR, 0-52.5 days). Ten realized shortages occurred at the hospital study site, compelling the antimicrobial stewardship team to recommend alternative therapies or restrict the use of drugs in short supply. The actual durations of evaluated antiinfective drug shortages during the study period were longer than the manufacturer-projected durations by a median of 17 days. Copyright © 2014 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Enteral feeding: drug/nutrient interaction.

PubMed

Lourenço, R

2001-04-01

Enteral nutrition support via a feeding tube is the first choice for artificial nutrition. Most patients also require simultaneous drug therapy, with the potential risk for drug-nutrient interactions which may become relevant in clinical practice. During enteral nutrition, drug-nutrient interactions are more likely to occur than in patients fed orally. However, there is a lack of awareness about its clinical significance, which should be recognised and prevented in order to optimise nutritional and pharmacological therapeutic goals of safety and efficacy. To raise the awareness of potential drug-nutrient interactions and influence on clinical outcomes. To identify factors that can promote drug-nutrient interactions and contribute to nutrition and/or therapeutic failure. To be aware of different types of drug-nutrient interactions. To understand complex underlying mechanisms responsible for drug-nutrient interactions. To learn basic rules for the administration of medications during tube-feeding. Copyright 2001 Harcourt Publishers Ltd.

A Drug Interactions Elective Course

PubMed Central

2009-01-01

Objectives To evaluate the impact of a drug interactions elective course on student knowledge and skills. Design A drug interactions elective which focused on assessment and application of drug interaction information and identification and management of commonly encountered drug interactions by therapeutic category was offered to third-year PharmD students. Students were expected to (1) determine whether a given interaction was clinically significant or required pharmacist intervention, and (2) make rational, scientifically sound, practical recommendations for management of drug interactions. Evaluation and Assessment Assessment included course evaluations, student self-assessments, and knowledge and skills assessments. Students who completed the course were more confident in their abilities relating to drug interactions than students who did not complete the course. Students who completed the course scored significantly better in all areas of the assessment compared to students who did not complete the course. Course evaluation results were also positive. Conclusion A course devoted to the identification and management of drug interactions improved PharmD students' knowledge and skills and could potentially improve the patient care they provide in the future. PMID:19657505

Drug-drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems.

PubMed

Kumar, Santosh; Rao, P S S; Earla, Ravindra; Kumar, Anil

2015-03-01

Substance abuse is a common problem among HIV-infected individuals. Importantly, addictions as well as moderate use of alcohol, smoking, or other illicit drugs have been identified as major reasons for non-adherence to antiretroviral therapy (ART) among HIV patients. The literature also suggests a decrease in the response to ART among HIV patients who use these substances, leading to failure to achieve optimal virological response and increased disease progression. This review discusses the challenges with adherence to ART as well as observed drug interactions and known toxicities with major drugs of abuse, such as alcohol, smoking, methamphetamine, cocaine, marijuana, and opioids. The lack of adherence and drug interactions potentially lead to decreased efficacy of ART drugs and increased ART, and drugs of abuse-mediated toxicity. As CYP is the common pathway in metabolizing both ART and drugs of abuse, we discuss the possible involvement of CYP pathways in such drug interactions. We acknowledge that further studies focusing on common metabolic pathways involving CYP and advance research in this area would help to potentially develop novel/alternate interventions and drug dose/regimen adjustments to improve medication outcomes in HIV patients who consume drugs of abuse.

Drug-Food Interactions

MedlinePlus

... article was contributed by: familydoctor.org editorial staff Categories: Drugs, Procedures & Devices, Prescription Medicines, Your Health ResourcesTags: adverse reactions, Food-Drug Interactions, patient education, patient information September 1, ...

How drug-like are 'ugly' drugs: do drug-likeness metrics predict ADME behaviour in humans?

PubMed

Ritchie, Timothy J; Macdonald, Simon J F

2014-04-01

Using a published drug-likeness score based on the calculated physicochemical properties of marketed oral drugs (quantitative estimate of drug-likeness, QED) and published human data, high-scoring and low-scoring drugs were compared to determine how well the score correlated with their actual pharmaceutical and pharmacokinetic (PK) profiles in humans. Drugs with high QED scores exhibit higher absorption and bioavailability, are administered at lower doses and have fewer drug-drug interaction warnings, P-glycoprotein interactions and absorption issues due to a food effect. By contrast, the high-scoring drugs exhibit similar behaviour to low-scoring drugs with respect to free fraction in plasma, extent of gut-wall metabolism, first-pass hepatic extraction, elimination half-life, clearance, volume of distribution and frequency of dosing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Drug-nutrient interactions in transplant recipients.

PubMed

Chan, L N

2001-01-01

Drug-nutrient interaction refers to an alteration of kinetics or dynamics of a drug or a nutritional element, or a compromise in nutritional status as a result of the addition of a drug. The potentials for drug-nutrient interaction increase with the number of drugs taken by the patient. Organ transplant recipients are therefore at high risk for drug-nutrient interactions because multiple medications are used to manage graft rejection, opportunistic infections, and other associated complications. Unrecognized or unmanaged drug-nutrient interactions in this patient population can have an adverse impact on their outcomes. This paper reviews the importance of recognizing drug-nutrient interaction when using cyclosporine-based regimens.

Participatory design for drug-drug interaction alerts.

PubMed

Luna, Daniel; Otero, Carlos; Almerares, Alfredo; Stanziola, Enrique; Risk, Marcelo; González Bernaldo de Quirós, Fernán

2015-01-01

The utilization of decision support systems, in the point of care, to alert drug-drug interactions has been shown to improve quality of care. Still, the use of these systems has not been as expected, it is believed, because of the difficulties in their knowledge databases; errors in the generation of the alerts and the lack of a suitable design. This study expands on the development of alerts using participatory design techniques based on user centered design process. This work was undertaken in three stages (inquiry, participatory design and usability testing) it showed that the use of these techniques improves satisfaction, effectiveness and efficiency in an alert system for drug-drug interactions, a fact that was evident in specific situations such as the decrease of errors to meet the specified task, the time, the workload optimization and users overall satisfaction in the system.

Clinical nutrition and drug interactions

PubMed Central

Ekincioğlu, Aygin Bayraktar; Demirkan, Kutay

2013-01-01

A drug’s plasma level, pharmacological effects or side effects, elimination, physicochemical properties or stability could be changed by interactions of drug-drug or drug-nutrition products in patients who receive enteral or parenteral nutritional support. As a result, patients might experience ineffective outcomes or unexpected effects of therapy (such as drug toxicity, embolism). Stability or incompatibility problems between parenteral nutrition admixtures and drugs might lead to alterations in expected therapeutic responses from drug and/or parenteral nutrition, occlusion in venous catheter or symptoms or mortality due to infusion of composed particles. Compatibilities between parenteral nutrition and drugs are not always guaranteed in clinical practice. Although the list of compatibility or incompatibilities of drugs are published for the use of clinicians in their practices, factors such as composition of parenteral nutrition admixture, drug concentration, contact time in catheter, temperature of the environment and exposure to light could change the status of compatibilities between drugs and nutrition admixtures. There could be substantial clinical changes occurring in the patient’s nutritional status and pharmacological effects of drugs due to interactions between enteral nutrition and drugs. Drug toxicity and ineffective nutritional support might occur as a result of those predictable interactions. Although administration of drugs via feeding tube is a complex and problematic route for drug usage, it is possible to minimise the risk of tube occlusion, decreased effects of drug and drug toxicity by using an appropriate technique. Therefore, it is important to consider pharmacological dosage forms of drugs while administering drugs via a feeding tube. In conclusion, since the pharmacists are well-experienced and more knowledgeable professionals in drugs and drug usage compared to other healthcare providers, it is suggested that provision of information

Discovery and explanation of drug-drug interactions via text mining.

PubMed

Percha, Bethany; Garten, Yael; Altman, Russ B

2012-01-01

Drug-drug interactions (DDIs) can occur when two drugs interact with the same gene product. Most available information about gene-drug relationships is contained within the scientific literature, but is dispersed over a large number of publications, with thousands of new publications added each month. In this setting, automated text mining is an attractive solution for identifying gene-drug relationships and aggregating them to predict novel DDIs. In previous work, we have shown that gene-drug interactions can be extracted from Medline abstracts with high fidelity - we extract not only the genes and drugs, but also the type of relationship expressed in individual sentences (e.g. metabolize, inhibit, activate and many others). We normalize these relationships and map them to a standardized ontology. In this work, we hypothesize that we can combine these normalized gene-drug relationships, drawn from a very broad and diverse literature, to infer DDIs. Using a training set of established DDIs, we have trained a random forest classifier to score potential DDIs based on the features of the normalized assertions extracted from the literature that relate two drugs to a gene product. The classifier recognizes the combinations of relationships, drugs and genes that are most associated with the gold standard DDIs, correctly identifying 79.8% of assertions relating interacting drug pairs and 78.9% of assertions relating noninteracting drug pairs. Most significantly, because our text processing method captures the semantics of individual gene-drug relationships, we can construct mechanistic pharmacological explanations for the newly-proposed DDIs. We show how our classifier can be used to explain known DDIs and to uncover new DDIs that have not yet been reported.

Herb-drug interactions.

PubMed

Fugh-Berman, A

2000-01-08

Concurrent use of herbs may mimic, magnify, or oppose the effect of drugs. Plausible cases of herb-drug interactions include: bleeding when warfarin is combined with ginkgo (Ginkgo biloba), garlic (Allium sativum), dong quai (Angelica sinensis), or danshen (Salvia miltiorrhiza); mild serotonin syndrome in patients who mix St John's wort (Hypericum perforatum) with serotonin-reuptake inhibitors; decreased bioavailability of digoxin, theophylline, cyclosporin, and phenprocoumon when these drugs are combined with St John's wort; induction of mania in depressed patients who mix antidepressants and Panax ginseng; exacerbation of extrapyramidal effects with neuroleptic drugs and betel nut (Areca catechu); increased risk of hypertension when tricyclic antidepressants are combined with yohimbine (Pausinystalia yohimbe); potentiation of oral and topical corticosteroids by liquorice (Glycyrrhiza glabra); decreased blood concentrations of prednisolone when taken with the Chinese herbal product xaio chai hu tang (sho-salko-to); and decreased concentrations of phenytoin when combined with the Ayurvedic syrup shankhapushpi. Anthranoid-containing plants (including senna [Cassia senna] and cascara [Rhamnus purshiana]) and soluble fibres (including guar gum and psyllium) can decrease the absorption of drugs. Many reports of herb-drug interactions are sketchy and lack laboratory analysis of suspect preparations. Health-care practitioners should caution patients against mixing herbs and pharmaceutical drugs.

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®

ABC multidrug transporters: target for modulation of drug pharmacokinetics and drug-drug interactions.

PubMed

Marquez, Béatrice; Van Bambeke, Françoise

2011-05-01

Nine proteins of the ABC superfamily (P-glycoprotein, 7 MRPs and BCRP) are involved in multidrug transport. Being localised at the surface of endothelial or epithelial cells, they expel drugs back to the external medium (if located at the apical side [P-glycoprotein, BCRP, MRP2, MRP4 in the kidney]) or to the blood (if located at the basolateral side [MRP1, MRP3, MRP4, MRP5]), modulating thereby their absorption, distribution, and elimination. In the CNS, most transporters are oriented to expel drugs to the blood. Transporters also cooperate with Phase I/Phase II metabolism enzymes by eliminating drug metabolites. Their major features are (i) their capacity to recognize drugs belonging to unrelated pharmacological classes, and (ii) their redundancy, a single molecule being possibly substrate for different transporters. This ensures an efficient protection of the body against invasion by xenobiotics. Competition for transport is now characterized as a mechanism of interaction between co-administered drugs, one molecule limiting the transport of the other, potentially affecting bioavailability, distribution, and/or elimination. Again, this mechanism reinforces drug interactions mediated by cytochrome P450 inhibition, as many substrates of P-glycoprotein and CYP3A4 are common. Induction of the expression of genes coding for MDR transporters is another mechanism of drug interaction, which could affect all drug substrates of the up-regulated transporter. Overexpression of MDR transporters confers resistance to anticancer agents and other therapies. All together, these data justify why studying drug active transport should be part of the evaluation of new drugs, as recently recommended by the FDA.

Indolealkylamines: biotransformations and potential drug-drug interactions.

PubMed

Yu, Ai-Ming

2008-06-01

Indolealkylamine (IAA) drugs are 5-hydroxytryptamine (5-HT or serotonin) analogs that mainly act on the serotonin system. Some IAAs are clinically utilized for antimigraine therapy, whereas other substances are notable as drugs of abuse. In the clinical evaluation of antimigraine triptan drugs, studies on their biotransformations and pharmacokinetics would facilitate the understanding and prevention of unwanted drug-drug interactions (DDIs). A stable, principal metabolite of an IAA drug of abuse could serve as a useful biomarker in assessing intoxication of the IAA substance. Studies on the metabolism of IAA drugs of abuse including lysergic acid amides, tryptamine derivatives and beta-carbolines are therefore emerging. An important role for polymorphic cytochrome P450 2D6 (CYP2D6) in the metabolism of IAA drugs of abuse has been revealed by recent studies, suggesting that variations in IAA metabolism, pharmaco- or toxicokinetics and dynamics can arise from distinct CYP2D6 status, and CYP2D6 polymorphism may represent an additional risk factor in the use of these IAA drugs. Furthermore, DDIs with IAA agents could occur additively at the pharmaco/toxicokinetic and dynamic levels, leading to severe or even fatal serotonin toxicity. In this review, the metabolism and potential DDIs of these therapeutic and abused IAA drugs are described.

Detecting drug-drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and non-steroidal anti-inflammatory drugs.

PubMed

van Puijenbroek, E P; Egberts, A C; Heerdink, E R; Leufkens, H G

2000-12-01

Drug-drug interactions are relatively rarely reported to spontaneous reporting systems (SRSs) for adverse drug reactions. For this reason, the traditional approach for analysing SRS has major limitations for the detection of drug-drug interactions. We developed a method that may enable signalling of these possible interactions, which are often not explicitly reported, utilising reports of adverse drug reactions in data sets of SRS. As an example, the influence of concomitant use of diuretics and non-steroidal anti-inflammatory drugs (NSAIDs) on symptoms indicating a decreased efficacy of diuretics was examined using reports received by the Netherlands Pharmacovigilance Foundation Lareb. Reports received between 1 January 1990 and 1 January 1999 of patients older than 50 years were included in the study. Cases were defined as reports with symptoms indicating a decreased efficacy of diuretics, non-cases as all other reports. Exposure categories were the use of NSAIDs or diuretics versus the use of neither of these drugs. The influence of the combined use of both drugs was examined using logistic regression analysis. The odds ratio of the statistical interaction term of the combined use of both drugs was increased [adjusted odds ratio 2.0, 95% confidence interval (CI) 1.1-3.7], which may indicate an enhanced effect of concomitant drug use. The findings illustrate that spontaneous reporting systems have a potential for signal detection and the analysis of possible drug-drug interactions. The method described may enable a more active approach in the detection of drug-drug interactions after marketing.

[Psychiatric polypharmacy: hazard through drug-drug-interaction and possibilities for prevention].

PubMed

Hahn, M; Braus, D F

2012-09-01

Psychiatric diseases and comorbidity have increased over the past years. Commonly used psychotropic drugs contain a high risk of drug interactions and adverse drug events (ADE). With a frequency of 10-12% psychotropic drugs are, among all pharmaceuticals, the most common cause of hospitalisation due to ADE. During a hospital stay the application of psychotropic drugs can also lead to adverse drug events--sometimes due to drug interactions. Currently, ADEs and drug interactions are the most frequent cause of death for in-patients (18% of all causes of death) with an overall mortality of 0.95%. As studies have shown, hospitals as well as insurers could save a considerable amount of resources by implementing a system with on-ward pharmacists, hereby reducing ADE and re-hospitalisation rates. In recent studies a large amount of current ADEs were rated as preventable. Patient impairment due to ADE is leading to an increase in liability cases with an expected 5% increase of compensation payments in 2011. To evaluate these ADE-related cases, a pharmaceutical assessment should be included in the expert trials, especially since a lack of awareness of medication errors is prevalent. When aiming towards a successful drug therapy, physicians must also consider that cheaper substances may often have an unfavourable drug interaction profile.

Similarity-based modeling in large-scale prediction of drug-drug interactions.

PubMed

Vilar, Santiago; Uriarte, Eugenio; Santana, Lourdes; Lorberbaum, Tal; Hripcsak, George; Friedman, Carol; Tatonetti, Nicholas P

2014-09-01

Drug-drug interactions (DDIs) are a major cause of adverse drug effects and a public health concern, as they increase hospital care expenses and reduce patients' quality of life. DDI detection is, therefore, an important objective in patient safety, one whose pursuit affects drug development and pharmacovigilance. In this article, we describe a protocol applicable on a large scale to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in established DDIs. The method integrates a reference standard database of known DDIs with drug similarity information extracted from different sources, such as 2D and 3D molecular structure, interaction profile, target and side-effect similarities. The method is interpretable in that it generates drug interaction candidates that are traceable to pharmacological or clinical effects. We describe a protocol with applications in patient safety and preclinical toxicity screening. The time frame to implement this protocol is 5-7 h, with additional time potentially necessary, depending on the complexity of the reference standard DDI database and the similarity measures implemented.

Biophysical interactions with model lipid membranes: applications in drug discovery and drug delivery

PubMed Central

Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod

2009-01-01

The transport of drugs or drug delivery systems across the cell membrane is a complex biological process, often difficult to understand because of its dynamic nature. In this regard, model lipid membranes, which mimic many aspects of cell-membrane lipids, have been very useful in helping investigators to discern the roles of lipids in cellular interactions. One can use drug-lipid interactions to predict pharmacokinetic properties of drugs, such as their transport, biodistribution, accumulation, and hence efficacy. These interactions can also be used to study the mechanisms of transport, based on the structure and hydrophilicity/hydrophobicity of drug molecules. In recent years, model lipid membranes have also been explored to understand their mechanisms of interactions with peptides, polymers, and nanocarriers. These interaction studies can be used to design and develop efficient drug delivery systems. Changes in the lipid composition of cells and tissue in certain disease conditions may alter biophysical interactions, which could be explored to develop target-specific drugs and drug delivery systems. In this review, we discuss different model membranes, drug-lipid interactions and their significance, studies of model membrane interactions with nanocarriers, and how biophysical interaction studies with lipid model membranes could play an important role in drug discovery and drug delivery. PMID:19432455

CLINICALLY SIGNIFICANT PSYCHOTROPIC DRUG-DRUG INTERACTIONS IN THE PRIMARY CARE SETTING

PubMed Central

English, Brett A.; Dortch, Marcus; Ereshefsky, Larry; Jhee, Stanford

2014-01-01

In recent years, the growing numbers of patients seeking care for a wide range of psychiatric illnesses in the primary care setting has resulted in an increase in the number of psychotropic medications prescribed. Along with the increased utilization of psychotropic medications, considerable variability is noted in the prescribing patterns of primary care providers and psychiatrists. Because psychiatric patients also suffer from a number of additional medical comorbidities, the increased utilization of psychotropic medications presents an elevated risk of clinically significant drug interactions in these patients. While life-threatening drug interactions are rare, clinically significant drug interactions impacting drug response or appearance of serious adverse drug reactions have been documented and can impact long-term outcomes. Additionally, the impact of genetic variability on the psychotropic drug’s pharmacodynamics and/or pharmacokinetics may further complicate drug therapy. Increased awareness of clinically relevant psychotropic drug interactions can aid clinicians to achieve optimal therapeutic outcomes in patients in the primary care setting. PMID:22707017

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.

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.

QSAR Modeling and Prediction of Drug-Drug Interactions.

PubMed

Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

2016-02-01

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Potential Drug-Drug Interactions among Patients prescriptions collected from Medicine Out-patient Setting.

PubMed

Farooqui, Riffat; Hoor, Talea; Karim, Nasim; Muneer, Mehtab

2018-01-01

To identify and evaluate the frequency, severity, mechanism and common pairs of drug-drug interactions (DDIs) in prescriptions by consultants in medicine outpatient department. This cross sectional descriptive study was done by Pharmacology department of Bahria University Medical & Dental College (BUMDC) in medicine outpatient department (OPD) of a private hospital in Karachi from December 2015 to January 2016. A total of 220 prescriptions written by consultants were collected. Medications given with patient's diagnosis were recorded. Drugs were analyzed for interactions by utilizing Medscape drug interaction checker, drugs.com checker and stockley`s drug interactions index. Two hundred eleven prescriptions were selected while remaining were excluded from the study because of unavailability of the prescribed drugs in the drug interaction checkers. In 211 prescriptions, two common diagnoses were diabetes mellitus (28.43%) and hypertension (27.96%). A total of 978 medications were given. Mean number of medications per prescription was 4.6. A total of 369 drug-drug interactions were identified in 211 prescriptions (175%). They were serious 4.33%, significant 66.12% and minor 29.53%. Pharmacokinetic and pharmacodynamic interactions were 37.94% and 51.21% respectively while 10.84% had unknown mechanism. Number wise common pairs of DDIs were Omeprazole-Losartan (S), Gabapentine- Acetaminophen (M), Losartan-Diclofenac (S). The frequency of DDIs is found to be too high in prescriptions of consultants from medicine OPD of a private hospital in Karachi. Significant drug-drug interactions were more and mostly caused by Pharmacodynamic mechanism. Number wise evaluation showed three common pairs of drugs involved in interactions.

Potential Drug-Drug Interactions among Patients prescriptions collected from Medicine Out-patient Setting

PubMed Central

Farooqui, Riffat; Hoor, Talea; Karim, Nasim; Muneer, Mehtab

2018-01-01

Objective: To identify and evaluate the frequency, severity, mechanism and common pairs of drug-drug interactions (DDIs) in prescriptions by consultants in medicine outpatient department. Methods: This cross sectional descriptive study was done by Pharmacology department of Bahria University Medical & Dental College (BUMDC) in medicine outpatient department (OPD) of a private hospital in Karachi from December 2015 to January 2016. A total of 220 prescriptions written by consultants were collected. Medications given with patient's diagnosis were recorded. Drugs were analyzed for interactions by utilizing Medscape drug interaction checker, drugs.com checker and stockley`s drug interactions index. Two hundred eleven prescriptions were selected while remaining were excluded from the study because of unavailability of the prescribed drugs in the drug interaction checkers. Results: In 211 prescriptions, two common diagnoses were diabetes mellitus (28.43%) and hypertension (27.96%). A total of 978 medications were given. Mean number of medications per prescription was 4.6. A total of 369 drug-drug interactions were identified in 211 prescriptions (175%). They were serious 4.33%, significant 66.12% and minor 29.53%. Pharmacokinetic and pharmacodynamic interactions were 37.94% and 51.21% respectively while 10.84% had unknown mechanism. Number wise common pairs of DDIs were Omeprazole-Losartan (S), Gabapentine- Acetaminophen (M), Losartan-Diclofenac (S). Conclusion: The frequency of DDIs is found to be too high in prescriptions of consultants from medicine OPD of a private hospital in Karachi. Significant drug-drug interactions were more and mostly caused by Pharmacodynamic mechanism. Number wise evaluation showed three common pairs of drugs involved in interactions. PMID:29643896

An approach to evaluating drug-nutrient interactions.

PubMed

Santos, Cristina A; Boullata, Joseph I

2005-12-01

Although the significance of interactions between drugs is widely appreciated, little attention has been given to interactions between drugs and nutrients. Pharmacists are challenged to remember documented interactions involving available drugs, and they face the possibility that each newly approved therapeutic agent may be involved not only in unrecognized drug-drug interactions but in drug-nutrient interactions as well. A more consistent approach to evaluating drug-nutrient interactions is needed. The approach must be systematic in order to assess the influence of nutritional status, food, or specific nutrients on a drug's pharmacokinetics and pharmacodynamics, as well as the influence of a drug on overall nutritional status or on the status of a specific nutrient. We provide such a process, using several recently approved drugs as working examples. Risk factors and clinical relevance are described, with distinctions made between documented and potential interactions. Application of this process by the pharmacist to any drug will help increase their expertise. Furthermore, full consideration by pharmacists of all possible interactions of the drug regimens used in practice can allow for improved patient care.

Food and drug interactions: a general review.

PubMed

Ötles, Semih; Senturk, Ahmet

2014-01-01

Although it is well known and identified that drug-drug interactions exist, the recognition of importance of food and drug interactions to practice has been growing much slower. On the other hand, drug-food/nutrient interactions continue to grow with the common use of medications. Beside the awareness of this type of interactions, food-drug interaction studies are critical to evaluate appropriate dosing, timing, and formulation of new drug candidates. Drug-food interactions take place mechanistically due to altered intestinal transport and metabolism, or systemic distribution, metabolism and excretion. In addition, some people have greater risk of food and drug interactions who have a poor diet, have serious health problems, childrens and pregnant women. In this article, basic informations about importance, classifications, transporters and enzymes of drug and nutrient interaction are given and some specific examples of both drug and nutrients and influences on each other are included.

High-Throughput Cytochrome P450 Cocktail Inhibition Assay for Assessing Drug-Drug and Drug-Botanical Interactions

PubMed Central

Li, Guannan; Huang, Ke; Nikolic, Dejan

2015-01-01

Detection of drug-drug interactions is essential during the early stages of drug discovery and development, and the understanding of drug-botanical interactions is important for the safe use of botanical dietary supplements. Among the different forms of drug interactions that are known, inhibition of cytochrome P450 (P450) enzymes is the most common cause of drug-drug or drug-botanical interactions. Therefore, a rapid and comprehensive mass spectrometry–based in vitro high-throughput P450 cocktail inhibition assay was developed that uses 10 substrates simultaneously against nine CYP isoforms. Including probe substrates for CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and two probes targeting different binding sites of CYP3A4/5, this cocktail simultaneously assesses at least as many P450 enzymes as previous assays while remaining among the fastest due to short incubation times and rapid analysis using ultrahigh pressure liquid chromatography–tandem mass spectrometry. The method was validated using known inhibitors of each P450 enzyme and then shown to be useful not only for single-compound testing but also for the evaluation of potential drug-botanical interactions using the botanical dietary supplement licorice (Glycyrrhiza glabra) as an example. PMID:26285764

Drug Interactions: What You Should Know

MedlinePlus

... driving a car or operating machinery dangerous. Drug-food/beverage interactions result from drugs reacting with foods or ... it with other drugs? Should I avoid certain foods, beverages or other products? What are possible drug interaction ...

Drug-nutrient interactions: a review.

PubMed

Maka, D A; Murphy, L K

2000-11-01

Concurrent administration of medications and nutrients can lead to interactions that change the absorption or metabolism of the medication or nutrient. Some of these interactions have little or no impact on the patient while others may be fatal. The objective of this article is to review the mechanisms of various drug-nutrient interactions. Topics to be discussed include specific populations at risk of interactions, nutrients that have a positive and negative effect on drug absorption, nutrients that result in alterations of drug metabolism, and a variety of pharmacologic interactions of medications with nutrients. It is vital that healthcare providers are familiar with drug-nutrient interactions and continue to educate themselves and their patients to optimize the effectiveness and minimize the toxicities of medications.

Genetic determinants of drug responsiveness and drug interactions.

PubMed

Caraco, Y

1998-10-01

Six cytochrome P450 enzymes mediate the oxidative metabolism of most drugs in common use: CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4. These enzymes have selective substrate specificity, and their activity is characterized by marked interindividual variation. Some of these systems (CYP2C19, CYP2D6) are polymorphically distributed; thus, a subset of the population may be genetically deficient in enzyme activity. Phenotyping procedures designed to identify subjects with impaired metabolism who may be at increased risk for drug toxicity have been developed and validated. This has been supplemented in recent years by the availability of genetic analysis and the identification of specific alleles that are associated with altered (i.e., reduced, deficient, or increased) enzyme activity. The potential of genotyping to predict pharmacodynamics holds great promise for the future because it does not involve the administration of exogenous compound and is not confounded by drug therapy. Drug interactions caused by the inhibition or induction of oxidative drug metabolism may be of great clinical importance because they may result in drug toxicity or therapeutic failure. Further understanding of cytochrome P450 complexity may allow, through a combined in vitro-in vivo approach, the reliable prediction and possible prevention of deleterious drug interactions.

Common drug-drug interactions in antifungal treatments for superficial fungal infections.

PubMed

Gupta, Aditya K; Versteeg, Sarah G; Shear, Neil H

2018-04-01

Antifungal agents can be co-administered alongside several other medications for a variety of reasons such as the presence of comorbidities. Pharmacodynamic interactions such as synergistic and antagonistic interactions could be the result of co-administered medications. Pharmacokinetic interactions could also transpire through the inhibition of metabolizing enzymes and drug transport systems, altering the absorption, metabolism and excretion of co-administered medications. Both pharmacodynamic and pharmacokinetic interactions can result in hospitalization due to serious adverse effects associated with antifungal agents, lower therapeutic doses required to achieve desired antifungal activity, and prevent antifungal resistance. Areas covered: The objective of this review is to summarize pharmacodynamic and pharmacokinetic interactions associated with common antifungal agents used to treat superficial fungal infections. Pharmacodynamic and pharmacokinetic interactions that impact the therapeutic effects of antifungal agents and drugs that are influenced by the presence of antifungal agents was the context to which these antifungal agents were addressed. Expert opinion: The potential for drug-drug interactions is minimal for topical antifungals as opposed to oral antifungals as they have minimal exposure to other co-administered medications. Developing non-lipophilic antifungals that have unique metabolizing pathways and are topical applied are suggested properties that could help limit drug-drug interactions associated with future treatments.

Possible drug-drug interaction in dogs and cats resulted from alteration in drug metabolism: A mini review.

PubMed

Sasaki, Kazuaki; Shimoda, Minoru

2015-05-01

Pharmacokinetic drug-drug interactions (in particular at metabolism) may result in fatal adverse effects in some cases. This basic information, therefore, is needed for drug therapy even in veterinary medicine, as multidrug therapy is not rare in canines and felines. The aim of this review was focused on possible drug-drug interactions in dogs and cats. The interaction includes enzyme induction by phenobarbital, enzyme inhibition by ketoconazole and fluoroquinolones, and down-regulation of enzymes by dexamethasone. A final conclusion based upon the available literatures and author's experience is given at the end of the review.

Nuclear Receptors in Drug Metabolism, Drug Response and Drug Interactions

PubMed Central

Prakash, Chandra; Zuniga, Baltazar; Song, Chung Seog; Jiang, Shoulei; Cropper, Jodie; Park, Sulgi; Chatterjee, Bandana

2016-01-01

Orally delivered small-molecule therapeutics are metabolized in the liver and intestine by phase I and phase II drug-metabolizing enzymes (DMEs), and transport proteins coordinate drug influx (phase 0) and drug/drug-metabolite efflux (phase III). Genes involved in drug metabolism and disposition are induced by xenobiotic-activated nuclear receptors (NRs), i.e. PXR (pregnane X receptor) and CAR (constitutive androstane receptor), and by the 1α, 25-dihydroxy vitamin D3-activated vitamin D receptor (VDR), due to transactivation of xenobiotic-response elements (XREs) present in phase 0-III genes. Additional NRs, like HNF4-α, FXR, LXR-α play important roles in drug metabolism in certain settings, such as in relation to cholesterol and bile acid metabolism. The phase I enzymes CYP3A4/A5, CYP2D6, CYP2B6, CYP2C9, CYP2C19, CYP1A2, CYP2C8, CYP2A6, CYP2J2, and CYP2E1 metabolize >90% of all prescription drugs, and phase II conjugation of hydrophilic functional groups (with/without phase I modification) facilitates drug clearance. The conjugation step is mediated by broad-specificity transferases like UGTs, SULTs, GSTs. This review delves into our current understanding of PXR/CAR/VDR-mediated regulation of DME and transporter expression, as well as effects of single nucleotide polymorphism (SNP) and epigenome (specified by promoter methylation, histone modification, microRNAs, long non coding RNAs) on the expression of PXR/CAR/VDR and phase 0-III mediators, and their impacts on variable drug response. Therapeutic agents that target epigenetic regulation and the molecular basis and consequences (overdosing, underdosing, or beneficial outcome) of drug-drug/drug-food/drug-herb interactions are also discussed. Precision medicine requires understanding of a drug’s impact on DME and transporter activity and their NR-regulated expression in order to achieve optimal drug efficacy without adverse drug reactions. In future drug screening, new tools such as humanized mouse models and

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.

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.

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

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

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

Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile.

PubMed

van Laarhoven, Twan; Marchiori, Elena

2013-01-01

In silico discovery of interactions between drug compounds and target proteins is of core importance for improving the efficiency of the laborious and costly experimental determination of drug-target interaction. Drug-target interaction data are available for many classes of pharmaceutically useful target proteins including enzymes, ion channels, GPCRs and nuclear receptors. However, current drug-target interaction databases contain a small number of drug-target pairs which are experimentally validated interactions. In particular, for some drug compounds (or targets) there is no available interaction. This motivates the need for developing methods that predict interacting pairs with high accuracy also for these 'new' drug compounds (or targets). We show that a simple weighted nearest neighbor procedure is highly effective for this task. We integrate this procedure into a recent machine learning method for drug-target interaction we developed in previous work. Results of experiments indicate that the resulting method predicts true interactions with high accuracy also for new drug compounds and achieves results comparable or better than those of recent state-of-the-art algorithms. Software is publicly available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2013/.

SFINX-a drug-drug interaction database designed for clinical decision support systems.

PubMed

Böttiger, Ylva; Laine, Kari; Andersson, Marine L; Korhonen, Tuomas; Molin, Björn; Ovesjö, Marie-Louise; Tirkkonen, Tuire; Rane, Anders; Gustafsson, Lars L; Eiermann, Birgit

2009-06-01

The aim was to develop a drug-drug interaction database (SFINX) to be integrated into decision support systems or to be used in website solutions for clinical evaluation of interactions. Key elements such as substance properties and names, drug formulations, text structures and references were defined before development of the database. Standard operating procedures for literature searches, text writing rules and a classification system for clinical relevance and documentation level were determined. ATC codes, CAS numbers and country-specific codes for substances were identified and quality assured to ensure safe integration of SFINX into other data systems. Much effort was put into giving short and practical advice regarding clinically relevant drug-drug interactions. SFINX includes over 8,000 interaction pairs and is integrated into Swedish and Finnish computerised decision support systems. Over 31,000 physicians and pharmacists are receiving interaction alerts through SFINX. User feedback is collected for continuous improvement of the content. SFINX is a potentially valuable tool delivering instant information on drug interactions during prescribing and dispensing.

HIV Treatment: What is a Drug Interaction?

MedlinePlus

... more) drugs or between a drug and a food or beverage. Taking a drug while having certain medical conditions ... interaction : A reaction between a drug and a food or beverage. Drug-condition interaction : A reaction that occurs when ...

Industry Perspective on Contemporary Protein-Binding Methodologies: Considerations for Regulatory Drug-Drug Interaction and Related Guidelines on Highly Bound Drugs.

PubMed

Di, Li; Breen, Christopher; Chambers, Rob; Eckley, Sean T; Fricke, Robert; Ghosh, Avijit; Harradine, Paul; Kalvass, J Cory; Ho, Stacy; Lee, Caroline A; Marathe, Punit; Perkins, Everett J; Qian, Mark; Tse, Susanna; Yan, Zhengyin; Zamek-Gliszczynski, Maciej J

2017-12-01

Regulatory agencies have recently issued drug-drug interaction guidelines, which require determination of plasma protein binding (PPB). To err on the conservative side, the agencies recommend that a 0.01 lower limit of fraction unbound (f u ) be used for highly bound compounds (>99%), irrespective of the actual measured values. While this may avoid false negatives, the recommendation would likely result in a high rate of false positive predictions, resulting in unnecessary clinical studies and more stringent inclusion/exclusion criteria, which may add cost and time in delivery of new medicines to patients. In this perspective, we provide a review of current approaches to measure PPB, and important determinants in enabling the accuracy and precision in these measurements. The ability to measure f u is further illustrated by a cross-company data comparison of PPB for warfarin and itraconazole, demonstrating good concordance of the measured f u values. The data indicate that f u values of ≤0.01 may be determined accurately across laboratories when appropriate methods are used. These data, along with numerous other examples presented in the literature, support the use of experimentally measured f u values for drug-drug interaction predictions, rather than using the arbitrary cutoff value of 0.01 as recommended in current regulatory guidelines. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Interactions between antihypertensive drugs and food.

PubMed

Jáuregui-Garrido, B; Jáuregui-Lobera, I

2012-01-01

A drug interaction is defined as any alteration, pharmacokinetics and/or pharmacodynamics, produced by different substances, other drug treatments, dietary factors and habits such as drinking and smoking. These interactions can affect the antihypertensive drugs, altering their therapeutic efficacy and causing toxic effects. The aim of this study was to conduct a review of available data about interactions between antihypertensive agents and food. The purpose of this review was to report an update of main findings with respect to the interactions between food and antihypertensive drugs by way of a search conducted in PubMed, which yielded a total of 236 articles initially. After excluding different articles, which were not focusing on the specific objective, the main results refer to interactions between antihypertensive drugs and food (in general) as well as between antihypertensive agents and grapefruit juice. Food may affect the bioavailability of antihypertensive drugs and this should be carefully considered. Advising patients to remove the grapefruit juice from their diet when treatment with these drugs seems to be the best recommendation. Given these interactions and the associated potential adverse effects the anamnesis must include detailed information about the specific eating habits of the patients.

Important drug-nutrient interactions in the elderly.

PubMed

Thomas, J A; Burns, R A

1998-09-01

Several drug-nutrient interactions can occur, but their prevalence may be accentuated in the elderly. Geriatric patients may experience age-related changes in the pharmacokinetics of a drug-absorption, distribution, metabolism and excretion. When drug-nutrient interactions occur, they usually affect absorptive processes more frequently. Specific transporter systems facilitate the absorption of many drugs. Little is known about how these transporter systems are affected by aging. Co-existing disease states in the elderly may exaggerate the action of a drug and represent a confounding factor in drug-nutrient interactions. While several different drug-nutrient interactions are important in the elderly, those affecting the cardiovascular system warrant special attention.

Interactions between antiarrhythmic drugs and food.

PubMed

Jáuregui-Garrido, B; Jáuregui-Lobera, I

2012-01-01

A drug interaction is defined as any alteration, pharmacokinetics and/or pharmacodynamics, produced by different substances, other drug treatments, dietary factors and habits such as drinking and smoking. These interactions can affect the antiarrhythmic drugs, altering their therapeutic efficacy and adverse effects. The aim of this study was to conduct a review of available data about interactions between antiarrhythmic drugs and food. The purpose of this review was to report an update of the existing literature data on the main findings with respect to food and antiarrhythmic drugs interactions by means of a search conducted in PubMed, which yielded a total of 250 articles initially. After excluding different articles which were not focusing on the specific objective, the main results refer to interactions among antiarrhythmic drugs and food in general, grapefruit juice, and others like fibre or medicinal plants. Food may affect the bioavailability of antiarrhythmic drugs and in some specific cases (dairy products, rich-in-protein diets, grapefruit juice), this should be carefully considered. The best recommendation seems to advise patients to remove the grapefruit juice from their diet when treatment with these drugs. Fibre should be separated from taking these drugs and regarding medicinal plants and given their increased use, the anamnesis must include information about its use, the reason for that use and what types of plants are used, all in order to give the corresponding recommendations.

Drugs and Diseases Interacting with Cigarette Smoking in US Prescription Drug Labelling.

PubMed

Li, Haibo; Shi, Qiang

2015-05-01

The US Food and Drug Administration (FDA) draft guidance for industry on drug interaction studies recommends, but does not mandate, that both cigarette smokers and non-smokers can be used to study drug metabolism in clinical trials, and that important results related to smoking should be included in drug labelling to guide medication usage. This study aimed to provide a comprehensive review of drugs or diseases interacting with smoking, as presented in all US drug labelling. The 62,857 drug labels deposited in the FDA Online Label Repository were searched using the keywords 'smoke', 'smoker(s)', 'smoking', 'tobacco' and 'cigarette(s)' on 19 June 2014. The resultant records were refined to include only human prescription drug labelling, for manual examination. For 188 single-active-ingredient drugs and 36 multiple-active-ingredient drugs, the labelling was found to contain smoking-related information. The pharmacokinetics of 29 and 21 single-active-ingredient drugs were affected and unaffected, respectively, by smoking. For the remaining drugs, the provided information related to smoking affecting efficacy, safety or diseases but not pharmacokinetics. Depending on the nature of specific drugs, the perturbation in pharmacokinetic parameters in smokers ranged from 13 to 500%, in comparison with non-smokers. Dosage modifications in smokers are necessary for four drugs and may be necessary for six drugs, but are unnecessary for seven drugs although the pharmacokinetic parameters of four of them are affected by smoking. Cigarette smoking is a risk factor for 16 types of diseases or adverse drug reactions. For one single-active-ingredient contraceptive drug and 10 multiple-active-ingredient contraceptive drugs, a black box warning (the FDA's strongest safety warning) is included in the labelling for increased risks of heart attacks and strokes in female smokers, and "women are strongly advised not to smoke" when using these drugs. This study presents the first

Deep-Learning-Based Drug-Target Interaction Prediction.

PubMed

Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

2017-04-07

Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

Drug-drug and food-drug pharmacokinetic interactions with new insulinotropic agents repaglinide and nateglinide.

PubMed

Scheen, André J

2007-01-01

This review describes the current knowledge on drug-drug and food-drug interactions with repaglinide and nateglinide. These two meglitinide derivatives, commonly called glinides, have been developed for improving insulin secretion of patients with type 2 diabetes mellitus. They are increasingly used either in monotherapy or in combination with other oral antihyperglycaemic agents for the treatment of type 2 diabetes. Compared with sulfonylureas, glinides have been shown to (i) provide a better control of postprandial hyperglycaemia, (ii) overcome some adverse effects, such as hypoglycaemia, and (iii) have a more favourable safety profile, especially in patients with renal failure. The meal-related timing of administration of glinides and the potential influence of food and meal composition on their bioavailability may be important. In addition, some food components (e.g. grapefruit juice) may cause pharmacokinetic interactions. Because glinides are metabolised via cytochrome P450 (CYP) 3A4 isoenzyme, they are indeed exposed to pharmacokinetic interactions. In addition to CYP3A4, repaglinide is metabolised via CYP2C8, while nateglinide metabolism also involves CYP2C9. Furthermore, both compounds and their metabolites may undergo specialised transport/uptake in the intestine, another source of pharmacokinetic interactions. Clinically relevant drug-drug interactions are those that occur when glinides are administered together with other glucose-lowering agents or compounds widely coadministered to diabetic patients (e.g. lipid-lowering agents), with drugs that are known to induce (risk of lower glinide plasma levels and thus of deterioration of glucose control) or inhibit (risk of higher glinide plasma levels leading to hypoglycaemia) CYP isoenzymes concerned in their metabolism, or with drugs that have a narrow efficacy : toxicity ratio. Pharmacokinetic interactions reported in the literature appear to be more frequent and more important with repaglinide than with

Drug-Drug Interactions and Diagnostics for Drug Users With HIV and HIV/HCV Coinfections: Introduction.

PubMed

Khalsa, Jag H; Talal, Andrew H; Morse, Gene

2017-03-01

Substance use and pharmacologic treatment of co-occurring infections such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV) are associated with many adverse consequences including pharmacokinetic and pharmacodynamic drug-drug interactions (DDIs). The National Institute on Drug Abuse sponsored a 2-day conference on DDIs at which clinicians/scientists from government, academia, and the pharmaceutical industry presented the most current research findings to formulate a comprehensive overview of DDIs. Specific topics discussed included drug metabolism; drug interactions between medications used in the treatment of HIV, HCV, and substance use disorders; intrahepatic concentrations and methods of assessment of drugs in liver disease of varying etiologies and degrees of impairment; and minimally invasive sampling techniques for the assessment of intrahepatic drug concentrations, viral replication, and changes in gene expression in response to treatment. Finally, the speakers identified research targets and priorities on DDIs. Areas of emphasis included development of diagnostic assays for drug concentration assessment in different organs, an enhanced understanding of factors responsible for alterations in drug metabolism and excretion, and establishment of clinical trials and work groups to study DDIs. Our long-term objective is to broaden investigation in the field of DDIs in substance users. © 2017, The American College of Clinical Pharmacology.

Clinical Drug-Drug Pharmacokinetic Interaction Potential of Sucralfate with Other Drugs: Review and Perspectives.

PubMed

Sulochana, Suresh P; Syed, Muzeeb; Chandrasekar, Devaraj V; Mullangi, Ramesh; Srinivas, Nuggehally R

2016-10-01

Sucralfate, a complex of aluminium hydroxide with sulfated sucrose, forms a strong gastrointestinal tract (GIT) mucosal barrier with excellent anti-ulcer property. Because sucralfate does not undergo any significant oral absorption, sucralfate resides in the GIT for a considerable length of time. The unabsorbed sucralfate may alter the pharmacokinetics of the oral drugs by impeding its absorption and reducing the oral bioavailability. Because of the increased use of sucralfate, it was important to provide a reappraisal of the published clinical drug-drug interaction studies of sucralfate with scores of drugs. This review covers several category of drugs such as non-steroidal anti-inflammatory drugs, fluoroquinolones, histamine H2-receptor blockers, macrolides, anti-fungals, anti-diabetics, salicylic acid derivatives, steroidal anti-inflammatory drugs and provides pharmacokinetic data summary along with study design, objectives and key remarks. While the loss of oral bioavailability was significant for the fluoroquinolone class, it generally varied for other classes of drugs, suggesting that impact of the co-administration of sucralfate is manageable in clinical situations. Given the technology advancement in formulation development, it may be in order feasible to develop appropriate formulation strategies to either avoid or minimize the absorption-related issues when co-administered with sucralfate. It is recommended that consideration of both in vitro and preclinical studies may be in order to gauge the level of interaction of a drug with sucralfate. Such data may aid in the development of appropriate strategies to navigate the co-administration of sucralfate with other drugs in this age of polypharmacy.

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.

Macrolide drug interactions: an update.

PubMed

Pai, M P; Graci, D M; Amsden, G W

2000-04-01

To describe the current drug interaction profiles for the commonly used macrolides in the US and Europe, and to comment on the clinical impact of these interactions. A MEDLINE search (1975-1998) was performed to identify all pertinent studies, review articles, and case reports. When appropriate information was not available in the literature, data were obtained from the product manufacturers. All available data were reviewed to provide an unbiased account of possible drug interactions. Data for some of the interactions were not available from the literature, but were available from abstracts or company-supplied materials. Although the data were not always explicit, the best attempt was made to deliver pertinent information that clinical practitioners would need to formulate practice opinions. When more in-depth information was supplied in the form of a review or study report, a thorough explanation of pertinent methodology was supplied. Several clinically significant drug interactions have been identified since the approval of erythromycin. These interactions usually were related to the inhibition of the cytochrome P450 enzyme systems, which are responsible for the metabolism of many drugs. The decreased metabolism by the macrolides has in some instances resulted in potentially severe adverse events. The development and marketing of newer macrolides are hoped to improve the drug interaction profile associated with this class. However, this has produced variable success. Some of the newer macrolides demonstrated an interaction profile similar to that of erythromycin; others have improved profiles. The most success in avoiding drug interactions related to the inhibition of cytochrome P450 has been through the development of the azalide subclass, of which azithromycin is the first and only to be marketed. Azithromycin has not been demonstrated to inhibit the cytochrome P450 system in studies using a human liver microsome model, and to date has produced none of the

Initial Drug Dissolution from Amorphous Solid Dispersions Controlled by Polymer Dissolution and Drug-Polymer Interaction.

PubMed

Chen, Yuejie; Wang, Shujing; Wang, Shan; Liu, Chengyu; Su, Ching; Hageman, Michael; Hussain, Munir; Haskell, Roy; Stefanski, Kevin; Qian, Feng

2016-10-01

To identify the key formulation factors controlling the initial drug and polymer dissolution rates from an amorphous solid dispersion (ASD). Ketoconazole (KTZ) ASDs using PVP, PVP-VA, HMPC, or HPMC-AS as polymeric matrix were prepared. For each drug-polymer system, two types of formulations with the same composition were prepared: 1. Spray dried dispersion (SDD) that is homogenous at molecular level, 2. Physical blend of SDD (80% drug loading) and pure polymer (SDD-PB) that is homogenous only at powder level. Flory-Huggins interaction parameters (χ) between KTZ and the four polymers were obtained by Flory-Huggins model fitting. Solution (13)C NMR and FT-IR were conducted to investigate the specific drug-polymer interaction in the solution and solid state, respectively. Intrinsic dissolution of both the drug and the polymer from ASDs were studied using a Higuchi style intrinsic dissolution apparatus. PXRD and confocal Raman microscopy were used to confirm the absence of drug crystallinity on the tablet surface before and after dissolution study. In solid state, KTZ is completely miscible with PVP, PVP-VA, or HPMC-AS, demonstrated by the negative χ values of -0.36, -0.46, -1.68, respectively; while is poorly miscible with HPMC shown by a positive χ value of 0.23. According to solution (13)C NMR and FT-IR studies, KTZ interacts with HPMC-AS strongly through H-bonding and dipole induced interaction; with PVPs and PVP-VA moderately through dipole-induced interactions; and with HPMC weakly without detectable attractive interaction. Furthermore, the "apparent" strength of drug-polymer interaction, measured by the extent of peak shift on NMR or FT-IR spectra, increases with the increasing number of interacting drug-polymer pairs. For ASDs with the presence of considerable drug-polymer interactions, such as KTZ/PVPs, KTZ/PVP-VA, or KTZ /HPMC-AS systems, drug released at the same rate as the polymer when intimate drug-polymer mixing was ensured (i.e., the SDD systems

Co-Prescription Trends in a Large Cohort of Subjects Predict Substantial Drug-Drug Interactions

PubMed Central

Sutherland, Jeffrey J.; Daly, Thomas M.; Liu, Xiong; Goldstein, Keith; Johnston, Joseph A.; Ryan, Timothy P.

2015-01-01

Pharmaceutical prescribing and drug-drug interaction data underlie recommendations on drug combinations that should be avoided or closely monitored by prescribers. Because the number of patients taking multiple medications is increasing, a comprehensive view of prescribing patterns in patients is important to better assess real world pharmaceutical response and evaluate the potential for multi-drug interactions. We obtained self-reported prescription data from NHANES surveys between 1999 and 2010, and confirm the previously reported finding of increasing drug use in the elderly. We studied co-prescription drug trends by focusing on the 2009-2010 survey, which contains prescription data on 690 drugs used by 10,537 subjects. We found that medication profiles were unique for individuals aged 65 years or more, with ≥98 unique drug regimens encountered per 100 subjects taking 3 or more medications. When drugs were viewed by therapeutic class, it was found that the most commonly prescribed drugs were not the most commonly co-prescribed drugs for any of the 16 drug classes investigated. We cross-referenced these medication lists with drug interaction data from Drugs.com to evaluate the potential for drug interactions. The number of drug alerts rose proportionally with the number of co-prescribed medications, rising from 3.3 alerts for individuals prescribed 5 medications to 11.7 alerts for individuals prescribed 10 medications. We found 22% of elderly subjects taking both a substrate and inhibitor of a given cytochrome P450 enzyme, and 4% taking multiple inhibitors of the same enzyme simultaneously. By examining drug pairs prescribed in 0.1% of the population or more, we found low agreement between co-prescription rate and co-discussion in the literature. These data show that prescribing trends in treatment could drive a large extent of individual variability in drug response, and that current pairwise approaches to assessing drug-drug interactions may be inadequate for

Potential drug interactions in patients given antiretroviral therapy

PubMed Central

dos Santos, Wendel Mombaque; Secoli, Silvia Regina; Padoin, Stela Maris de Mello

2016-01-01

ABSTRACT Objective: to investigate potential drug-drug interactions (PDDI) in patients with HIV infection on antiretroviral therapy. Methods: a cross-sectional study was conducted on 161 adults with HIV infection. Clinical, socio demographic, and antiretroviral treatment data were collected. To analyze the potential drug interactions, we used the software Micromedex(r). Statistical analysis was performed by binary logistic regression, with a p-value of ≤0.05 considered statistically significant. Results: of the participants, 52.2% were exposed to potential drug-drug interactions. In total, there were 218 potential drug-drug interactions, of which 79.8% occurred between drugs used for antiretroviral therapy. There was an association between the use of five or more medications and potential drug-drug interactions (p = 0.000) and between the time period of antiretroviral therapy being over six years and potential drug-drug interactions (p < 0.00). The clinical impact was prevalent sedation and cardiotoxicity. Conclusions: the PDDI identified in this study of moderate and higher severity are events that not only affect the therapeutic response leading to toxicity in the central nervous and cardiovascular systems, but also can interfere in tests used for detection of HIV resistance to antiretroviral drugs. PMID:27878224

Position-aware deep multi-task learning for drug-drug interaction extraction.

PubMed

Zhou, Deyu; Miao, Lei; He, Yulan

2018-05-01

A drug-drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely needed. In this paper, we propose a novel position-aware deep multi-task learning approach for extracting DDIs from biomedical texts. In particular, sentences are represented as a sequence of word embeddings and position embeddings. An attention-based bidirectional long short-term memory (BiLSTM) network is used to encode each sentence. The relative position information of words with the target drugs in text is combined with the hidden states of BiLSTM to generate the position-aware attention weights. Moreover, the tasks of predicting whether or not two drugs interact with each other and further distinguishing the types of interactions are learned jointly in multi-task learning framework. The proposed approach has been evaluated on the DDIExtraction challenge 2013 corpus and the results show that with the position-aware attention only, our proposed approach outperforms the state-of-the-art method by 0.99% for binary DDI classification, and with both position-aware attention and multi-task learning, our approach achieves a micro F-score of 72.99% on interaction type identification, outperforming the state-of-the-art approach by 1.51%, which demonstrates the effectiveness of the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Pharmacokinetic drug interactions of morphine, codeine, and their derivatives: theory and clinical reality, Part II.

PubMed

Armstrong, Scott C; Cozza, Kelly L

2003-01-01

Pharmacokinetic drug-drug interactions with codeine, dihydrocodeine, hydrocodone, oxycodone, and buprenorphine are reviewed in this column. These compounds have a very similar chemical structure to morphine. Unlike morphine, which is metabolized chiefly through conjugation reactions with uridine diphosphate glucuronosyl transferase (UGT) enzymes, these five drugs are metabolized both through oxidative reactions by the cytochrome P450 (CYP450) enzyme and conjugation by UGT enzymes. There is controversy as to whether codeine, dihydrocodeine, and hydrocodone are actually prodrugs requiring activation by the CYP450 2D6 enzyme or UGT enzymes. Oxycodone and buprenorphine, however, are clearly not prodrugs and are metabolized by the CYP450 2D6 and 3A4 enzymes, respectively. Knowledge of this metabolism assists in the understanding for the potential of drug-drug interactions with these drugs. This understanding is important so that clinicians can choose the proper dosages for analgesia and anticipate potential drug-drug interactions.

Antiretroviral Drug Interactions: Overview of Interactions Involving New and Investigational Agents and the Role of Therapeutic Drug Monitoring for Management

PubMed Central

Rathbun, R. Chris; Liedtke, Michelle D.

2011-01-01

Antiretrovirals are prone to drug-drug and drug-food interactions that can result in subtherapeutic or supratherapeutic concentrations. Interactions between antiretrovirals and medications for other diseases are common due to shared metabolism through cytochrome P450 (CYP450) and uridine diphosphate glucuronosyltransferase (UGT) enzymes and transport by membrane proteins (e.g., p-glycoprotein, organic anion-transporting polypeptide). The clinical significance of antiretroviral drug interactions is reviewed, with a focus on new and investigational agents. An overview of the mechanistic basis for drug interactions and the effect of individual antiretrovirals on CYP450 and UGT isoforms are provided. Interactions between antiretrovirals and medications for other co-morbidities are summarized. The role of therapeutic drug monitoring in the detection and management of antiretroviral drug interactions is also briefly discussed. PMID:24309307

Assessing and managing drug-nutrient interactions.

PubMed

Anderson, Karl E; Greenblatt, David J

2002-01-01

Drug-nutrient interactions can occur through many mechanisms. The amount of protein in the diet and the presence of micronutrients, such as polycyclic aromatic hydrocarbons and indoles, can affect drug metabolism. Although furanocoumarins in grapefruit juice can interact with certain oral medications, noninteracting medications generally can be substituted. Pharmacists need to provide patients with accurate information about drug-nutrient interactions and help to clarify common misconceptions about these effects.

Hazards and Benefits of Drug Interaction

ERIC Educational Resources Information Center

Labianca, Dominick A.

1978-01-01

Most cases of drug toxicity are direct consequences of drug misuse--either intentional or inadvertent. Discusses two types of drug interaction--synergistic and antagonistic. The former produces a combined effect greater than the sum of the effects of the individual drugs concerned; the latter is produced when the desired action of one drug is…

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.

Drug-nutrient interaction in clinical nutrition.

PubMed

Chan, Lingtak-Neander

2002-05-01

Drug-nutrient interactions have been recognized for decades. It is known that improper management of some of these interactions may lead to therapeutic failure or cause serious adverse effects to the patients. While most of the known drug-nutrient interactions involve changes in oral bioavailabilities and absorption of the offending compounds, recent investigations suggest that different mechanisms also exist. A mechanism-derived classification system for drug-nutrient interactions has only recently been developed. This system should facilitate the future research and development of practice guidelines in the identification and management of important interactions.

Energetics of drug-DNA interactions.

PubMed

Chaires, J B

1997-01-01

Understanding the thermodynamics of drug binding to DNA is of both practical and fundamental interest. The practical interest lies in the contribution that thermodynamics can make to the rational design process for the development of new DNA targeted drugs. Thermodynamics offer key insights into the molecular forces that drive complex formation that cannot be obtained by structural or computational studies alone. The fundamental interest in these interactions lies in what they can reveal about the general problems of parsing and predicting ligand binding free energies. For these problems, drug-DNA interactions offer several distinct advantages, among them being that the structures of many drug-DNA complexes are known at high resolution and that such structures reveal that in many cases the drug acts as a rigid body, with little conformational change upon binding. Complete thermodynamic profiles (delta G, delta H, delta S, delta Cp) for numerous drug-DNA interactions have been obtained, with the help of high-sensitivity microcalorimetry. The purpose of this article is to offer a perspective on the interpretation of these thermodynamics parameters, and in particular how they might be correlated with known structural features. Obligatory conformational changes in the DNA to accommodate intercalators and the loss of translational and rotational freedom upon complex formation both present unfavorable free energy barriers for binding. Such barriers must be overcome by favorable free energy contributions from the hydrophobic transfer of ligand from solution into the binding site, polyelectrolyte contributions from coupled ion release, and molecular interactions (hydrogen and ionic bonds, van der Waals interactions) that form within the binding site. Theoretical and semiempirical tools that allow estimates of these contributions to be made will be discussed, and their use in dissecting experimental data illustrated. This process, even at the current level of approximation

Clinical relevance of cimetidine drug interactions.

PubMed

Shinn, A F

1992-01-01

The excellent efficacy and tolerability profiles of H2-antagonists have established these agents as the leading class of antiulcer drugs. Attention has been focused on drug interactions with H2-antagonists as a means of product differentiation and because many patients are receiving multiple drug therapy. The main mechanism of most drug interactions involving cimetidine appears to be inhibition of the hepatic microsomal enzyme cytochrome P450, an effect which may be related to the different structures of H2-antagonists. Ranitidine appears to have less affinity than cimetidine for this system. There have been many published case reports and studies of drug interactions with cimetidine, but many of these have provided pharmacokinetic data only, with little information concerning the clinical significance of these findings. Nevertheless, the coadministration of cimetidine with drugs that have a narrow therapeutic margin (such as theophylline) may potentially result in clinically significant adverse effects. The monitoring of serum concentrations of drugs coadministered with cimetidine may reduce the risk of adverse events but does not abolish the problem. However, for most patients, concomitant administration of cimetidine with drugs possessing a wide therapeutic margin is unlikely to pose a significant problem.

Resolving anaphoras for the extraction of drug-drug interactions in pharmacological documents

PubMed Central

2010-01-01

Background Drug-drug interactions are frequently reported in the increasing amount of biomedical literature. Information Extraction (IE) techniques have been devised as a useful instrument to manage this knowledge. Nevertheless, IE at the sentence level has a limited effect because of the frequent references to previous entities in the discourse, a phenomenon known as 'anaphora'. DrugNerAR, a drug anaphora resolution system is presented to address the problem of co-referring expressions in pharmacological literature. This development is part of a larger and innovative study about automatic drug-drug interaction extraction. Methods The system uses a set of linguistic rules drawn by Centering Theory over the analysis provided by a biomedical syntactic parser. Semantic information provided by the Unified Medical Language System (UMLS) is also integrated in order to improve the recognition and the resolution of nominal drug anaphors. Besides, a corpus has been developed in order to analyze the phenomena and evaluate the current approach. Each possible case of anaphoric expression was looked into to determine the most effective way of resolution. Results An F-score of 0.76 in anaphora resolution was achieved, outperforming significantly the baseline by almost 73%. This ad-hoc reference line was developed to check the results as there is no previous work on anaphora resolution in pharmalogical documents. The obtained results resemble those found in related-semantic domains. Conclusions The present approach shows very promising results in the challenge of accounting for anaphoric expressions in pharmacological texts. DrugNerAr obtains similar results to other approaches dealing with anaphora resolution in the biomedical domain, but, unlike these approaches, it focuses on documents reflecting drug interactions. The Centering Theory has proved being effective at the selection of antecedents in anaphora resolution. A key component in the success of this framework is the

Drug membrane interaction and the importance for drug transport, distribution, accumulation, efficacy and resistance.

PubMed

Seydel, J K; Coats, E A; Cordes, H P; Wiese, M

1994-10-01

Some aspects of drug membrane interaction and its influence on drug transport, accumulation, efficacy and resistance have been discussed. The interactions manifest themselves macroscopically in changes in the physical and thermodynamic properties of "pure membranes" or bilayers. As various amounts of foreign molecules enter the membrane, in particular the main gel to liquid crystalline phase transition can be dramatically changed. This may change permeability, cell-fusion, cell resistance and may also lead to changes in conformation of the embedded receptor proteins. Furthermore, specific interactions with lipids may lead to drug accumulation in membranes and thus to much larger concentrations at the active site than present in the surrounding water phase. The lipid environment may also lead to changes in the preferred conformation of drug molecules. These events are directly related to drug efficacy. The determination of essential molecular criteria for the interaction could be used to design new and more selective therapeutics. This excursion in some aspects of drug membrane interaction underlines the importance of lipids and their interaction with drug molecules for our understanding of drug action, but this is not really a new thought but has been formulated in 1884 by THUDICUM: "Phospholipids are the centre, life and chemical soul of all bioplasm whatsoever, that of plants as well as of animals".

[Pharmacokinetic interactions of telaprevir with other drugs].

PubMed

Berenguer Berenguer, Juan; González-García, Juan

2013-07-01

Telaprevir is a new direct-acting antiviral drug for the treatment of hepatitis C virus (HCV) infection and is both a substrate and an inhibitor of cytochrome P450 (CYP450) isoenzymes. With the introduction of this new drug, assessment of drug-drug interactions has become a key factor in the evaluation of patients under treatment for HCV infection. During the treatment of this infection, many patients require other drugs to mitigate the adverse effects of anti-HCV drugs and to control other comorbidities. Moreover, most patients coinfected with HIV and HCV require antiretroviral therapy during treatment for HCV. Physicians should therefore be familiar with the pharmacokinetic properties of direct-acting antivirals for HCV treatment and their potential drug-drug interactions. The present article reviews the available information to date on the interactions of telaprevir with other drugs and provides recommendations for daily clinical practice. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Drug Interactions in Childhood Cancer

PubMed Central

Haidar, Cyrine; Jeha, Sima

2016-01-01

Children with cancer are increasingly benefiting from novel therapeutic strategies and advances in supportive care, as reflected in improvements in both their survival and quality of life. However, the continuous emergence of new oncology drugs and supportive care agents has also increased the possibility of deleterious drug interactions and healthcare providers need to practice extreme caution when combining medications. In this review, we discuss the most common interactions of chemotherapeutic agents with supportive care drugs such as anticonvulsants, antiemetics, uric acid–lowering agents, acid suppressants, antimicrobials, and pain management medications in pediatric oncology patients. As chemotherapy agents interact not only with medications but also with foods and herbal supplements that patients receive during the course of their treatment, we also briefly review such interactions and provide recommendations to avoid unwanted and potentially fatal interactions in children with cancer. PMID:20869315

Factors influencing the difference between forecasted and actual drug sales volumes under the price-volume agreement in South Korea.

PubMed

Park, Sun-Young; Han, Euna; Kim, Jini; Lee, Eui-Kyung

2016-08-01

This study analyzed factors contributing to increases in the actual sales volumes relative to forecasted volumes of drugs under price-volume agreement (PVA) policy in South Korea. Sales volumes of newly listed drugs on the national formulary are monitored under PVA policy. When actual sales volume exceeds the pre-agreed forecasted volume by 30% or more, the drug is subject to price-reduction. Logistic regression assessed the factors related to whether drugs were the PVA price-reduction drugs. A generalized linear model with gamma distribution and log-link assessed the factors influencing the increase in actual volumes compared to forecasted volume in the PVA price-reduction drugs. Of 186 PVA monitored drugs, 34.9% were price-reduction drugs. Drugs marketed by pharmaceutical companies with previous-occupation in the therapeutic markets were more likely to be PVA price-reduction drugs than drugs marketed by firms with no previous-occupation. Drugs of multinational pharmaceutical companies were more likely to be PVA price-reduction drugs than those of domestic companies. Having more alternative existing drugs was significantly associated with higher odds of being PVA price-reduction drugs. Among the PVA price-reduction drugs, the increasing rate of actual volume compared to forecasted volume was significantly higher in drugs with clinical usefulness. By focusing the negotiation efforts on those target drugs, PVA policy can be administered more efficiently with the improved predictability of the drug sales volumes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Managing Drug-Drug Interaction Between Ombitasvir, Paritaprevir/Ritonavir, Dasabuvir, and Mycophenolate Mofetil.

PubMed

Lemaitre, Florian; Ben Ali, Zeineb; Tron, Camille; Jezequel, Caroline; Boglione-Kerrien, Christelle; Verdier, Marie-Clémence; Guyader, Dominique; Bellissant, Eric

2017-08-01

No drug-drug interaction study has been conducted to date for the combination of ombitasvir, paritaprevir/ritonavir, dasabuvir (3D), and mycophenolic acid (MPA). We here report the case of a hepatitis C virus-infected patient treated with 3D and MPA for vasculitis. In light of the threat of drug-drug interaction, the concentration of MPA was measured before, during, and 15 days after the end of the 3D treatment. Similar values were found at all 3 time points, thus indicating that there is probably no need to adapt MPA dosage to 3D.

Radiopharmaceuticals drug interactions: a critical review.

PubMed

Santos-Oliveira, Ralph; Smith, Sheila W; Carneiro-Leão, Ana Maria A

2008-12-01

Radiopharmaceuticals play a critical role in modern medicine primarily for diagnostic purposes, but also for monitoring disease progression and response to treatment. As the use of image has been increased, so has the use of prescription medications. These trends increase the risk of interactions between medications and radiopharmaceuticals. These interactions which have an impact on image by competing with the radiopharmaceutical for binding sites for example can lead to false negative results. Drugs that accelerate the metabolism of the radiopharmaceutical can have a positive impact (i.e. speeding its clearance) or, if repeating image is needed, a negative impact. In some cases, for example in cardiac image among patients taking doxirubacin, these interactions may have a therapeutic benefit. The incidence of drug-radiopharmaceuticals adverse reactions is unknown, since they may not be reported or even recognized. Here,we compiled the medical literature, using the criteria of a systematic review established by the Cochrane Collaboration, on pharmaceutical-drug interactions to provide a summary of documented interactions by organ system and radiopharmaceuticals. The purpose is to provide a reference on drug interactions that could inform the nuclear medicine staff in their daily routine. Efforts to increase adverse event reporting, and ideally consolidate reports worldwide, can provide a critically needed resource for prevention of drug-radiopharmaceuticals interactions.

[Clinical relevance of drug interactions between nonsteroidal antiinflammatory drugs (NSAIDs) and antihypertensives].

PubMed

Villa, Juan; Cano, Alejandra; Franco, David; Monsalve, Mauricio; Hincapié, Jaime; Amariles, Pedro

2014-11-01

To establish the clinical relevance of drug interactions between nonsteroidal antiinflammatory drugs (NSAIDs) and antihypertensives, based on the interaction severity and probability of occurrence. Systematic review. A PubMed/Medline search was made using the MeSH terms: NSAIDs, Antihypertensive drugs, and Drug interactions. Articles between 2002 and 2012, human studies, in Spanish and English and full text access were included. Found articles were included and some of the references used in this works. Studies with in vitro methods, effects on ocular hypertension and those who do not consider the interaction NSAIDs, antihypertensives were excluded. For the selection of the papers included three independent reviewers were involved. We used a tool for data extraction and for assess of the interaction clinical relevance. Nineteen of 50 papers found were included. There were identified 21 interactions with pharmacodynamic mechanism, classified by their clinical relevance in level-2 high risk (76.2%) and level-3 medium risk (23.8%). In addition, evidence of 16 combinations of no interaction were found. Some NSAIDs may attenuate the effectiveness of antihypertensive drugs when used concurrently, especially with angiotensin converting enzyme inhibitors, diuretics, beta blockers and angiotensin receptorsii blockers. There was no evidence of effect modification of calcium channel antagonists, especially dihydropyridine, by concurrent use of NSAIDs. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Physiologically-Based Pharmacokinetic Modeling of Macitentan: Prediction of Drug-Drug Interactions.

PubMed

de Kanter, Ruben; Sidharta, Patricia N; Delahaye, Stéphane; Gnerre, Carmela; Segrestaa, Jerome; Buchmann, Stephan; Kohl, Christopher; Treiber, Alexander

2016-03-01

Macitentan is a novel dual endothelin receptor antagonist for the treatment of pulmonary arterial hypertension (PAH). It is metabolized by cytochrome P450 (CYP) enzymes, mainly CYP3A4, to its active metabolite ACT-132577. A physiological-based pharmacokinetic (PBPK) model was developed by combining observations from clinical studies and physicochemical parameters as well as absorption, distribution, metabolism and excretion parameters determined in vitro. The model predicted the observed pharmacokinetics of macitentan and its active metabolite ACT-132577 after single and multiple dosing. It performed well in recovering the observed effect of the CYP3A4 inhibitors ketoconazole and cyclosporine, and the CYP3A4 inducer rifampicin, as well as in predicting interactions with S-warfarin and sildenafil. The model was robust enough to allow prospective predictions of macitentan-drug combinations not studied, including an alternative dosing regimen of ketoconazole and nine other CYP3A4-interacting drugs. Among these were the HIV drugs ritonavir and saquinavir, which were included because HIV infection is a known risk factor for the development of PAH. This example of the application of PBPK modeling to predict drug-drug interactions was used to support the labeling of macitentan (Opsumit).

Adverse events caused by potential drug-drug interactions in an intensive care unit of a teaching hospital

PubMed Central

Alvim, Mariana Macedo; da Silva, Lidiane Ayres; Leite, Isabel Cristina Gonçalves; Silvério, Marcelo Silva

2015-01-01

Objective To evaluate the incidence of potential drug-drug interactions in an intensive care unit of a hospital, focusing on antimicrobial drugs. Methods This cross-sectional study analyzed electronic prescriptions of patients admitted to the intensive care unit of a teaching hospital between January 1 and March 31, 2014 and assessed potential drug-drug interactions associated with antimicrobial drugs. Antimicrobial drug consumption levels were expressed in daily doses per 100 patient-days. The search and classification of the interactions were based on the Micromedex® system. Results The daily prescriptions of 82 patients were analyzed, totaling 656 prescriptions. Antimicrobial drugs represented 25% of all prescription drugs, with meropenem, vancomycin and ceftriaxone being the most prescribed medications. According to the approach of daily dose per 100 patient-days, the most commonly used antimicrobial drugs were cefepime, meropenem, sulfamethoxazole + trimethoprim and ciprofloxacin. The mean number of interactions per patient was 2.6. Among the interactions, 51% were classified as contraindicated or significantly severe. Highly significant interactions (clinical value 1 and 2) were observed with a prevalence of 98%. Conclusion The current study demonstrated that antimicrobial drugs are frequently prescribed in intensive care units and present a very high number of potential drug-drug interactions, with most of them being considered highly significant. PMID:26761473

Large-Scale Identification and Analysis of Suppressive Drug Interactions

PubMed Central

Cokol, Murat; Weinstein, Zohar B.; Yilancioglu, Kaan; Tasan, Murat; Doak, Allison; Cansever, Dilay; Mutlu, Beste; Li, Siyang; Rodriguez-Esteban, Raul; Akhmedov, Murodzhon; Guvenek, Aysegul; Cokol, Melike; Cetiner, Selim; Giaever, Guri; Iossifov, Ivan; Nislow, Corey; Shoichet, Brian; Roth, Frederick P.

2014-01-01

SUMMARY One drug may suppress the effects of another. Although knowledge of drug suppression is vital to avoid efficacy-reducing drug interactions or discover countermeasures for chemical toxins, drug-drug suppression relationships have not been systematically mapped. Here, we analyze the growth response of Saccharomyces cerevisiae to anti-fungal compound (“drug”) pairs. Among 440 ordered drug pairs, we identified 94 suppressive drug interactions. Using only pairs not selected on the basis of their suppression behavior, we provide an estimate of the prevalence of suppressive interactions between anti-fungal compounds as 17%. Analysis of the drug suppression network suggested that Bromopyruvate is a frequently suppressive drug and Staurosporine is a frequently suppressed drug. We investigated potential explanations for suppressive drug interactions, including chemogenomic analysis, coaggregation, and pH effects, allowing us to explain the interaction tendencies of Bromopyruvate. PMID:24704506

Hepatic transporter drug-drug interactions: an evaluation of approaches and methodologies.

PubMed

Williamson, Beth; Riley, Robert J

2017-12-01

Drug-drug interactions (DDIs) continue to account for 5% of hospital admissions and therefore remain a major regulatory concern. Effective, quantitative prediction of DDIs will reduce unexpected clinical findings and encourage projects to frontload DDI investigations rather than concentrating on risk management ('manage the baggage') later in drug development. A key challenge in DDI prediction is the discrepancies between reported models. Areas covered: The current synopsis focuses on four recent influential publications on hepatic drug transporter DDIs using static models that tackle interactions with individual transporters and in combination with other drug transporters and metabolising enzymes. These models vary in their assumptions (including input parameters), transparency, reproducibility and complexity. In this review, these facets are compared and contrasted with recommendations made as to their application. Expert opinion: Over the past decade, static models have evolved from simple [I]/k i models to incorporate victim and perpetrator disposition mechanisms including the absorption rate constant, the fraction of the drug metabolised/eliminated and/or clearance concepts. Nonetheless, models that comprise additional parameters and complexity do not necessarily out-perform simpler models with fewer inputs. Further, consideration of the property space to exploit some drug target classes has also highlighted the fine balance required between frontloading and back-loading studies to design out or 'manage the baggage'.

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

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

PubMed

Shi, Jian-Yu; Yiu, Siu-Ming; Li, Yiming; Leung, Henry C M; Chin, Francis Y L

2015-07-15

Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html. Copyright © 2015 Elsevier Inc. All rights reserved.

Venetoclax (ABT-199) Might Act as a Perpetrator in Pharmacokinetic Drug-Drug Interactions.

PubMed

Weiss, Johanna; Gajek, Thomas; Köhler, Bruno Christian; Haefeli, Walter Emil

2016-02-24

Venetoclax (ABT-199) represents a specific B-cell lymphoma 2 (Bcl-2) inhibitor that is currently under development for the treatment of lymphoid malignancies. So far, there is no published information on its interaction potential with important drug metabolizing enzymes and drug transporters, or its efficacy in multidrug resistant (MDR) cells. We therefore scrutinized its drug-drug interaction potential in vitro. Inhibition of cytochrome P450 enzymes (CYPs) was quantified by commercial kits. Inhibition of drug transporters (P-glycoprotein (P-gp, ABCB1), breast cancer resistance protein (BCRP), and organic anion transporting polypeptides (OATPs)) was evaluated by the use of fluorescent probe substrates. Induction of drug transporters and drug metabolizing enzymes was quantified by real-time RT-PCR. The efficacy of venetoclax in MDR cells lines was evaluated with proliferation assays. Venetoclax moderately inhibited P-gp, BCRP, OATP1B1, OATP1B3, CYP3A4, and CYP2C19, whereas CYP2B6 activity was increased. Venetoclax induced the mRNA expression of CYP1A1, CYP1A2, UGT1A3, and UGT1A9. In contrast, expression of ABCB1 was suppressed, which might revert tumor resistance towards antineoplastic P-gp substrates. P-gp over-expression led to reduced antiproliferative effects of venetoclax. Effective concentrations for inhibition and induction lay in the range of maximum plasma concentrations of venetoclax, indicating that it might act as a perpetrator drug in pharmacokinetic drug-drug interactions.

Pharmacokinetic Drug Interactions with Panax ginseng.

PubMed

Ramanathan, Meenakshi R; Penzak, Scott R

2017-08-01

Panax ginseng is widely used as an adaptogen throughout the world. The major active constituents of P. ginseng are ginsenosides. Most naturally occurring ginsenosides are deglycosylated by colonic bacteria to intestinal metabolites. Ginsenosides along with these metabolites are widely accepted as being responsible for the pharmacologic activity and drug interaction potential of ginseng. Numerous preclinical studies have assessed the influence of various ginseng components on cytochrome P450 (CYP), glucuronidation, and drug transport activity. Results from these investigations have been largely inconclusive due to the use of different ginseng products and variations in methodology between studies. Drug interaction studies in humans have been conflicting and have largely yielded negative results or results that suggest only a weak interaction. One study using a midazolam probe found weak CYP3A induction and another using a fexofenadine probe found weak P-gp inhibition. Despite several case reports indicating a drug interaction between warfarin and P. ginseng, pharmacokinetic studies involving these agents in combination have failed to find significant pharmacokinetic or pharmacodynamic interactions. To this end, drug interactions involving P. ginseng appear to be rare; however, close clinical monitoring is still suggested for patients taking warfarin or CYP3A or P-gp substrates with narrow therapeutic indices.

Evaluation of linear classifiers on articles containing pharmacokinetic evidence of drug-drug interactions.

PubMed

Kolchinsky, A; Lourenço, A; Li, L; Rocha, L M

2013-01-01

Drug-drug interaction (DDI) is a major cause of morbidity and mortality. DDI research includes the study of different aspects of drug interactions, from in vitro pharmacology, which deals with drug interaction mechanisms, to pharmaco-epidemiology, which investigates the effects of DDI on drug efficacy and adverse drug reactions. Biomedical literature mining can aid both kinds of approaches by extracting relevant DDI signals from either the published literature or large clinical databases. However, though drug interaction is an ideal area for translational research, the inclusion of literature mining methodologies in DDI workflows is still very preliminary. One area that can benefit from literature mining is the automatic identification of a large number of potential DDIs, whose pharmacological mechanisms and clinical significance can then be studied via in vitro pharmacology and in populo pharmaco-epidemiology. We implemented a set of classifiers for identifying published articles relevant to experimental pharmacokinetic DDI evidence. These documents are important for identifying causal mechanisms behind putative drug-drug interactions, an important step in the extraction of large numbers of potential DDIs. We evaluate performance of several linear classifiers on PubMed abstracts, under different feature transformation and dimensionality reduction methods. In addition, we investigate the performance benefits of including various publicly-available named entity recognition features, as well as a set of internally-developed pharmacokinetic dictionaries. We found that several classifiers performed well in distinguishing relevant and irrelevant abstracts. We found that the combination of unigram and bigram textual features gave better performance than unigram features alone, and also that normalization transforms that adjusted for feature frequency and document length improved classification. For some classifiers, such as linear discriminant analysis (LDA), proper

Metabolic mechanisms of drug-nutrient interactions.

PubMed

Hathcock, J N

1985-01-01

Metabolic mechanisms of nutrition and drug interactions include 1) the effects of diet on drug metabolism and action and 2) the effects of drugs on nutritional processes. The type, amount, and timing of foods consumed influence drug dissolution, absorption, distribution, metabolism, and excretion. High-fat meals enhance the absorption of griseofulvin and some other drugs. Milk and other sources of calcium inhibit absorption of tetracycline. High-fat meals increase plasma concentrations of free fatty acids and thereby displace many drugs from binding sites on plasma albumin. High-protein diets increase the activity of the mixed-function oxidase system and enhance the metabolism of numerous drugs. High-electrolyte intakes increase excretion of lithium and also diminish the action of diuretic agents. Bile acid sequestrants and some laxatives decrease lipid digestion and absorption, as well as absorption of the fat-soluble vitamins. Numerous drugs, including tetracycline and cholestyramine, bind iron and decrease its absorption. Coumarins inhibit the function of vitamin K. Phenobarbital and other anticonvulsants are inducers of cytochrome P-450 and the mixed-function oxidase system. Long-term treatment with these inducers can cause excessive metabolism and deficiency of vitamin D. Prooxidant drugs such as chloroquine, drugs detoxified by conjugation with glutathione, and alcohol can deplete reduced glutathione with consequent effects on amino acid transport and the redox status of cells. Acid-forming foods acidify the urine and increase the loss of alkaline drugs such as the amphetamines. Base-forming drugs increase the loss of acidic drugs such as barbiturates. The range of metabolic interactions of drugs and nutrients includes the full scope of physiological processes to which drugs and nutrients are subject.

[Cooperation with the electronic medical record and accounting system of an actual dose of drug given by a radiology information system].

PubMed

Yamamoto, Hideo; Yoneda, Tarou; Satou, Shuji; Ishikawa, Toru; Hara, Misako

2009-12-20

By input of the actual dose of a drug given into a radiology information system, the system converting with an accounting system into a cost of the drug from the actual dose in the electronic medical record was built. In the drug master, the first unit was set as the cost of the drug, and we set the second unit as the actual dose. The second unit in the radiology information system was received by the accounting system through electronic medical record. In the accounting system, the actual dose was changed into the cost of the drug using the dose of conversion to the first unit. The actual dose was recorded on a radiology information system and electronic medical record. The actual dose was indicated on the accounting system, and the cost for the drug was calculated. About the actual dose of drug, cooperation of the information in a radiology information system and electronic medical record were completed. It was possible to decide the volume of drug from the correct dose of drug at the previous inspection. If it is necessary for the patient to have another treatment of medicine, it is important to know the actual dose of drug given. Moreover, authenticity of electronic medical record based on a statute has also improved.

Predicting transporter-mediated drug interactions: Commentary on: "Pharmacokinetic evaluation of a drug transporter cocktail consisting of digoxin, furosemide, metformin and rosuvastatin" and "Validation of a microdose probe drug cocktail for clinical drug interaction assessments for drug transporters and CYP3A".

PubMed

Zhang, L; Sparreboom, A

2017-04-01

Transporters, expressed in various tissues, govern the absorption, distribution, metabolism, and excretion of drugs, and consequently their inherent safety and efficacy profiles. Drugs may interact with a transporter as a substrate and/or an inhibitor. Understanding transporter-mediated drug-drug interactions (DDIs), in addition to enzyme-mediated DDIs, is an integral part of risk assessment in drug development and regulatory review because the concomitant use of more than one medication in patients is common. © 2016 ASCPT.

Making Transporter Models for Drug-Drug Interaction Prediction Mobile.

PubMed

Ekins, Sean; Clark, Alex M; Wright, Stephen H

2015-10-01

The past decade has seen increased numbers of studies publishing ligand-based computational models for drug transporters. Although they generally use small experimental data sets, these models can provide insights into structure-activity relationships for the transporter. In addition, such models have helped to identify new compounds as substrates or inhibitors of transporters of interest. We recently proposed that many transporters are promiscuous and may require profiling of new chemical entities against multiple substrates for a specific transporter. Furthermore, it should be noted that virtually all of the published ligand-based transporter models are only accessible to those involved in creating them and, consequently, are rarely shared effectively. One way to surmount this is to make models shareable or more accessible. The development of mobile apps that can access such models is highlighted here. These apps can be used to predict ligand interactions with transporters using Bayesian algorithms. We used recently published transporter data sets (MATE1, MATE2K, OCT2, OCTN2, ASBT, and NTCP) to build preliminary models in a commercial tool and in open software that can deliver the model in a mobile app. In addition, several transporter data sets extracted from the ChEMBL database were used to illustrate how such public data and models can be shared. Predicting drug-drug interactions for various transporters using computational models is potentially within reach of anyone with an iPhone or iPad. Such tools could help prioritize which substrates should be used for in vivo drug-drug interaction testing and enable open sharing of models. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Drug–drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems

PubMed Central

Rao, PSS; Earla, Ravindra; Kumar, Anil

2015-01-01

Introduction Substance abuse is a common problem among HIV-infected individuals. Importantly, addictions as well as moderate use of alcohol, smoking, or other illicit drugs have been identified as major reasons for non-adherence to antiretroviral therapy (ART) among HIV patients. The literature also suggests a decrease in the response to ART among HIV patients who use these substances, leading to failure to achieve optimal virological response and increased disease progression. Areas covered This review discusses the challenges with adherence to ART as well as observed drug interactions and known toxicities with major drugs of abuse, such as alcohol, smoking, methamphetamine, cocaine, marijuana, and opioids. The lack of adherence and drug interactions potentially lead to decreased efficacy of ART drugs and increased ART, and drugs of abuse-mediated toxicity. As CYP is the common pathway in metabolizing both ART and drugs of abuse, we discuss the possible involvement of CYP pathways in such drug interactions. Expert opinion We acknowledge that further studies focusing on common metabolic pathways involving CYP and advance research in this area would help to potentially develop novel/alternate interventions and drug dose/regimen adjustments to improve medication outcomes in HIV patients who consume drugs of abuse. PMID:25539046

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

Drug–drug interactions with imatinib

PubMed Central

Récoché, Isabelle; Rousseau, Vanessa; Bourrel, Robert; Lapeyre-Mestre, Maryse; Chebane, Leila; Despas, Fabien; Montastruc, Jean-Louis; Bondon-Guitton, Emmanuelle

2016-01-01

Abstract Many patients treated with imatinib, used in cancer treatment, are using several other drugs that could interact with imatinib. Our aim was to study all the drug–drug interactions (DDIs) observed in patients treated with imatinib. We performed 2 observational studies, between the 1st January 2012 and the 31st August 2015 in the Midi-Pyrénées area (South Western France), using the French health insurance reimbursement database and then the French Pharmacovigilance Database (FPVD). A total of 544 patients received at least 1 reimbursement for imatinib. Among them, 486 (89.3%) had at least 1 drug that could potentially interact with imatinib. Paracetamol was the most frequent drug involved (77.4%). Proton pump inhibitors, dexamethasone and levothyroxine, were found in >10% of patients. In the FPVD, among a total of 25 reports of ADRs with imatinib recorded in the Midi-Pyrénées area, 10 (40%) had potential DDIs with imatinib. Imatinib was most frequently prescribed by hospital physicians and drugs interacting with imatinib, by general practitioners. Our study showed that at least 40% of the patients treated with imatinib were at risk of DDIs and that all prescribers must be cautious with DDIs in patients treated with imatinib. During imatinib treatment, we particularly recommend to limit the dose of paracetamol at 1300 mg per day, to avoid the use of dexamethasone, and to double the dose of levothyroxine. PMID:27749579

Public health relevance of drug-nutrition interactions.

PubMed

Péter, Szabolcs; Navis, Gerjan; de Borst, Martin H; von Schacky, Clemens; van Orten-Luiten, Anne Claire B; Zhernakova, Alexandra; Witkamp, Renger F; Janse, André; Weber, Peter; Bakker, Stephan J L; Eggersdorfer, Manfred

2017-08-01

The public health relevance of drug-nutrition interactions is currently highly undervalued and overlooked. This is particularly the case for elderly persons where multi-morbidity and consequently polypharmacy is very common. Vitamins and other micronutrients have central functions in metabolism, and their interactions with drugs may result in clinically relevant physiological impairments but possibly also in positive effects. On 12 April 2016, the University Medical Center Groningen (The Netherlands), as part of its Healthy Ageing program, organized a workshop on the public health relevance of drug-nutrient interactions. In this meeting, experts in the field presented results from recent studies on interactions between pharmaceuticals and nutrients, and discussed the role of nutrition for elderly, focusing on those persons receiving pharmaceutical treatment. This paper summarizes the proceedings of the symposium and provides an outlook for future research needs and public health measures. Since food, pharma and health are closely interconnected domains, awareness is needed in the medical community about the potential relevance of drug-nutrition interactions. Experts and stakeholders should advocate for the integration of drug-nutrition evaluations in the drug development process. Strategies for the individual patients should be developed, by installing drug review protocols, screening for malnutrition and integrating this topic into the general medical advice.

DrugBank: a knowledgebase for drugs, drug actions and drug targets

PubMed Central

Wishart, David S.; Knox, Craig; Guo, An Chi; Cheng, Dean; Shrivastava, Savita; Tzur, Dan; Gautam, Bijaya; Hassanali, Murtaza

2008-01-01

DrugBank is a richly annotated resource that combines detailed drug data with comprehensive drug target and drug action information. Since its first release in 2006, DrugBank has been widely used to facilitate in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. The latest version of DrugBank (release 2.0) has been expanded significantly over the previous release. With ∼4900 drug entries, it now contains 60% more FDA-approved small molecule and biotech drugs including 10% more ‘experimental’ drugs. Significantly, more protein target data has also been added to the database, with the latest version of DrugBank containing three times as many non-redundant protein or drug target sequences as before (1565 versus 524). Each DrugCard entry now contains more than 100 data fields with half of the information being devoted to drug/chemical data and the other half devoted to pharmacological, pharmacogenomic and molecular biological data. A number of new data fields, including food–drug interactions, drug–drug interactions and experimental ADME data have been added in response to numerous user requests. DrugBank has also significantly improved the power and simplicity of its structure query and text query searches. DrugBank is available at http://www.drugbank.ca PMID:18048412

Drug-nutrient interactions in elderly people.

PubMed

Akamine, Dirce; Filho, Michel K; Peres, Carmem M

2007-05-01

The presence of multiple diseases, polypharmacy, malnutrition, and impaired metabolism in elderly individuals increases the risks of adverse events related to drug-food interactions. Some considerations for elderly people influenced by drug-food interactions are reviewed. When investigating pharmacokinetic and pharmacodynamic modifications in the elderly, other factors have to be considered, such as anorexia, dementia, depression, intolerance, gastrointestinal-tract disorders, social and economic factors, reduced abilities (visual and manual) and difficulties in chewing or swallowing. Specific reference is made herein to the health status of the elderly Brazilian population based on the observations of our research group. In addition, the most common diseases (such as cancer, coronary heart disease, dementia, diabetes mellitus, hypertension and osteoporosis), the drugs usually prescribed to treat them, and the adverse nutritional reactions that occur in older patients are summarized. In order to develop a correct drug prescription plan and nutritional intervention to avoid any kind of undesirable drug-food interaction effect, it is necessary to adequately diagnose the disease and often re-evaluate the chosen treatment, identify disease stages and the necessary therapies to minimize the number of drugs administered, and select a reasonable nutritional assessment.

Food-drug interactions: grapefruit juice.

PubMed

Diaconu, Camelia Harapu; Cuciureanu, Magdalena; Vlase, L; Cuciureanu, Rodica

2011-01-01

Food-drug interactions are increasingly recognized as important clinical events which may change significantly the bioavailability of oral administrated drugs. Grapefruit juice (GFJ) demonstrated multiple interactions with drugs leading to loss of the therapeutic effects or increased side-effects. GFJ decreases pre-systemic metabolism through a) competitive or mechanism-based inhibition of gut wall CYP3A4 isoenzymes and b) P-glycoprotein (P-gp), c) multidrug resistance protein-2 (MRP2) or d) organic anion-transporting polypeptide (OATP) inhibition. Although, GFJ presents high amounts of flavonoids (e.g. naringin, naringenin), furanocoumarins (e.g. 6',7'-dihydroxybergamottin, bergamottin) are the main chemicals involved in the pharmacokinetic interactions. As compounds of GFJ show additive or synergistic effects, all the major furanocoumarins are necessary for the maximal inhibitory effect. Also, related citrus fruits (sweeties, pummelo and sour orange) or various plants containing furanocoumarins may present pharmacological interactions, yet to be discovered.

PXR as a mediator of herb-drug interaction.

PubMed

Hogle, Brett C; Guan, Xiudong; Folan, M Maggie; Xie, Wen

2018-04-01

Medicinal herbs have been a part of human medicine for thousands of years. The herb-drug interaction is an extension of drug-drug interaction, in which the consumptions of herbs cause alterations in the metabolism of drugs the patients happen to take at the same time. The pregnane X receptor (PXR) has been established as one of the most important transcriptional factors that regulate the expression of phase I enzymes, phase II enzymes, and drug transporters in the xenobiotic responses. Since its initial discovery, PXR has been implicated in multiple herb-drug interactions that can lead to alterations of the drug's pharmacokinetic properties and cause fluctuating therapeutic efficacies, possibly leading to complications. Regions of the world that heavily incorporate herbalism into their primary health care and people turning to alternative medicines as a personal choice could be at risk for adverse reactions or unintended results from these interactions. This article is intended to highlight our understanding of the PXR-mediated herb-drug interactions. Copyright © 2017. Published by Elsevier B.V.

Anticoagulant Medicine: Potential for Drug-Food Interactions

MedlinePlus

... Medications Anticoagulants and Drug-Food Interactions Anticoagulants and Drug-Food Interactions Make an Appointment Ask a Question ... care provider before making the change. Anticoagulants and Medicine There are many medicines that can interact with ...

Interactions between drugs and polymers influencing hot melt extrusion.

PubMed

Li, Yongcheng; Pang, Huishi; Guo, Zhefei; Lin, Ling; Dong, Yixuan; Li, Ge; Lu, Ming; Wu, Chuangbin

2014-02-01

Hot melt extrusion (HME) as a technique for producing amorphous solid dispersion (ASD) has been widely used in pharmaceutical research. The biggest challenge for the application of HME is the thermal degradation of drug, poor physical stability of ASD and precipitation of drug during dissolution. Interactions between drugs and polymers may play an important role in overcoming these barriers. In this review, influence of drug-polymer interactions on HME and the methods for characterizing the drug-polymer interactions were reviewed. Strong drug-polymer interactions, especially ionic interactions and hydrogen bonds, are helpful to improving the thermal stability of drug during HME, enhancing the physical stability of ASD during storage and maintaining supersaturated solution after dissolution in gastrointestinal tract. The interactions can be quantitatively and qualitatively characterized by many analysing methods. As many factors collectively determine the properties of HME products, drug-polymer interactions play an extremely important role. However, the action mechanisms of drug-polymer interactions need intensive investigation to provide more useful information for optimizing the formulation and the process parameters of HME. © 2013 Royal Pharmaceutical Society.

[Simple method for precognition of drug interaction between oral iron and phenolic hydroxyl group-containing drugs].

PubMed

Sunagane, Nobuyoshi; Yoshinobu, Etsuko; Murayama, Nobuko; Terawaki, Yasufumi; Kamimura, Naoki; Uruno, Tsutomu

2005-02-01

In the present study, we devised a simple method for detecting the drug interaction between oral iron preparations and phenolic hydroxyl group-containing drugs, using the coloring reaction as indicator, due to the formation of complexes or chelates. In the method, oral iron preparations and test drugs in amounts as much as single dose for adults were added to 10 ml of purified water to make sample suspensions for testing. Thirty minutes after mixing an oral iron suspension and a test drug suspension, the change of color in the mixture was observed macroscopically and graded as 0 to 3, with a marked color change judged as grade 3 and no color change as grade 0. Screening of 14 test drugs commonly used orally was carried out. When using sodium ferrous citrate preparations as oral iron, 5 were classified as grade 3, 2 as grade 2, 4 as grade 1, and 3 as grade 0, respectively. To verify usefulness of the method, the interactions suggested by screening were pharmacokinetically assessed by measuring serum concentrations of the drug in mice. When a levodopa or droxidopa preparation, judged as grade 3 in screening, was concomitantly administered with an iron preparation, a significant reduction in bioavailability of the test drug was observed, indicating possible drug interaction between the test drug and oral iron. Combined administration of an acetaminophen preparation, judged as grade 1, and oral iron preparation showed no influence on the bioavailability of the test drug, implying no detectable interactions between them. In conclusion, the simple method devised in the present study is useful for precognition of drug interactions between oral iron preparations and phenolic hydroxyl group-containing drugs, and the drugs with a higher grade in screening may induce drug interactions with oral iron.

DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank.

PubMed

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-06-15

Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. http://datamining-iip.fudan.edu.cn/service/DrugE-Rank zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Drug-drug interactions involving antidepressants: focus on desvenlafaxine.

PubMed

Low, Yvette; Setia, Sajita; Lima, Graca

2018-01-01

Psychiatric and physical conditions often coexist, and there is robust evidence that associates the frequency of depression with single and multiple physical conditions. More than half of patients with depression may have at least one chronic physical condition. Therefore, antidepressants are often used in cotherapy with other medications for the management of both psychiatric and chronic physical illnesses. The risk of drug-drug interactions (DDIs) is augmented by complex polypharmacy regimens and extended periods of treatment required, of which possible outcomes range from tolerability issues to lack of efficacy and serious adverse events. Optimal patient outcomes may be achieved through drug selection with minimal potential for DDIs. Desvenlafaxine is a serotonin-norepinephrine reuptake inhibitor approved for the treatment of adults with major depressive disorder. Pharmacokinetic studies of desvenlafaxine have shown a simple metabolic profile unique among antidepressants. This review examines the DDI profiles of antidepressants, particularly desvenlafaxine, in relation to drugs of different therapeutic areas. The summary and comparison of information available is meant to help clinicians in making informed decisions when using desvenlafaxine in patients with depression and comorbid chronic conditions.

Interactions between recreational drugs and antiretroviral agents.

PubMed

Antoniou, Tony; Tseng, Alice Lin-In

2002-10-01

To summarize existing data regarding potential interactions between recreational drugs and drugs commonly used in the management of HIV-positive patients. Information was obtained via a MEDLINE search (1966-August 2002) using the MeSH headings human immunodeficiency virus, drug interactions, cytochrome P450, medication names commonly prescribed for the management of HIV and related opportunistic infections, and names of commonly used recreational drugs. Abstracts of national and international conferences, review articles, textbooks, and references of all articles were also reviewed. Literature on pharmacokinetic interactions was considered for inclusion. Pertinent information was selected and summarized for discussion. In the absence of specific data, prediction of potential clinically significant interactions was based on pharmacokinetic and pharmacodynamic properties. All protease inhibitors (PIs) and nonnucleoside reverse transcriptase inhibitors are substrates and potent inhibitors or inducers of the cytochrome P450 system. Many classes of recreational drugs, including benzodiazepines, amphetamines, and opioids, are also metabolized by the liver and can potentially interact with antiretrovirals. Controlled interaction studies are often not available, but clinically significant interactions have been observed in a number of case reports. Overdoses secondary to interactions between the "rave" drugs methylenedioxymethamphetamine (MDMA) or gamma-hydroxybutyrate (GHB) and PIs have been reported. PIs, particularly ritonavir, may also inhibit metabolism of amphetamines, ketamine, lysergic acid diethylmide (LSD), and phencyclidine (PCP). Case series and pharmacokinetic studies suggest that nevirapine and efavirenz induce methadone metabolism, which may lead to symptoms of opiate withdrawal. A similar interaction may exist between methadone and the PIs ritonavir and nelfinavir, although the data are less consistent. Opiate metabolism can be inhibited or induced by

New era in drug interaction evaluation: US Food and Drug Administration update on CYP enzymes, transporters, and the guidance process.

PubMed

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

2008-06-01

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

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.

Drug-nutrient interaction.

PubMed

Matsui, M S; Rozovski, S J

1982-01-01

The effect of certain drugs on nutrient metabolism is discussed. Antituberculotic drugs such as INH and cycloserine interfere with vitamin B6 metabolism and may produce a secondary niacin deficiency. Oral contraceptives interfere with the metabolism of folic acid and ascorbic acid, and in cases of deficient nutrition, they also seem to interfere with riboflavin. Anticonvulsants can act as folate antagonists and precipitate folic acid deficiency. Therefore, in some cases, supplementation with folate has been recommended simultaneously with anticonvulsant therapy. Cholestyramine therapy has been associated with malabsorption of vitamins; several reports suggest that cholestyramine affects absorption of the fat-soluble vitamins K and D and, in addition, may alter water-soluble vitamins, including folic acid. The study of the interaction of drugs and nutrients is an area that deserves a greater attention in the future, especially in groups where nutrient deficiencies may be prevalent.

[Interactions of food and drug metabolism].

PubMed

Delzenne, N M; Verbeeck, R K

2001-01-01

The nutritional state, and/or the ingestion of specific nutrients, is/are able to modify drug disposition, by interfering with drug absorption, distribution, storage, and metabolism. Recent data report that nutrients interfere with drug metabolism either by modifying key enzymes of phase I (cytochromeP450 dependent mixed function oxidase) and II (glucuronosyl, sulfonyl- ... transferases), or by modulating coenzymes availability (NADPH, UDPglucuronic acid...). Food components involved in drug metabolism modifications are either macro-nutrients (carbohydrates, lipids, proteins, ethanol), micronutriments (vitamins, minerals), or phytochemicals. Drug-nutrients interactions may be beneficials, and thus could constitute, i.e. a way to improve drug therapeutic index, or generate adverse effects.

Drug utilization, prescription errors and potential drug-drug interactions: an experience in rural Sri Lanka.

PubMed

Rathish, Devarajan; Bahini, Sivaswamy; Sivakumar, Thanikai; Thiranagama, Thilani; Abarajithan, Tharmarajah; Wijerathne, Buddhika; Jayasumana, Channa; Siribaddana, Sisira

2016-06-25

Prescription writing is a process which transfers the therapeutic message from the prescriber to the patient through the pharmacist. Prescribing errors, drug duplication and potential drug-drug interactions (pDDI) in prescriptions lead to medication error. Assessment of the above was made in prescriptions dispensed at State Pharmaceutical Corporation (SPC), Anuradhapura, Sri Lanka. A cross sectional study was conducted. Drugs were classified according to the WHO anatomical, therapeutic chemical classification system. A three point Likert scale, a checklist and Medscape online drug interaction checker were used to assess legibility, completeness and pDDIs respectively. Thousand prescriptions were collected. Majority were hand written (99.8 %) and from the private sector (73 %). The most frequently prescribed substance and subgroup were atorvastatin (4 %, n = 3668) and proton pump inhibitors (7 %, n = 3668) respectively. Out of the substances prescribed from the government and private sectors, 59 and 50 % respectively were available in the national list of essential medicines, Sri Lanka. Patients address (5 %), Sri Lanka Medical Council (SLMC) registration number (35 %), route (7 %), generic name (16 %), treatment symbol (48 %), diagnosis (41 %) and refill information (6 %) were seen in less than half of the prescriptions. Most were legible with effort (65 %) and illegibility was seen in 9 %. There was significant difference in omission and/or errors of generic name (P = 0.000), dose (P = 0.000), SLMC registration number (P = 0.000), and in evidence of pDDI (P = 0.009) with regards to the sector of prescribing. The commonest subgroup involved in duplication was non-steroidal anti-inflammatory drugs (NSAIDs) (43 %; 56/130). There were 1376 potential drug interactions (466/887 prescriptions). Most common pair causing pDDI was aspirin with losartan (4 %, n = 1376). Atorvastatin was the most frequently prescribed substance

Drug interactions evaluation: An integrated part of risk assessment of therapeutics

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

Zhang, Lei; Reynolds, Kellie S.; Zhao, Ping

2010-03-01

Pharmacokinetic drug interactions can lead to serious adverse events or decreased drug efficacy. The evaluation of a new molecular entity's (NME's) drug-drug interaction potential is an integral part of risk assessment during drug development and regulatory review. Alteration of activities of enzymes or transporters involved in the absorption, distribution, metabolism, or excretion of a new molecular entity by concomitant drugs may alter drug exposure, which can impact response (safety or efficacy). The recent Food and Drug Administration (FDA) draft drug interaction guidance ( (http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm072101.pdf)) highlights the methodologies and criteria that may be used to guide drug interaction evaluation by industrymore » and regulatory agencies and to construct informative labeling for health practitioner and patients. In addition, the Food and Drug Administration established a 'Drug Development and Drug Interactions' website to provide up-to-date information regarding evaluation of drug interactions ( (http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DevelopmentResources/DrugInteractionsLabeling/ucm080499.htm)). This review summarizes key elements in the FDA drug interaction guidance and new scientific developments that can guide the evaluation of drug-drug interactions during the drug development process.« less

Predicting drug-target interactions using restricted Boltzmann machines.

PubMed

Wang, Yuhao; Zeng, Jianyang

2013-07-01

In silico prediction of drug-target interactions plays an important role toward identifying and developing new uses of existing or abandoned drugs. Network-based approaches have recently become a popular tool for discovering new drug-target interactions (DTIs). Unfortunately, most of these network-based approaches can only predict binary interactions between drugs and targets, and information about different types of interactions has not been well exploited for DTI prediction in previous studies. On the other hand, incorporating additional information about drug-target relationships or drug modes of action can improve prediction of DTIs. Furthermore, the predicted types of DTIs can broaden our understanding about the molecular basis of drug action. We propose a first machine learning approach to integrate multiple types of DTIs and predict unknown drug-target relationships or drug modes of action. We cast the new DTI prediction problem into a two-layer graphical model, called restricted Boltzmann machine, and apply a practical learning algorithm to train our model and make predictions. Tests on two public databases show that our restricted Boltzmann machine model can effectively capture the latent features of a DTI network and achieve excellent performance on predicting different types of DTIs, with the area under precision-recall curve up to 89.6. In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type. Further tests show that our approach can infer a high fraction of novel DTIs that has been validated by known experiments in the literature or other databases. These results indicate that our approach can have highly practical relevance to DTI prediction and drug repositioning, and hence advance the drug discovery process. Software and datasets are available on request. Supplementary data are

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.

Macrolides versus azalides: a drug interaction update.

PubMed

Amsden, G W

1995-09-01

To describe the current drug interaction profiles for all approved and investigational macrolide and azalide antimicrobials, and to comment on the clinical impact of these interactions when appropriate. MEDLINE was searched to identify all pertinent studies, review articles, and case reports from 1975 to 1995. When appropriate information was not available in the literature, data were obtained from the product manufacturers. All available data were reviewed to give an unbiased account of possible drug interactions. Data for some of the interactions were not available from the literature, but were available from abstracts or from company-supplied materials. Although the data were not always entirely explicative, the best attempt was made to deliver the pertinent information that clinical practitioners would need to formulate practice opinions. When more in-depth information was supplied in the form of a review or study report, a thorough explanation of pertinent methodology was supplied. Since the introduction of erythromycin into clinical practice, there have been several clinically significant drug interactions identified throughout the literature associated with this drug. These interactions have been caused mostly by inhibition of the CYP3A subclass of hepatic enzymes, thereby decreasing the metabolism of any other agent given concurrently that is also cleared through this mechanism. With the development and marketing of several new macrolides, it was hoped that the drug interaction profile associated with this class would improve. This has been met with variable success. Although some of the extensions of the 14-membered ring macrolides have shown an incidence of interactions equal to that of erythromycin, others have shown improved profiles. In contrast, the 16-membered ring macrolides have demonstrated a much improved, though not absent, interaction profile. The most success in avoiding drug interactions through structure modification has been accomplished

Drug/Cell-line Browser: interactive canvas visualization of cancer drug/cell-line viability assay datasets.

PubMed

Duan, Qiaonan; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Tan, Christopher M; Benes, Cyril H; Ma'ayan, Avi

2014-11-15

Recently, several high profile studies collected cell viability data from panels of cancer cell lines treated with many drugs applied at different concentrations. Such drug sensitivity data for cancer cell lines provide suggestive treatments for different types and subtypes of cancer. Visualization of these datasets can reveal patterns that may not be obvious by examining the data without such efforts. Here we introduce Drug/Cell-line Browser (DCB), an online interactive HTML5 data visualization tool for interacting with three of the recently published datasets of cancer cell lines/drug-viability studies. DCB uses clustering and canvas visualization of the drugs and the cell lines, as well as a bar graph that summarizes drug effectiveness for the tissue of origin or the cancer subtypes for single or multiple drugs. DCB can help in understanding drug response patterns and prioritizing drug/cancer cell line interactions by tissue of origin or cancer subtype. DCB is an open source Web-based tool that is freely available at: http://www.maayanlab.net/LINCS/DCB CONTACT: avi.maayan@mssm.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pharmacokinetic drug-drug interaction and their implication in clinical management.

PubMed

Palleria, Caterina; Di Paolo, Antonello; Giofrè, Chiara; Caglioti, Chiara; Leuzzi, Giacomo; Siniscalchi, Antonio; De Sarro, Giovambattista; Gallelli, Luca

2013-07-01

Drug-drug interactions (DDIs) are one of the commonest causes of medication error in developed countries, particularly in the elderly due to poly-therapy, with a prevalence of 20-40%. In particular, poly-therapy increases the complexity of therapeutic management and thereby the risk of clinically important DDIs, which can both induce the development of adverse drug reactions or reduce the clinical efficacy. DDIs can be classify into two main groups: pharmacokinetic and pharmacodynamic. In this review, using Medline, PubMed, Embase, Cochrane library and Reference lists we searched articles published until June 30 2012, and we described the mechanism of pharmacokinetic DDIs focusing the interest on their clinical implications.

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.

Interactions between drugs and drug-nutrient in enteral nutrition: a review based on evidences.

PubMed

Ferreira Silva, Renata; Rita Carvalho Garbi Novaes, Maria

2014-09-01

Enteral nutrition (EN) provides calories, macronutrients and micronutrients in adequate quantity and quality to meet the patient's needs. Some drugs when crushed and diluted may have their properties altered, including the reduction of bioavailability causing the reduction of the serum concentration of the drug; tube obstruction; drug-drug interaction or drug-nutrient interaction. The study was conducted through review of submitted articles in the databases of the Virtual Health Library (VHL): MEDLINE (National Library of Medicine, USA), Lilacs (Latin American and Caribbean Literature on Health Sciences) PUBMED - NCBI (National Center for Biotechnology Information) and COCHRANE. For this survey, 42 articles were identified during database searching. After applying the inclusion and exclusion criteria, 08 articles were selected, obtained from the MEDLINE and Lilacs. Some interactions were found such as the aluminium hydroxide and lactulose with the enteral nutrition, which may result in a precipitation and reduction of drug bioavailability. Mineral oil will alter the absorption of fat-soluble vitamins and reduces the tube light. Others results were found as phenytoin, warfarin, captopril and furosemide with enteral nutrition may reduce the maximum serum concentration. Drug interactions are more common in day-to-day activities than health professionals may suppose. Knowledge on the matter may also assist in reducing cases of obstruction of tubes, through which enteral nutrition and medications are administered. Thus, the multidisciplinary team, acting together, may have more beneficial effects to the patient. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study

PubMed Central

Ning, Yifan; Hernandez, Andres; Horn, John R; Jacobson, Rebecca; Boyce, Richard D

2016-01-01

Background Because vital details of potential pharmacokinetic drug-drug interactions are often described in free-text structured product labels, manual curation is a necessary but expensive step in the development of electronic drug-drug interaction information resources. The use of nonexperts to annotate potential drug-drug interaction (PDDI) mentions in drug product label annotation may be a means of lessening the burden of manual curation. Objective Our goal was to explore the practicality of using nonexpert participants to annotate drug-drug interaction descriptions from structured product labels. By presenting annotation tasks to both pharmacy experts and relatively naïve participants, we hoped to demonstrate the feasibility of using nonexpert annotators for drug-drug information annotation. We were also interested in exploring whether and to what extent natural language processing (NLP) preannotation helped improve task completion time, accuracy, and subjective satisfaction. Methods Two experts and 4 nonexperts were asked to annotate 208 structured product label sections under 4 conditions completed sequentially: (1) no NLP assistance, (2) preannotation of drug mentions, (3) preannotation of drug mentions and PDDIs, and (4) a repeat of the no-annotation condition. Results were evaluated within the 2 groups and relative to an existing gold standard. Participants were asked to provide reports on the time required to complete tasks and their perceptions of task difficulty. Results One of the experts and 3 of the nonexperts completed all tasks. Annotation results from the nonexpert group were relatively strong in every scenario and better than the performance of the NLP pipeline. The expert and 2 of the nonexperts were able to complete most tasks in less than 3 hours. Usability perceptions were generally positive (3.67 for expert, mean of 3.33 for nonexperts). Conclusions The results suggest that nonexpert annotation might be a feasible option for comprehensive

Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.

PubMed

Hochheiser, Harry; Ning, Yifan; Hernandez, Andres; Horn, John R; Jacobson, Rebecca; Boyce, Richard D

2016-04-11

Because vital details of potential pharmacokinetic drug-drug interactions are often described in free-text structured product labels, manual curation is a necessary but expensive step in the development of electronic drug-drug interaction information resources. The use of nonexperts to annotate potential drug-drug interaction (PDDI) mentions in drug product label annotation may be a means of lessening the burden of manual curation. Our goal was to explore the practicality of using nonexpert participants to annotate drug-drug interaction descriptions from structured product labels. By presenting annotation tasks to both pharmacy experts and relatively naïve participants, we hoped to demonstrate the feasibility of using nonexpert annotators for drug-drug information annotation. We were also interested in exploring whether and to what extent natural language processing (NLP) preannotation helped improve task completion time, accuracy, and subjective satisfaction. Two experts and 4 nonexperts were asked to annotate 208 structured product label sections under 4 conditions completed sequentially: (1) no NLP assistance, (2) preannotation of drug mentions, (3) preannotation of drug mentions and PDDIs, and (4) a repeat of the no-annotation condition. Results were evaluated within the 2 groups and relative to an existing gold standard. Participants were asked to provide reports on the time required to complete tasks and their perceptions of task difficulty. One of the experts and 3 of the nonexperts completed all tasks. Annotation results from the nonexpert group were relatively strong in every scenario and better than the performance of the NLP pipeline. The expert and 2 of the nonexperts were able to complete most tasks in less than 3 hours. Usability perceptions were generally positive (3.67 for expert, mean of 3.33 for nonexperts). The results suggest that nonexpert annotation might be a feasible option for comprehensive labeling of annotated PDDIs across a broader

Results of a Doravirine-Atorvastatin Drug-Drug Interaction Study.

PubMed

Khalilieh, Sauzanne; Yee, Ka Lai; Sanchez, Rosa I; Triantafyllou, Ilias; Fan, Li; Maklad, Noha; Jordan, Heather; Martell, Maureen; Iwamoto, Marian

2017-02-01

Doravirine is a novel, highly potent, nonnucleoside reverse transcriptase inhibitor that is administered once daily and that is in development for the treatment of HIV-1 infection. In vitro and clinical data suggest that doravirine is unlikely to cause significant drug-drug interactions via major drug-metabolizing enzymes or transporters. As a common HIV-1 infection comorbidity, hypercholesterolemia is often treated with statins, including the commonly prescribed atorvastatin. Atorvastatin is subject to drug-drug interactions with cytochrome P450 3A4 (CYP3A4) inhibitors. Increased exposure due to CYP3A4 inhibition may lead to serious adverse events (AEs), including rhabdomyolysis. Furthermore, atorvastatin is a substrate for breast cancer resistance protein (BCRP), of which doravirine may be a weak inhibitor; this may increase atorvastatin exposure. The potential of doravirine to affect atorvastatin pharmacokinetics was investigated in a two-period, fixed-sequence study in healthy individuals. In period 1, a single dose of atorvastatin at 20 mg was administered followed by a 72-h washout. In period 2, doravirine at 100 mg was administered once daily for 8 days, with a single dose of atorvastatin at 20 mg concomitantly being administered on day 5. Sixteen subjects were enrolled, and 14 completed the trial; 2 discontinued due to AEs unrelated to the treatment. The atorvastatin area under the curve from time zero to infinity was similar with and without doravirine (geometric mean ratio [GMR] for doravirine-atorvastatin/atorvastatin, 0.98; 90% confidence interval [CI], 0.90 to 1.06), while the maximum concentration decreased by 33% (GMR for doravirine-atorvastatin/atorvastatin, 0.67; 90% CI, 0.52 to 0.85). These changes were deemed not to be clinically meaningful. Both of the study drugs were generally well tolerated. Doravirine had no clinically relevant effect on atorvastatin pharmacokinetics in healthy subjects, providing support for the coadministration of

Results of a Doravirine-Atorvastatin Drug-Drug Interaction Study

PubMed Central

Yee, Ka Lai; Sanchez, Rosa I.; Triantafyllou, Ilias; Fan, Li; Maklad, Noha; Jordan, Heather; Martell, Maureen; Iwamoto, Marian

2016-01-01

ABSTRACT Doravirine is a novel, highly potent, nonnucleoside reverse transcriptase inhibitor that is administered once daily and that is in development for the treatment of HIV-1 infection. In vitro and clinical data suggest that doravirine is unlikely to cause significant drug-drug interactions via major drug-metabolizing enzymes or transporters. As a common HIV-1 infection comorbidity, hypercholesterolemia is often treated with statins, including the commonly prescribed atorvastatin. Atorvastatin is subject to drug-drug interactions with cytochrome P450 3A4 (CYP3A4) inhibitors. Increased exposure due to CYP3A4 inhibition may lead to serious adverse events (AEs), including rhabdomyolysis. Furthermore, atorvastatin is a substrate for breast cancer resistance protein (BCRP), of which doravirine may be a weak inhibitor; this may increase atorvastatin exposure. The potential of doravirine to affect atorvastatin pharmacokinetics was investigated in a two-period, fixed-sequence study in healthy individuals. In period 1, a single dose of atorvastatin at 20 mg was administered followed by a 72-h washout. In period 2, doravirine at 100 mg was administered once daily for 8 days, with a single dose of atorvastatin at 20 mg concomitantly being administered on day 5. Sixteen subjects were enrolled, and 14 completed the trial; 2 discontinued due to AEs unrelated to the treatment. The atorvastatin area under the curve from time zero to infinity was similar with and without doravirine (geometric mean ratio [GMR] for doravirine-atorvastatin/atorvastatin, 0.98; 90% confidence interval [CI], 0.90 to 1.06), while the maximum concentration decreased by 33% (GMR for doravirine-atorvastatin/atorvastatin, 0.67; 90% CI, 0.52 to 0.85). These changes were deemed not to be clinically meaningful. Both of the study drugs were generally well tolerated. Doravirine had no clinically relevant effect on atorvastatin pharmacokinetics in healthy subjects, providing support for the coadministration of

Herb–drug interactions: an overview of systematic reviews

PubMed Central

Posadzki, Paul; Watson, Leala; Ernst, Edzard

2013-01-01

OBJECTIVES The aim of this overview of systematic reviews (SRs) is to evaluate critically the evidence regarding interactions between herbal medicinal products (HMPs) and synthetic drugs. METHODS Four electronic databases were searched to identify relevant SRs. RESULTS Forty‐six SRs of 46 different HMPs met our inclusion criteria. The vast majority of SRs were of poor methodological quality. The majority of these HMPs were not associated with severe herb–drug interactions. Serious herb–drug interactions were noted for Hypericum perforatum and Viscum album. The most severe interactions resulted in transplant rejection, delayed emergence from anaesthesia, cardiovascular collapse, renal and liver toxicity, cardiotoxicity, bradycardia, hypovolaemic shock, inflammatory reactions with organ fibrosis and death. Moderately severe interactions were noted for Ginkgo biloba, Panax ginseng, Piper methysticum, Serenoa repens and Camellia sinensis. The most commonly interacting drugs were antiplatelet agents and anticoagulants. CONCLUSION The majority of the HMPs evaluated in SRs were not associated with drug interactions with serious consequences. However, the poor quality and the scarcity of the primary data prevent firm conclusions. PMID:22670731

DrugECs: An Ensemble System with Feature Subspaces for Accurate Drug-Target Interaction Prediction

PubMed Central

Jiang, Jinjian; Wang, Nian; Zhang, Jun

2017-01-01

Background Drug-target interaction is key in drug discovery, especially in the design of new lead compound. However, the work to find a new lead compound for a specific target is complicated and hard, and it always leads to many mistakes. Therefore computational techniques are commonly adopted in drug design, which can save time and costs to a significant extent. Results To address the issue, a new prediction system is proposed in this work to identify drug-target interaction. First, drug-target pairs are encoded with a fragment technique and the software “PaDEL-Descriptor.” The fragment technique is for encoding target proteins, which divides each protein sequence into several fragments in order and encodes each fragment with several physiochemical properties of amino acids. The software “PaDEL-Descriptor” creates encoding vectors for drug molecules. Second, the dataset of drug-target pairs is resampled and several overlapped subsets are obtained, which are then input into kNN (k-Nearest Neighbor) classifier to build an ensemble system. Conclusion Experimental results on the drug-target dataset showed that our method performs better and runs faster than the state-of-the-art predictors. PMID:28744468

Hypericum perforatum: pharmacokinetic, mechanism of action, tolerability, and clinical drug-drug interactions.

PubMed

Russo, Emilio; Scicchitano, Francesca; Whalley, Benjamin J; Mazzitello, Carmela; Ciriaco, Miriam; Esposito, Stefania; Patanè, Marinella; Upton, Roy; Pugliese, Michela; Chimirri, Serafina; Mammì, Maria; Palleria, Caterina; De Sarro, Giovambattista

2014-05-01

Hypericum perforatum (HP) belongs to the Hypericaceae family and is one of the oldest used and most extensively investigated medicinal herbs. The medicinal form comprises the leaves and flowering tops of which the primary ingredients of interest are naphthodianthrones, xanthones, flavonoids, phloroglucinols (e.g. hyperforin), and hypericin. Although several constituents elicit pharmacological effects that are consistent with HP's antidepressant activity, no single mechanism of action underlying these effects has thus far been found. Various clinical trials have shown that HP has a comparable antidepressant efficacy as some currently used antidepressant drugs in the treatment of mild/moderate depression. Interestingly, low-hyperforin-content preparations are effective in the treatment of depression. Moreover, HP is also used to treat certain forms of anxiety. However, HP can induce various cytochrome P450s isozymes and/or P-glycoprotein, of which many drugs are substrates and which are the main origin of HP-drug interactions. Here, we analyse the existing evidence describing the clinical consequence of HP-drug interactions. Although some of the reported interactions are based on findings from in vitro studies, the clinical importance of which remain to be demonstrated, others are based on case reports where causality can, in some cases, be determined to reveal clinically significant interactions that suggest caution, consideration, and disclosure of potential interactions prior to informed use of HP. Copyright © 2013 John Wiley & Sons, Ltd.

Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

PubMed

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

Pharmacokinetic drug-drug interaction and their implication in clinical management

PubMed Central

Palleria, Caterina; Di Paolo, Antonello; Giofrè, Chiara; Caglioti, Chiara; Leuzzi, Giacomo; Siniscalchi, Antonio; De Sarro, Giovambattista; Gallelli, Luca

2013-01-01

Drug-drug interactions (DDIs) are one of the commonest causes of medication error in developed countries, particularly in the elderly due to poly-therapy, with a prevalence of 20-40%. In particular, poly-therapy increases the complexity of therapeutic management and thereby the risk of clinically important DDIs, which can both induce the development of adverse drug reactions or reduce the clinical efficacy. DDIs can be classify into two main groups: pharmacokinetic and pharmacodynamic. In this review, using Medline, PubMed, Embase, Cochrane library and Reference lists we searched articles published until June 30 2012, and we described the mechanism of pharmacokinetic DDIs focusing the interest on their clinical implications. PMID:24516494

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

Predicting Drug-Target Interactions With Multi-Information Fusion.

PubMed

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

2017-03-01

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

Nano-assembly of Surfactants with Interfacial Drug-Interactive Motifs as Tailor-Designed Drug Carriers

PubMed Central

Gao, Xiang; Huang, Yixian; Makhov, Alexander M.; Epperly, Michael; Lu, Jianqin; Grab, Sheila; Zhang, Peijun; Rohan, Lisa; Xie, Xiang-qun (Sean); Wipf, Peter; Greenberger, Joel; Li, Song

2012-01-01

PEGylated lipopeptide surfactants carrying drug-interactive motifs specific for a peptide-nitroxide antioxidant, JP4-039, were designed and constructed to facilitate the solubilization of this drug candidate as micelles and emulsion nanoparticles. A simple screening process based on the ability that prevents the formation of crystals of JP4-039 in aqueous solution was used to identify agents that have potential drug-interactive activities. Several protected lysine derivatives possessing this activity were identified, of which α-Fmoc-ε-tBoc lysine is the most potent, followed by α-Cbz- and α-iso-butyloxycarbonyl-ε-tBoc-lysine. Using polymer-supported liquid-phase synthesis approach, a series of synthetic lipopeptide surfactants with PEG head group, varied numbers and geometries of α-Fmoc or α-Cbz-lysyl groups located at interfacial region as the drug-interactive domains, and oleoyl chains as the hydrophobic tails were synthesized. All α-Fmoc-lysyl-containing lipopeptide surfactants were able to solubilize JP4-039 as micelles, with enhanced solubilizing activity for surfactants with increased numbers of α-Fmoc groups. The PEGylated lipopeptide surfactants with α-Fmoc-lysyl groups alone tend to form filamentous or worm-like micelles. The presence of JP4-039 transformed α-Fmoc-containing filamentous micelles into dots and bar-like mixed micelles with substantially reduced sizes. Fluorescence quenching and NMR studies revealed that the drug and surfactant molecules were in a close proximity in the complex. JP4-039-loaded emulsion carrying α-Cbz-containing surfactants demonstrated enhanced stability over drug loaded emulsion without lipopeptide surfactants. JP4-039-emulsion showed significant mitigation effect on mice exposed to a lethal dose of radiation. PEGylated lipopeptides with an interfacially located drug-interactive domain are therefore tailor-designed formulation materials potentially useful for drug development. PMID:23244299

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.

A current review of cytochrome P450 interactions of psychotropic drugs.

PubMed

Madhusoodanan, Subramoniam; Velama, Umamaheswararao; Parmar, Jeniel; Goia, Diana; Brenner, Ronald

2014-05-01

The number of psychotropic drugs has expanded tremendously over the past few decades with a proportional increase in drug-drug interactions. The majority of psychotropic agents are biotransformed by hepatic enzymes, which can lead to significant drug-drug interactions. Most drug-drug interactions of psychotropics occur at metabolic level involving the hepatic cytochrome P450 enzyme system. We searched the National Library of Medicine, PsycINFO, and Cochrane reviews from 1981 to 2012 for original studies including clinical trials, double-blind, placebo-controlled studies, and randomized controlled trials. In addition, case reports, books, review articles, and hand-selected journals were utilized to supplement this review. Based on the clinical intensity of outcome, cytochrome interactions can be classified as severe, moderate, and mild. Severe interactions include effects that might be acutely life threatening. They are mainly inhibitory interactions with cardiovascular drugs. Moderate interactions include efficacy issues. Mild interactions include nonserious side effects, such as somnolence. Psychotropic drugs may interact with other prescribed medications used to treat concomitant medical illnesses. A thorough understanding of the most prescribed medications and patient education will help reduce the likelihood of potentially fatal drug-drug interactions.

Drug-Gut Microbiota Interactions: Implications for Neuropharmacology.

PubMed

Walsh, Jacinta; Griffin, Brendan T; Clarke, Gerard; Hyland, Niall P

2018-05-21

The fate and activity of drugs are frequently dictated not only by the host per se but also by the microorganisms present in the gastrointestinal tract. The gut microbiome is known to, both directly and indirectly, affect drug metabolism. More evidence now hints at the impact that drugs can have on the function and composition of the gut microbiome. Both microbiota-mediated alterations in drug metabolism and drug-mediated alterations in the gut microbiome can have beneficial or detrimental effects on the host. Greater insights into the mechanisms driving these reciprocal drug-gut microbiota interactions are needed, to guide the development of microbiome-targeted dietary or pharmacological interventions, with the potential to enhance drug efficacy or reduce drug side-effects. In this review, we explore the relationship between drugs and the gut microbiome, with a specific focus on potential mechanisms underpinning the drug-mediated alterations on the gut microbiome and the potential implications for psychoactive drugs. This article is protected by copyright. All rights reserved.

Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

PubMed Central

Jiang, Jing; Lu, Weiqiang; Li, Weihua; Liu, Guixia; Zhou, Weixing; Huang, Jin; Tang, Yun

2012-01-01

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning. PMID:22589709

Assessment of Drug-Drug Interaction in Ayder Comprehensive Specialized Hospital, Mekelle, Northern Ethiopia: A Retrospective Study

PubMed Central

Gebretsadik, Zeru; Gebrehans, Micheale; Getnet, Desalegn; Gebrie, Desye; Alema, Tsgab

2017-01-01

Introduction Adverse drug interaction is a major cause of morbidity and mortality. Its occurrence is influenced by a multitude of factors. The influences of drug-drug interactions (DDIs) can be minimized through creation of awareness to health care professionals. Objective The objective of this study was to assess DDIs in Ayder Comprehensive Specialized Hospital (ACSH). Methodology A retrospective study design was employed on patient prescriptions available in the outpatient department of pharmacy and filled from September 2016 to February 2017 in ACSH. Result From the 600 prescription records assessed, the average number of drugs on single prescription was 2.73. Regarding the interaction observed 34 (9.63%) prescriptions with major drug-drug interaction, 210 (59.5%) moderate, 87 (24.65%) minor, and 22 (6.22%) unknown were identified. Age category showed significant association to affect the occurrence of DDIs and polypharmacy had statistically significant association with DDIs in bivariate analysis which was lost in adjusted OR. Conclusion From the current study it can be concluded that nearly half of the prescription ordered in ACSH contained DDIs and from the prescription with interacting medications majority of them had moderate DDIs. PMID:29250554

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.

A mass spectrometry imaging approach for investigating how drug-drug interactions influence drug blood-brain barrier permeability.

PubMed

Vallianatou, Theodosia; Strittmatter, Nicole; Nilsson, Anna; Shariatgorji, Mohammadreza; Hamm, Gregory; Pereira, Marcela; Källback, Patrik; Svenningsson, Per; Karlgren, Maria; Goodwin, Richard J A; Andrén, Per E

2018-05-15

There is a high need to develop quantitative imaging methods capable of providing detailed brain localization information of several molecular species simultaneously. In addition, extensive information on the effect of the blood-brain barrier on the penetration, distribution and efficacy of neuroactive compounds is required. Thus, we have developed a mass spectrometry imaging method to visualize and quantify the brain distribution of drugs with varying blood-brain barrier permeability. With this approach, we were able to determine blood-brain barrier transport of different drugs and define the drug distribution in very small brain structures (e.g., choroid plexus) due to the high spatial resolution provided. Simultaneously, we investigated the effect of drug-drug interactions by inhibiting the membrane transporter multidrug resistance 1 protein. We propose that the described approach can serve as a valuable analytical tool during the development of neuroactive drugs, as it can provide physiologically relevant information often neglected by traditional imaging technologies. Copyright © 2018. Published by Elsevier Inc.

Cytochrome P450 enzyme mediated herbal drug interactions (Part 1)

PubMed Central

Wanwimolruk, Sompon; Prachayasittikul, Virapong

2014-01-01

It is well recognized that herbal supplements or herbal medicines are now commonly used. As many patients taking prescription medications are concomitantly using herbal supplements, there is considerable risk for adverse herbal drug interactions. Such interactions can enhance the risk for an individual patient, especially with regard to drugs with a narrow therapeutic index such as warfarin, cyclosporine A and digoxin. Herbal drug interactions can alter pharmacokinetic or/and pharmacodynamic properties of administered drugs. The most common pharmacokinetic interactions usually involve either the inhibition or induction of the metabolism of drugs catalyzed by the important enzymes, cytochrome P450 (CYP). The aim of the present article is to provide an updated review of clinically relevant metabolic CYP-mediated drug interactions between selected herbal supplements and prescription drugs. The commonly used herbal supplements selected include Echinacea, Ginkgo biloba, garlic, St. John's wort, goldenseal, and milk thistle. To date, several significant herbal drug interactions have their origins in the alteration of CYP enzyme activity by various phytochemicals. Numerous herbal drug interactions have been reported. Although the significance of many interactions is uncertain but several interactions, especially those with St. John’s wort, may have critical clinical consequences. St. John’s wort is a source of hyperforin, an active ingredient that has a strong affinity for the pregnane xenobiotic receptor (PXR). As a PXR ligand, hyperforin promotes expression of CYP3A4 enzymes in the small intestine and liver. This in turn causes induction of CYP3A4 and can reduce the oral bioavailability of many drugs making them less effective. The available evidence indicates that, at commonly recommended doses, other selected herbs including Echinacea, Ginkgo biloba, garlic, goldenseal and milk thistle do not act as potent or moderate inhibitors or inducers of CYP enzymes. A good

Drug-drug interaction between methotrexate and levetiracetam resulting in delayed methotrexate elimination.

PubMed

Bain, Emily; Birhiray, Ruemu E; Reeves, David J

2014-02-01

To report a case of delayed methotrexate (MTX) elimination while receiving concomitant levetiracetam. A 46-year-old man with relapsed osteosarcoma of the base of the skull receiving high-dose MTX tolerated his first cycle of MTX with elimination to nontoxic MTX levels (≤0.1 µmol/L) within 90 hours. After hospital discharge, the patient experienced seizures secondary to brain metastasis and started on levetiracetam, which was continued as maintenance therapy. The patient experienced delayed MTX elimination during cycles 2, 3, and 4 while receiving levetiracetam. On average, elimination to nontoxic MTX levels took 130 hours (106-144 hours). Before the fifth cycle of MTX, lorazepam was substituted for the levetiracetam. MTX was eliminated to nontoxic levels within 95 hours. During all cycles, the patient received standard supportive care and serum creatinine remained stable. No other drugs known to interact with MTX were administered. This possible drug interaction has only been reported once in the pediatric population. With a score of 6 on the Drug Interaction Probability Scale for evaluating causation of drug interactions, it is probable that the delayed MTX elimination was caused by an interaction with levetiracetam. Coadministration of levetiracetam and MTX may result in delayed elimination of MTX, increasing the likelihood of toxicity. Consideration should be given to temporarily switching from levetiracetam to another antiepileptic (ie, lorazepam) to prevent this interaction. This is particularly important in those experiencing delayed elimination with prior cycles of concomitant MTX and levetiracetam or those at greater risk for MTX toxicity.

Prevalence of the prescription of potentially interacting drugs.

PubMed

Tragni, Elena; Casula, Manuela; Pieri, Vasco; Favato, Giampiero; Marcobelli, Alberico; Trotta, Maria Giovanna; Catapano, Alberico Luigi

2013-01-01

The use of multiple medications is becoming more common, with a correspondingly increased risk of untoward effects and drug-related morbidity and mortality. We aimed at estimating the prevalence of prescription of relevant potentially interacting drugs and at evaluating possible predictors of potentially interacting drug exposure. We retrospectively analyzed data on prescriptions dispensed from January 2004 to August 2005 to individuals of two Italian regions with a population of almost 2.1 million individuals. We identified 27 pairs of potentially interacting drugs by examining clinical relevance, documentation, and volume of use in Italy. Subjects who received at least one prescription of both drugs were selected. Co-prescribing denotes "two prescriptions in the same day", and concomitant medication "the prescription of two drugs with overlapping coverage". A logistic regression analysis was conducted to examine the predictors of potential Drug-Drug Interaction (pDDIs). 957,553 subjects (45.3% of study population) were exposed to at least one of the drugs/classes of the 27 pairs. Overall, pDDIs occurred 2,465,819 times. The highest rates of concomitant prescription and of co-prescription were for ACE inhibitors+NSAIDs (6,253 and 4,621/100,000 plan participants). Considering concomitance, the male/female ratio was <1 in 17/27 pairs (from 0.31 for NSAIDs-ASA+SSRI to 0.74 for omeprazole+clopidogrel). The mean age was lowest for methotrexate pairs (+omeprazole, 59.9 years; +NSAIDs-ASA, 59.1 years) and highest for digoxin+verapamil (75.4 years). In 13/27 pairs, the mean ages were ≥70 years. On average, subjects involved in pDDIs received ≥10 drugs. The odds of exposure were more frequently higher for age ≥65 years, males, and those taking a large number of drugs. A substantial number of clinically important pDDIs were observed, particularly among warfarin users. Awareness of the most prevalent pDDIs could help practitioners in preventing concomitant use

Core drug-drug interaction alerts for inclusion in pediatric electronic health records with computerized prescriber order entry.

PubMed

Harper, Marvin B; Longhurst, Christopher A; McGuire, Troy L; Tarrago, Rod; Desai, Bimal R; Patterson, Al

2014-03-01

The study aims to develop a core set of pediatric drug-drug interaction (DDI) pairs for which electronic alerts should be presented to prescribers during the ordering process. A clinical decision support working group composed of Children's Hospital Association (CHA) members was developed. CHA Pharmacists and Chief Medical Information Officers participated. Consensus was reached on a core set of 19 DDI pairs that should be presented to pediatric prescribers during the order process. We have provided a core list of 19 high value drug pairs for electronic drug-drug interaction alerts to be recommended for inclusion as high value alerts in prescriber order entry software used with a pediatric patient population. We believe this list represents the most important pediatric drug interactions for practical implementation within computerized prescriber order entry systems.

Biology of PXR: role in drug-hormone interactions

PubMed Central

Wang, Jing; Dai, Shu; Guo, Yan; Xie, Wen; Zhai, Yonggong

2014-01-01

Hormonal homeostasis is essential for a variety of physiological and pathological processes. Elimination and detoxification of xenobiotics, such as drugs introduced into the human body, could disrupt the balance of hormones due to the induction of drug metabolizing enzymes (DMEs) and transporters. Pregnane X receptor (PXR, NR1I2) functions as a master xenobiotic receptor involved in drug metabolism and drug-drug interactions by its coordinated transcriptional regulation of phase I and phase II DMEs and transporters. Recently, increasing evidences indicate that PXR can also mediate the endocrine disruptor function and thus impact the integrity of the endocrine system. This review focuses primarily on the recent advances in our understanding of the function of PXR in glucocorticoid, mineralocorticoid, androgen and estrogen homeostasis. The elucidation of PXR-mediated drug-hormone interactions might have important therapeutic implications in dealing with hormone-dependent diseases and safety assessment of drugs. PMID:26417296

Mechanism-based inactivation of human cytochrome P450 enzymes: strategies for diagnosis and drug-drug interaction risk assessment.

PubMed

Venkatakrishnan, K; Obach, R S; Rostami-Hodjegan, A

2007-01-01

Among drugs that cause pharmacokinetic drug-drug interactions, mechanism-based inactivators of cytochrome P450 represent several of those agents that cause interactions of the greatest magnitude. In vitro inactivation kinetic data can be used to predict the potential for new drugs to cause drug interactions in the clinic. However, several factors exist, each with its own uncertainty, that must be taken into account in order to predict the magnitude of interactions reliably. These include aspects of in vitro experimental design, an understanding of relevant in vivo concentrations of the inactivator, and the extent to which the inactivated enzyme is involved in the clearance of the affected drug. Additionally, the rate of enzyme degradation in vivo is also an important factor that needs to be considered in the prediction of the drug interaction magnitudes. To address mechanism-based inactivation for new drugs, various in vitro experimental approaches have been employed. The selection of approaches for in vitro kinetic characterization of inactivation as well as in vitro-in vivo extrapolation should be guided by the purpose of the exercise and the stage of drug discovery and development, with an increase in the level of sophistication throughout the research and development process.

Co-morbidity and clinically significant interactions between antiepileptic drugs and other drugs in elderly patients with newly diagnosed epilepsy.

PubMed

Bruun, Emmi; Virta, Lauri J; Kälviäinen, Reetta; Keränen, Tapani

2017-08-01

A study was conducted to investigate the frequency of potential pharmacokinetic drug-to-drug interactions in elderly patients with newly diagnosed epilepsy. We also investigated co-morbid conditions associated with epilepsy. From the register of Kuopio University Hospital (KUH) we identified community-dwelling patients aged 65 or above with newly diagnosed epilepsy and in whom use of the first individual antiepileptic drug (AED) began in 2000-2013 (n=529). Furthermore, register data of the Social Insurance Institution of Finland were used for assessing potential interactions in a nationwide cohort of elderly subjects with newly diagnosed epilepsy. We extracted all patients aged 65 or above who had received special reimbursement for the cost of AEDs prescribed on account of epilepsy in 2012 where their first AED was recorded in 2011-2012 as monotherapy (n=1081). Clinically relevant drug interactions (of class C or D) at the time of starting of the first AED, as assessed via the SFINX-PHARAO database, were analysed. Hypertension (67%), dyslipidemia (45%), and ischaemic stroke (32%) were the most common co-morbid conditions in the hospital cohort of patients. In these patients, excessive polypharmacy (more than 10 concomitant drugs) was identified in 27% of cases. Of the patients started on carbamazepine, 52 subjects (32%) had one class-C or class-D drug interaction and 51 (31%) had two or more C- or D-class interactions. Only 2% of the subjects started on valproate exhibited a class-C interaction. None of the subjects using oxcarbazepine displayed class-C or class-D interactions. Patients with 3-5 (OR 4.22; p=0.05) or over six (OR 8.86; p=0.003) other drugs were more likely to have C- or D-class interaction. The most common drugs with potential interactions with carbamazepine were dihydropyridine calcium-blockers, statins, warfarin, and psychotropic drugs. Elderly patients with newly diagnosed epilepsy are at high risk of clinically relevant pharmacokinetic

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

NASA Astrophysics Data System (ADS)

Iqbal, Zafar

For nearly five decades, pharmaceutical researchers have studied solid solutions of drugs in polymers as a potential means to enhance the dissolution of drugs with poor aqueous solubility. This has become of greater importance in recent years because most new potential drug compounds (new chemical entities) exhibit poor water solubility and present great challenges to scientists who must design dosage forms from which the drugs are bioavailable. During the formulation of a solid solution, the drug undergoes physical but not chemical alterations that increase its chemical potential in the formulation relative to that of the pure drug in its stable form. This increased chemical potential is responsible for enhanced dissolution as well as physical instabilities, such as amorphous to crystalline conversions and precipitation within the solid state. The chemical potential is derived from the Gibbs free energy, so it is reasonable to explain the behavior of solid solution systems in terms of thermodynamics. Solid solutions and dispersions have been extensively studied by pharmaceutical scientists, both with regard to manufacturing aspects and the proposal of various models in attempts to explain the physical bases for how these systems work. Recently, Dave and Bellantone proposed a model based on the thermodynamic changes resulting from the formulation of binary solid solutions of a drug in the polymer PVP. Their model introduced a modification of the F-H theory, which was used to quantify the drug-polymer interaction energies and calculate the entropy of mixing of the drug and polymer. In this work, the model of Dave and Bellantone was extended to include three-component systems, consisting of one drug mixed in a carrier matrix consisting of mixture of two polymers or a polymer and a surfactant. For this research, solid solutions were formed using various drug weight fractions in the formulations. The study focused on the following points: (1) Prepare solid solution

Dendrimers in drug delivery and targeting: Drug-dendrimer interactions and toxicity issues

PubMed Central

Madaan, Kanika; Kumar, Sandeep; Poonia, Neelam; Lather, Viney; Pandita, Deepti

2014-01-01

Dendrimers are the emerging polymeric architectures that are known for their defined structures, versatility in drug delivery and high functionality whose properties resemble with biomolecules. These nanostructured macromolecules have shown their potential abilities in entrapping and/or conjugating the high molecular weight hydrophilic/hydrophobic entities by host-guest interactions and covalent bonding (prodrug approach) respectively. Moreover, high ratio of surface groups to molecular volume has made them a promising synthetic vector for gene delivery. Owing to these properties dendrimers have fascinated the researchers in the development of new drug carriers and they have been implicated in many therapeutic and biomedical applications. Despite of their extensive applications, their use in biological systems is limited due to toxicity issues associated with them. Considering this, the present review has focused on the different strategies of their synthesis, drug delivery and targeting, gene delivery and other biomedical applications, interactions involved in formation of drug-dendrimer complex along with characterization techniques employed for their evaluation, toxicity problems and associated approaches to alleviate their inherent toxicity. PMID:25035633

Herb-drug interactions: challenges and opportunities for improved predictions.

PubMed

Brantley, Scott J; Argikar, Aneesh A; Lin, Yvonne S; Nagar, Swati; Paine, Mary F

2014-03-01

Supported by a usage history that predates written records and the perception that "natural" ensures safety, herbal products have increasingly been incorporated into Western health care. Consumers often self-administer these products concomitantly with conventional medications without informing their health care provider(s). Such herb-drug combinations can produce untoward effects when the herbal product perturbs the activity of drug metabolizing enzymes and/or transporters. Despite increasing recognition of these types of herb-drug interactions, a standard system for interaction prediction and evaluation is nonexistent. Consequently, the mechanisms underlying herb-drug interactions remain an understudied area of pharmacotherapy. Evaluation of herbal product interaction liability is challenging due to variability in herbal product composition, uncertainty of the causative constituents, and often scant knowledge of causative constituent pharmacokinetics. These limitations are confounded further by the varying perspectives concerning herbal product regulation. Systematic evaluation of herbal product drug interaction liability, as is routine for new drugs under development, necessitates identifying individual constituents from herbal products and characterizing the interaction potential of such constituents. Integration of this information into in silico models that estimate the pharmacokinetics of individual constituents should facilitate prospective identification of herb-drug interactions. These concepts are highlighted with the exemplar herbal products milk thistle and resveratrol. Implementation of this methodology should help provide definitive information to both consumers and clinicians about the risk of adding herbal products to conventional pharmacotherapeutic regimens.

Potential Drug-Drug Interactions in a Cohort of Elderly, Polymedicated Primary Care Patients on Antithrombotic Treatment.

PubMed

Schneider, Katharina Luise; Kastenmüller, Kathrin; Weckbecker, Klaus; Bleckwenn, Markus; Böhme, Miriam; Stingl, Julia Carolin

2018-06-01

Drug-drug interactions (DDIs) are an important risk factor for adverse drug reactions. Older, polymedicated patients are particularly affected. Although antithrombotics have been detected as high-risk drugs for DDIs, data on older patients exposed to them are scarce. Baseline data of 365 IDrug study outpatients (≥ 60 years, use of an antithrombotic and one or more additional long-term drug) were analyzed regarding potential drug-drug interactions (pDDIs) with a clinical decision support system. Data included prescription and self-medication drugs. The prevalence of having one or more pDDI was 85.2%. The median number of alerts per patient was three (range 0-17). For 58.4% of the patients, potential severe/contraindicated interactions were detected. Antiplatelets and non-steroidal anti-inflammatory drugs (NSAIDs) showed the highest number of average pDDI alert involvements per use (2.9 and 2.2, respectively). For NSAIDs, also the highest average number of severe/contraindicated alert involvements per use (1.2) was observed. 91.8% of all pDDI involvements concerned the 25 most frequently used drug classes. 97.5% of the severe/contraindicated pDDIs were attributed to only nine different potential clinical manifestations. The most common management recommendation for severe/contraindicated pDDIs was to intensify monitoring. Number of drugs was the only detected factor significantly associated with increased number of pDDIs (p < 0.001). The findings indicate a high risk for pDDIs in older, polymedicated patients on antithrombotics. As a consequence of patients' frequently similar drug regimens, the variety of potential clinical manifestations was small. Awareness of these pDDI symptoms and the triggering drugs as well as patients' self-medication use may contribute to increased patient safety.

Theoretical and experimental investigation of drug-polymer interaction and miscibility and its impact on drug supersaturation in aqueous medium.

PubMed

Baghel, Shrawan; Cathcart, Helen; O'Reilly, Niall J

2016-10-01

Amorphous solid dispersions (ASDs) have the potential to offer higher apparent solubility and bioavailability of BCS class II drugs. Knowledge of the solid state drug-polymer solubility/miscibility and their mutual interaction are fundamental requirements for the effective design and development of such systems. To this end, we have carried out a comprehensive investigation of various ASD systems of dipyridamole and cinnarizine in polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) at different drug loadings. Theoretical and experimental examinations (by implementing binary and ternary Flory-Huggins (F-H) theory) related to drug-polymer interaction/miscibility including solubility parameter approach, melting point depression method, phase diagram, drug-polymer interaction in the presence of moisture and the effect of drug loading on interaction parameter were performed. The information obtained from this study was used to predict the stability of ASDs at different drug loadings and under different thermal and moisture conditions. Thermal and moisture sorption analysis not only provided the composition-dependent interaction parameter but also predicted the composition dependent miscibility. DPM-PVP, DPM-PAA and CNZ-PAA systems have shown molecular level mixing over the complete range of drug loading. For CNZ-PVP, the presence of a single Tg at lower drug loadings (10, 20 and 35%w/w) indicates the formation of solid solution. However, drug recrystallization was observed for samples with higher drug weight fractions (50 and 65%w/w). Finally, the role of polymer in maintaining drug supersaturation has also been explored. It has been found that drug-polymer combinations capable of hydrogen-bonding in the solution state (DPM-PVP, DPM-PAA and CNZ-PAA) are more effective in preventing drug crystallization compared to the drug-polymer systems without such interaction (CNZ-PVP). The DPM-PAA system outperformed all other ASDs in various stability conditions (dry-state, in

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

PubMed

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

2017-07-01

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

Prevalence of statin-drug interactions in older people: a systematic review.

PubMed

Thai, Michele; Reeve, Emily; Hilmer, Sarah N; Qi, Katie; Pearson, Sallie-Anne; Gnjidic, Danijela

2016-05-01

Statins are among the most frequently prescribed medications internationally. Older people are commonly prescribed multiple medications and are at an increased risk of drug-drug interactions, including statin-drug interactions. The aim of this study was to conduct a systematic review of current evidence on the prevalence of statin-drug interactions in older people. A systematic search of observational studies in Embase, Medline, and PubMed was conducted. Articles were included if they were published in English during the period July 2000-July 2014 and reported on the prevalence of statin-drug interactions in people over 65 years of age. Two reviewers independently assessed the articles for eligibility and extracted the data. The search returned 1556 eligible articles. A total of 19 articles met the inclusion criteria. In studies (n = 7) that focused on statin users only, the prevalence of potential statin-drug interactions assessed using different measures ranged from 0.19 to 33.0 %. In studies that examined drug interactions across a population of both statin users and non-users (n = 12), the prevalence of potential statin-drug interactions ranged from 0.1 to 7.1 % (n = 8), and the prevalence of clinically relevant statin-drug interactions ranged from 1.5 to 4 % (n = 4). Current published evidence suggests substantial variations in the prevalence of statin-drug interactions and their clinical relevance. Further studies are necessary to provide a better understanding of the prevalence of clinically significant statin-drug interactions, the medications most frequently contributing to statin-drug interactions, and impact on relevant clinical outcomes in older people.

Drug interactions with the dietary fiber Plantago ovata husk.

PubMed

Fernandez, Nelida; Lopez, Cristina; Díez, Raquel; Garcia, Juan J; Diez, Maria Jose; Sahagun, Ana; Sierra, Matilde

2012-11-01

Plantago ovata husk is a viscous water-soluble fiber obtained by milling the seed of Plantago ovata. The increased use of this compound for the treatment of diseases makes it necessary to know of its potential drug interactions. The present paper reviews the literature concerning interactions between drugs and the dietary fiber Plantago ovata husk. All publications which might describe interactions between the dietetic fiber Plantago ovata husk and other drugs were identified by searches using databases such as MEDLINE or EMBASE. Drug interactions have been the subject of numerous studies, but few of them have been carried out with dietary fiber and the results obtained have often been variable. The incidence and importance of interactions between fiber and drugs has increased due to a worldwide rise in the use of dietary fiber. Plantago ovata husk has the potential for producing both benefits and risks with both desirable and undesirable effects when coadministered with drugs. More clinical studies are justifiably needed to improve treatments and to better evaluate patient safety.

Family medicine residents' knowledge and attitudes about drug-nutrient interactions.

PubMed

Lasswell, A B; DeForge, B R; Sobal, J; Muncie, H L; Michocki, R

1995-04-01

The Joint Commission on Accreditation of Healthcare Organizations (JCAHO) requires that health professionals recognize the importance of drug-nutrient interactions and educate patients to prevent adverse effects. Drug-nutrient interactions are an important issue in medical practice, but it is not clear how or if physicians are trained in this issue. This investigation was a needs assessment that examined attitudes and knowledge about drug-nutrient interactions that was examined in a national sample of 834 family medicine residents in 56 residency programs. Most reported they had little or no formal training in drug-nutrient interactions in medical school (83%) or residency (80%). However, 79% believed it was the physician's responsibility to inform patients about drug-nutrient interactions, although many thought pharmacists (75%) and dietitians (66%) share this responsibility. Overall, residents correctly answered 61% +/- 19 of fourteen drug-nutrient interaction knowledge items. There was a slight increase in drug-nutrient knowledge as year of residency increased. Physicians' knowledge of drug-nutrient interactions may be improved by including nutrition education in the topics taught by physicians, nutritionists, and pharmacists using several educational strategies. Nutrition educators in particular can play a role in curriculum development about drug-nutrient interactions by developing, refining, and evaluating materials and educational tools. Nutrition educators need to provide this information in academic settings for the training of all health professionals as well as in patient education settings such as hospitals and public health clinics.

Herb–Drug Interactions: Challenges and Opportunities for Improved Predictions

PubMed Central

Brantley, Scott J.; Argikar, Aneesh A.; Lin, Yvonne S.; Nagar, Swati

2014-01-01

Supported by a usage history that predates written records and the perception that “natural” ensures safety, herbal products have increasingly been incorporated into Western health care. Consumers often self-administer these products concomitantly with conventional medications without informing their health care provider(s). Such herb–drug combinations can produce untoward effects when the herbal product perturbs the activity of drug metabolizing enzymes and/or transporters. Despite increasing recognition of these types of herb–drug interactions, a standard system for interaction prediction and evaluation is nonexistent. Consequently, the mechanisms underlying herb–drug interactions remain an understudied area of pharmacotherapy. Evaluation of herbal product interaction liability is challenging due to variability in herbal product composition, uncertainty of the causative constituents, and often scant knowledge of causative constituent pharmacokinetics. These limitations are confounded further by the varying perspectives concerning herbal product regulation. Systematic evaluation of herbal product drug interaction liability, as is routine for new drugs under development, necessitates identifying individual constituents from herbal products and characterizing the interaction potential of such constituents. Integration of this information into in silico models that estimate the pharmacokinetics of individual constituents should facilitate prospective identification of herb–drug interactions. These concepts are highlighted with the exemplar herbal products milk thistle and resveratrol. Implementation of this methodology should help provide definitive information to both consumers and clinicians about the risk of adding herbal products to conventional pharmacotherapeutic regimens. PMID:24335390

Drug-target interaction prediction: A Bayesian ranking approach.

PubMed

Peska, Ladislav; Buza, Krisztian; Koller, Júlia

2017-12-01

In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug

[Drug-food interactions in internal medicine: What physicians should know?].

PubMed

Mouly, S; Morgand, M; Lopes, A; Lloret-Linares, C; Bergmann, J-F

2015-08-01

Orally administered medications may interact with various fruits, vegetables, herbal medicines, functional foods or dietary supplements. Drug-food interactions, which are mostly unknown from prescribers, including internists, may be responsible for changes in drug plasma concentrations, which may decrease efficacy or led to sometimes life-threatening toxicity. Aging, concomitant medications, transplant recipients, patients with cancer, malnutrition, HIV infection and those receiving enteral or parenteral feeding are at increased risk of drug-food interactions. This review focused on the most clinically relevant drug-food interactions, including those with grapefruit juice, Saint-John's Wort, enteral or parenteral nutrition, their respective consequences in the clinical setting in order to provide thoughtful information for internists in their routine clinical practice. Specific clinical settings are also detailed, such as the Ramadan or multiple medications especially in elderly patients. Drug-food interactions are also presented with respect to the main therapeutic families, including the non-steroidal anti-inflammatory drugs, analgesics, cardiovascular medications, warfarin as well as new oral anticoagulants, anticancer drugs and immunosuppressant medications. Considerable effort has been achieved to a better understanding of food-drug interactions and increase clinicians' ability to anticipate their occurrence and consequences in clinical practice. Describing the frequency of relevant food-drug interactions in internal medicine is paramount in order to optimize patient care and drug dosing on an individual basis as well as to increase patients and doctors information. Copyright © 2015 Société nationale française de médecine interne (SNFMI). Published by Elsevier SAS. All rights reserved.

Detection of First-Line Drug Resistance Mutations and Drug-Protein Interaction Dynamics from Tuberculosis Patients in South India.

PubMed

Nachappa, Somanna Ajjamada; Neelambike, Sumana M; Amruthavalli, Chokkanna; Ramachandra, Nallur B

2018-05-01

Diagnosis of drug-resistant tuberculosis predominantly relies on culture-based drug susceptibility testing, which take weeks to produce a result and a more time-efficient alternative method is multiplex allele-specific PCR (MAS-PCR). Also, understanding the role of mutations in causing resistance helps better drug designing. To evaluate the ability of MAS-PCR in the detection of drug resistance and to understand the mechanism of interaction of drugs with mutant proteins in Mycobacterium tuberculosis. Detection of drug-resistant mutations using MAS-PCR and validation through DNA sequencing. MAS-PCR targeted five loci on three genes, katG 315 and inhA -15 for the drug isoniazid (INH), and rpoB 516, 526, and 531 for rifampicin (RIF). Furthermore, the sequence data were analyzed to study the effect on interaction of the anti-TB drug molecule with the target protein using in silico docking. We identified drug-resistant mutations in 8 out of 114 isolates with 2 of them as multidrug-resistant TB using MAS-PCR. DNA sequencing confirmed only six of these, recording a sensitivity of 85.7% and specificity of 99.3% for MAS-PCR. Molecular docking showed estimated free energy of binding (ΔG) being higher for RIF binding with RpoB S531L mutant. Codon 315 in KatG does not directly interact with INH but blocks the drug access to active site. We propose DNA sequencing-based drug resistance detection for TB, which is more accurate than MAS-PCR. Understanding the action of resistant mutations in disrupting the normal drug-protein interaction aids in designing effective drug alternatives.

Interactions between traditional Chinese medicine and western drugs in Taiwan: A population-based study.

PubMed

Chen, Kuan Chen; Lu, Richard; Iqbal, Usman; Hsu, Ko-Ching; Chen, Bi-Li; Nguyen, Phung-Anh; Yang, Hsuan-Chia; Huang, Chih-Wei; Li, Yu-Chuan Jack; Jian, Wen-Shan; Tsai, Shin-Han

2015-12-01

Drug-drug interactions have long been an active research area in clinical medicine. In Taiwan, however, the widespread use of traditional Chinese medicines (TCM) presents additional complexity to the topic. Therefore, it is important to see the interaction between traditional Chinese and western medicine. (1) To create a comprehensive database of multi-herb/western drug interactions indexed according to the ways in which physicians actually practice and (2) to measure this database's impact on the detection of adverse effects between traditional Chinese medicine compounds and western medicines. First, a multi-herb/western medicine drug interactions database was created by separating each TCM compound into its constituent herbs. Each individual herb was then checked against an existing single-herb/western drug interactions database. The data source comes from the National Health Insurance research database, which spans the years 1998-2011. This study estimated the interaction prevalence rate and further separated the rates according to patient characteristics, distribution by county, and hospital accreditation levels. Finally, this new database was integrated into a computer order entry module of the electronic medical records system of a regional teaching hospital. The effects it had were measured for two months. The most commonly interacting Chinese herbs were Ephedrae Herba and Angelicae Sinensis Radix/Angelicae Dahuricae Radix. Ephedrae Herba contains active ingredients similar to in ephedrine. 15 kinds of traditional Chinese medicine compounds contain Ephedrae Herba. Angelicae Sinensis Radix and Angelicae Dahuricae Radix contain ingredients similar to coumarin, a blood thinner. 9 kinds of traditional Chinese medicine compounds contained Angelicae Sinensis Radix/Angelicae Dahuricae Radix. In the period from 1998 to 2011, the prevalence of herb-drug interactions related to Ephedrae Herba was 0.18%. The most commonly prescribed traditional Chinese compounds were

Pharmacokinetic and pharmacodynamic drug interactions with ethanol (alcohol).

PubMed

Chan, Lingtak-Neander; Anderson, Gail D

2014-12-01

Ethanol (alcohol) is one of the most widely used legal drugs in the world. Ethanol is metabolized by alcohol dehydrogenase (ADH) and the cytochrome P450 (CYP) 2E1 drug-metabolizing enzyme that is also responsible for the biotransformation of xenobiotics and fatty acids. Drugs that inhibit ADH or CYP2E1 are the most likely theoretical compounds that would lead to a clinically significant pharmacokinetic interaction with ethanol, which include only a limited number of drugs. Acute ethanol primarily alters the pharmacokinetics of other drugs by changing the rate and extent of absorption, with more limited effects on clearance. Both acute and chronic ethanol use can cause transient changes to many physiologic responses in different organ systems such as hypotension and impairment of motor and cognitive functions, resulting in both pharmacokinetic and pharmacodynamic interactions. Evaluating drug interactions with long-term use of ethanol is uniquely challenging. Specifically, it is difficult to distinguish between the effects of long-term ethanol use on liver pathology and chronic malnutrition. Ethanol-induced liver disease results in decreased activity of hepatic metabolic enzymes and changes in protein binding. Clinical studies that include patients with chronic alcohol use may be evaluating the effects of mild cirrhosis on liver metabolism, and not just ethanol itself. The definition of chronic alcohol use is very inconsistent, which greatly affects the quality of the data and clinical application of the results. Our study of the literature has shown that a significantly higher volume of clinical studies have focused on the pharmacokinetic interactions of ethanol and other drugs. The data on pharmacodynamic interactions are more limited and future research addressing pharmacodynamic interactions with ethanol, especially regarding the non-central nervous system effects, is much needed.

Prolonged Drug-Drug Interaction between Terbinafine and Perphenazine.

PubMed

Park, Young-Min

2012-12-01

I report here an elderly woman receiving perphenazine together with terbinafine. After 1 week of terbinafine treatment she experienced extrapyramidal symptoms and, in particular, akathisia. Her symptoms did not disappear for 6 weeks, and so at 2 weeks prior to this most recent admission she had stopped taking terbinafine. However, these symptoms persisted for 3 weeks after discontinuing terbinafine. It is well known that terbinafine inhibits CYP2D6 and that perphenazine is metabolized mainly by CYP2D6. Thus, when terbinafine and perphenazine are coadministrated, the subsequent increase in the concentration of perphenazine may induce extrapyramidal symptoms. Thus, terbinafine therapy may be associated with the induction and persistence of extrapyramidal symptoms, including akathisia. This case report emphasizes the importance of monitoring drug-drug interactions in patients undergoing terbinafine and perphenazine therapy.

Detecting signals of drug-drug interactions in a spontaneous reports database.

PubMed

Thakrar, Bharat T; Grundschober, Sabine Borel; Doessegger, Lucette

2007-10-01

The spontaneous reports database is widely used for detecting signals of ADRs. We have extended the methodology to include the detection of signals of ADRs that are associated with drug-drug interactions (DDI). In particular, we have investigated two different statistical assumptions for detecting signals of DDI. Using the FDA's spontaneous reports database, we investigated two models, a multiplicative and an additive model, to detect signals of DDI. We applied the models to four known DDIs (methotrexate-diclofenac and bone marrow depression, simvastatin-ciclosporin and myopathy, ketoconazole-terfenadine and torsades de pointes, and cisapride-erythromycin and torsades de pointes) and to four drug-event combinations where there is currently no evidence of a DDI (fexofenadine-ketoconazole and torsades de pointes, methotrexade-rofecoxib and bone marrow depression, fluvastatin-ciclosporin and myopathy, and cisapride-azithromycine and torsade de pointes) and estimated the measure of interaction on the two scales. The additive model correctly identified all four known DDIs by giving a statistically significant (P < 0.05) positive measure of interaction. The multiplicative model identified the first two of the known DDIs as having a statistically significant or borderline significant (P < 0.1) positive measure of interaction term, gave a nonsignificant positive trend for the third interaction (P = 0.27), and a negative trend for the last interaction. Both models correctly identified the four known non interactions by estimating a negative measure of interaction. The spontaneous reports database is a valuable resource for detecting signals of DDIs. In particular, the additive model is more sensitive in detecting such signals. The multiplicative model may further help qualify the strength of the signal detected by the additive model.

Drug-target interaction prediction via class imbalance-aware ensemble learning.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2016-12-22

Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of predicting new undiscovered interactions. However, a key challenge regarding this data that has not yet been addressed by these methods, namely class imbalance, is potentially degrading the prediction performance. Class imbalance can be divided into two sub-problems. Firstly, the number of known interacting drug-target pairs is much smaller than that of non-interacting drug-target pairs. This imbalance ratio between interacting and non-interacting drug-target pairs is referred to as the between-class imbalance. Between-class imbalance degrades prediction performance due to the bias in prediction results towards the majority class (i.e. the non-interacting pairs), leading to more prediction errors in the minority class (i.e. the interacting pairs). Secondly, there are multiple types of drug-target interactions in the data with some types having relatively fewer members (or are less represented) than others. This variation in representation of the different interaction types leads to another kind of imbalance referred to as the within-class imbalance. In within-class imbalance, prediction results are biased towards the better represented interaction types, leading to more prediction errors in the less represented interaction types. We propose an ensemble learning method that incorporates techniques to address the issues of between-class imbalance and within-class imbalance. Experiments show that the proposed method improves results over 4 state-of-the-art methods. In addition, we simulated cases for new drugs and targets to see how our method would perform in predicting their interactions. New drugs and targets are those for which no prior interactions are known. Our method displayed satisfactory prediction performance and was

Validation of a microdose probe drug cocktail for clinical drug interaction assessments for drug transporters and CYP3A.

PubMed

Prueksaritanont, T; Tatosian, D A; Chu, X; Railkar, R; Evers, R; Chavez-Eng, C; Lutz, R; Zeng, W; Yabut, J; Chan, G H; Cai, X; Latham, A H; Hehman, J; Stypinski, D; Brejda, J; Zhou, C; Thornton, B; Bateman, K P; Fraser, I; Stoch, S A

2017-04-01

A microdose cocktail containing midazolam, dabigatran etexilate, pitavastatin, rosuvastatin, and atorvastatin has been established to allow simultaneous assessment of a perpetrator impact on the most common drug metabolizing enzyme, cytochrome P450 (CYP)3A, and the major transporters organic anion-transporting polypeptides (OATP)1B, breast cancer resistance protein (BCRP), and MDR1 P-glycoprotein (P-gp). The clinical utility of these microdose cocktail probe substrates was qualified by conducting clinical drug interaction studies with three inhibitors with different in vitro inhibitory profiles (rifampin, itraconazole, and clarithromycin). Generally, the pharmacokinetic profiles of the probe substrates, in the absence and presence of the inhibitors, were comparable to their reported corresponding pharmacological doses, and/or in agreement with theoretical expectations. The exception was dabigatran, which resulted in an approximately twofold higher magnitude for microdose compared to conventional dosing, and, thus, can be used to flag a worst-case scenario for P-gp. Broader application of the microdose cocktail will facilitate a more comprehensive understanding of the roles of drug transporters in drug disposition and drug interactions. © 2016 American Society for Clinical Pharmacology and Therapeutics.

Drug-food interaction counseling programs in teaching hospitals.

PubMed

Wix, A R; Doering, P L; Hatton, R C

1992-04-01

The results of a survey to characterize drug-food interaction counseling programs in teaching hospitals and solicit opinions on these programs from pharmacists and dietitians are reported. A questionnaire was mailed to the pharmacy director and the director of dietary services at teaching hospitals nationwide. The questionnaire contained 33 questions relating to hospital characteristics, drug-food interaction counseling programs, and the standard calling for such programs issued by the Joint Commission on Accreditation of Healthcare Organizations. Of 792 questionnaires mailed, 425 were returned (response rate, 53.7). A majority of the pharmacists and dietitians (51.2%) did not consider their drug-food interaction counseling program to be formal; some had no program. The pharmacy department was involved more in program development than in the daily operation of such programs. The most frequent methods of identifying patients for counseling were using lists of patients' drugs and using physicians' orders. A mean of only five drugs were targeted per program. Slightly over half the respondents rated the Joint Commission standard less effective than other standards in its ability to improve patient care. A majority of teaching hospitals did not have formal drug-food interaction counseling programs. Pharmacists and dietitians did not view these programs as greatly beneficial and did not believe that the Joint Commission has clearly delineated the requirements for meeting its standard.

Clinical Confirmation that the Selective JAK1 Inhibitor Filgotinib (GLPG0634) has a Low Liability for Drug-drug Interactions.

PubMed

Namour, Florence; Desrivot, Julie; Van der Aa, Annegret; Harrison, Pille; Tasset, Chantal; van't Klooster, Gerben

2016-01-01

The selective Janus kinase 1 inhibitor filgotinib (GLPG0634), which is currently in clinical development for the treatment of rheumatoid arthritis (RA) and Crohn's disease, demonstrated encouraging safety and efficacy profiles in RA patients after 4 weeks of daily dosing. As RA patients might be treated with multiple medications simultaneously, possible drug-drug interactions of filgotinib with cytochrome P450 enzymes and with key drug transporters were evaluated in vitro and in clinical studies. The enzymes involved in filgotinib's metabolism and the potential interactions of the parent and its active major metabolite with drug-metabolizing enzymes and drug transporters, were identified using recombinant enzymes, human microsomes, and cell systems. Furthermore, filgotinib's interaction potential with CYP3A4 was examined in an open-label study in healthy volunteers, which evaluated the impact of filgotinib co-administration on the CYP3A4-sensitive substrate midazolam. The potential interaction with the common RA drug methotrexate was investigated in a clinical study in RA patients. In vitro, filgotinib and its active metabolite at clinically relevant concentrations did not interact with cytochrome P450 enzymes and uridine 5'-diphospho-glucuronosyltransferases, and did not inhibit key drug transporters. In the clinic, a lack of relevant pharmacokinetic drug interactions by filgotinib and its active metabolite with substrates of CYP3A4, as well as with organic anion transporters involved in methotrexate elimination were found. the collective in vivo and in vitro data on drug-metabolizing enzymes and on key drug transporters, support co-administration of filgotinib with commonly used RA drugs to patients without the need for dose adjustments.

Food and drug interaction: consequences for the nutrition/health status.

PubMed

Genser, Dieter

2008-01-01

Food-drug interactions are defined as alterations of pharmacokinetics or pharmacodynamics of a drug or nutritional element or a compromise in nutritional status as a result of the addition of a drug. Elderly patients are particularly at risk because more than 30% of all the prescription drugs are taken by this population. Failure to identify and properly manage drug-nutrient interactions can lead to serious consequences. For instance, drug-nutrient interactions can result in reduced absorption of certain oral antibiotics and may lead to suboptimal antibiotic concentrations at the site of infection. This predisposes the patient to treatment failure. Induction or inhibition of enzymes in the gut by nutrients may lead to a significant change in oral bioavailability of drugs or vice versa. For example, grapefruit juice is a selective intestinal CYP3A4 inhibitor. The overall exposure of some drugs can be increased by more than fivefold when taken with grapefruit juice and increase the risk of adverse effects. The use of certain drugs may affect GI tract function and may lead to a loss of bodily electrolytes and fluid. Limiting drug prescriptions to essential medications for as short a period as possible and periodic re-evaluations of the treatment chosen are essential to minimize adverse drug-nutrient interactions. Copyright 2008 S. Karger AG, Basel.

Drug-drug interaction and doping: Effect of non-prohibited drugs on the urinary excretion profile of methandienone.

PubMed

Mazzarino, Monica; Khevenhüller-Metsch, Franziska L; Fiacco, Ilaria; Parr, Maria Kristina; de la Torre, Xavier; Botrè, Francesco

2018-05-15

The potential consequences of drug-drug interactions on the excretion profile of the anabolic androgenic steroid methandienone (17β-hydroxy-17α-methylandrosta-1,4-dien-3-one) are discussed here. More specifically, we have evaluated by in vitro and in vivo experiments the effects of seven non-prohibited drugs (fluconazole, ketoconazole, itraconazole, miconazole, fluoxetine, paroxetine and nefazodone) on the main metabolic pathways of methandienone. These are selected among those most commonly used by the athletes. The in vitro assays were based on the use of human liver microsomes, specific recombinant enzyme isoforms of cytochrome P450 and uridine 5'-diphospho-glucuronosyl-transferase. The in vivo study was performed by analyzing urines collected after the oral administration of methandienone with and without the co-administration of ketoconazole. Methandienone and its metabolites were determined by liquid chromatography-mass spectrometry-based techniques after sample pre-treatment including an enzymatic hydrolysis step (performed only for the investigation on phase II metabolism) and liquid/liquid extraction with t-butyl methyl-ether. The results from the in vitro experiments showed that the formation of the hydroxylated and dehydrogenated metabolites was significantly reduced in the presence of itraconazole, ketoconazole, miconazole and nefazodone, whereas the production of the 18-nor-hydroxylated metabolites and glucuronidation reactions was reduced significantly only in the presence of ketoconazole and miconazole. The analysis of the post-administration samples confirmed the in vitro observations, validating the hypothesis that drug-drug interaction may cause significant alterations in the metabolic profile of banned drugs, making their detection during doping control tests more challenging. This article is protected by copyright. All rights reserved.

Evaluation of drug interaction microcomputer software: comparative study.

PubMed

Poirier, T I; Giudici, R

1991-01-01

Twelve drug interaction microcomputer software programs were evaluated and compared using general and specific criteria. This article summarizes and compares the features, ratings, advantages, and disadvantages of each program. Features of an ideal drug interaction program are noted. Recommended programs based on three price ranges are suggested.

iDrug: a web-accessible and interactive drug discovery and design platform

PubMed Central

2014-01-01

Background The progress in computer-aided drug design (CADD) approaches over the past decades accelerated the early-stage pharmaceutical research. Many powerful standalone tools for CADD have been developed in academia. As programs are developed by various research groups, a consistent user-friendly online graphical working environment, combining computational techniques such as pharmacophore mapping, similarity calculation, scoring, and target identification is needed. Results We presented a versatile, user-friendly, and efficient online tool for computer-aided drug design based on pharmacophore and 3D molecular similarity searching. The web interface enables binding sites detection, virtual screening hits identification, and drug targets prediction in an interactive manner through a seamless interface to all adapted packages (e.g., Cavity, PocketV.2, PharmMapper, SHAFTS). Several commercially available compound databases for hit identification and a well-annotated pharmacophore database for drug targets prediction were integrated in iDrug as well. The web interface provides tools for real-time molecular building/editing, converting, displaying, and analyzing. All the customized configurations of the functional modules can be accessed through featured session files provided, which can be saved to the local disk and uploaded to resume or update the history work. Conclusions iDrug is easy to use, and provides a novel, fast and reliable tool for conducting drug design experiments. By using iDrug, various molecular design processing tasks can be submitted and visualized simply in one browser without installing locally any standalone modeling softwares. iDrug is accessible free of charge at http://lilab.ecust.edu.cn/idrug. PMID:24955134

Cytochrome P450 drug interactions with statin therapy.

PubMed

Goh, Ivanna Xin Wei; How, Choon How; Tavintharan, Subramaniam

2013-03-01

Statins are commonly used in the treatment of hyperlipidaemia. Although the benefits of statins are well-documented, they have the potential to cause myopathy and rhabdomyolysis due to the complex interactions of drugs, comorbidities and genetics. The cytochrome P450 family consists of major enzymes involved in drug metabolism and bioactivation. This article aims to highlight drug interactions involving statins, as well as provide updated recommendations and approaches regarding the safe and appropriate use of statins in the primary care setting.

Herb-drug interactions. Interactions between saw palmetto and prescription medications.

PubMed

Bressler, Rubin

2005-11-01

Patients over age 50 typically present with one chronic disease per decade. Each chronic disease typically requires long-term drug therapy, meaning most older patients require several drugs to maintain health. Simultaneously, use of complementary and alternative medicine (CAM) has increased in the United States in the last 20 years, reaching 36% in 2002; herbal medicine use accounts for approximately 22% of all CAM use. Older adults often add herbal medicines to prescription medications, yet do not always inform their physicians. The drug metabolizing enzyme systems process all compounds foreign to the body, including prescription and herbal medications. Therefore use of both medicinals simultaneously has a potential for adverse interactions. This review, which discusses saw palmetto, is the last in a series covering the documented interactions among the top 5 efficacious herbal medicines and prescription drugs.

Cytochrome P450 enzyme mediated herbal drug interactions (Part 2)

PubMed Central

Wanwimolruk, Sompon; Phopin, Kamonrat; Prachayasittikul, Virapong

2014-01-01

To date, a number of significant herbal drug interactions have their origins in the alteration of cytochrome P450 (CYP) activity by various phytochemicals. Among the most noteworthy are those involving St. John's wort and drugs metabolized by human CYP3A4 enzyme. This review article is the continued work from our previous article (Part 1) published in this journal (Wanwimolruk and Prachayasittikul, 2014[ref:133]). This article extends the scope of the review to six more herbs and updates information on herbal drug interactions. These include black cohosh, ginseng, grape seed extract, green tea, kava, saw palmetto and some important Chinese medicines are also presented. Even though there have been many studies to determine the effects of herbs and herbal medicines on the activity of CYP, most of them were in vitro and in animal studies. Therefore, the studies are limited in predicting the clinical relevance of herbal drug interactions. It appeared that the majority of the herbal medicines have no clear effects on most of the CYPs examined. For example, the existing clinical trial data imply that black cohosh, ginseng and saw palmetto are unlikely to affect the pharmacokinetics of conventional drugs metabolized by human CYPs. For grape seed extract and green tea, adverse herbal drug interactions are unlikely when they are concomitantly taken with prescription drugs that are CYP substrates. Although there were few clinical studies on potential CYP-mediated interactions produced by kava, present data suggest that kava supplements have the ability to inhibit CYP1A2 and CYP2E1 significantly. Therefore, caution should be taken when patients take kava with CYP1A2 or CYP2E1 substrate drugs as it may enhance their therapeutic and adverse effects. Despite the long use of traditional Chinese herbal medicines, little is known about the potential drug interactions with these herbs. Many popularly used Chinese medicines have been shown in vitro to significantly change the

RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.

PubMed

Wang, Lei; You, Zhu-Hong; Chen, Xing; Yan, Xin; Liu, Gang; Zhang, Wei

2018-01-01

Identification of interaction between drugs and target proteins plays an important role in discovering new drug candidates. However, through the experimental method to identify the drug-target interactions remain to be extremely time-consuming, expensive and challenging even nowadays. Therefore, it is urgent to develop new computational methods to predict potential drugtarget interactions (DTI). In this article, a novel computational model is developed for predicting potential drug-target interactions under the theory that each drug-target interaction pair can be represented by the structural properties from drugs and evolutionary information derived from proteins. Specifically, the protein sequences are encoded as Position-Specific Scoring Matrix (PSSM) descriptor which contains information of biological evolutionary and the drug molecules are encoded as fingerprint feature vector which represents the existence of certain functional groups or fragments. Four benchmark datasets involving enzymes, ion channels, GPCRs and nuclear receptors, are independently used for establishing predictive models with Rotation Forest (RF) model. The proposed method achieved the prediction accuracy of 91.3%, 89.1%, 84.1% and 71.1% for four datasets respectively. In order to make our method more persuasive, we compared our classifier with the state-of-theart Support Vector Machine (SVM) classifier. We also compared the proposed method with other excellent methods. Experimental results demonstrate that the proposed method is effective in the prediction of DTI, and can provide assistance for new drug research and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Drug-drug interactions between immunosuppressants and antidiabetic drugs in the treatment of post-transplant diabetes mellitus.

PubMed

Vanhove, Thomas; Remijsen, Quinten; Kuypers, Dirk; Gillard, Pieter

2017-04-01

Post-transplant diabetes mellitus is a frequent complication of solid organ transplantation that generally requires treatment with lifestyle interventions and antidiabetic medication. A number of demonstrated and potential pharmacokinetic drug-drug interactions (DDIs) exist between commonly used immunosuppressants and antidiabetic drugs, which are comprehensively summarized in this review. Cyclosporine (CsA) itself inhibits the cytochrome P450 (CYP) 3A4 enzyme and a variety of drug transporters. As a result, it increases exposure to repaglinide and sitagliptin, will likely increase the exposure to nateglinide, glyburide, saxagliptin, vildagliptin and alogliptin, and could theoretically increase the exposure to gliquidone and several sodium-glucose transporter (SGLT)-2 inhibitors. Currently available data, although limited, suggest that these increases are modest and, particularly with regard to gliptins and SGLT-2 inhibitors, unlikely to result in hypoglycemia. The interaction with repaglinide is more pronounced but does not preclude concomitant use if repaglinide dose is gradually titrated. Mycophenolate mofetil and azathioprine do not engage in DDIs with any antidiabetic drug. Although calcineurin inhibitors (CNIs) and mammalian target of rapamycin inhibitors (mTORi) are intrinsically prone to DDIs, their disposition is not influenced by metformin, pioglitazone, sulfonylureas (except possibly glyburide) or insulin. An effect of gliptins on the disposition of CNIs and mTORi is unlikely, but has not been definitively ruled out. Based on their disposition profiles, glyburide and canagliflozin could affect CNI and mTORi disposition although this requires further study. Finally, delayed gastric emptying as a result of glucagon-like peptide-1 agonists seems to have a limited, but not necessarily negligible effect on CNI disposition. Copyright © 2016 Elsevier Inc. All rights reserved.

Drug-nutrient interactions.

PubMed

Thomas, J A

1995-10-01

Nutrition status plays a significant role in a drug's pharmacodynamics. Some disease states and other special conditions affect nutrient status and a drug's therapeutic efficacy. Many classes of drugs, including antimicrobials, hypoglycemics, and hypocholesterolemic agents, can be affected by the presence of food, with the geriatric patient particularly at risk. While a drug's pharmacokinetic profile can usually be predicted, it can be modified by nutrients and by certain pathophysiologic conditions, including aging, hepatic dysfunction, and micronutrients.

Drug-disease interactions: narrative review of aspirin in gastric ulcer.

PubMed

Nwose, Ezekiel Uba; Yee, Kwang Choon

2016-09-01

Drug-disease interactions include the impact of a drug and a particular disease condition on each other. However, the current practice in addressing drug-disease interaction is unbalanced and mostly limited to how the drug worsens the disease or health condition. Aspirin and gastric ulcer interaction are used as an example to illustrate this concept, especially the narration of how disease affects drug efficacy. The number of molecules that make up 100 mg of aspirin is identified with a view to discuss the pharmacokinetics, especially in terms of absorption and distribution. Using hypothetical scenarios, the pharmacodynamics in co-morbidities that could involve gastric ulcer and aspirin are also discussed. There seems to be oversight in definition and description of drug-disease interaction, which is often limited to 'how drug exacerbates disease'. The implication of this limited definition is that the discussions, research and teaching of the topic either lacks information, or are not clear on 'how disease affects drug efficacy'. For example, gastric ulcer has the potential to enhance absorption, bioavailability and therapeutic effects of aspirin, but this is rarely discussed in preference to the probability of gastro-intestinal bleeding side-effect.

Cartilage-targeting drug delivery: can electrostatic interactions help?

PubMed

Bajpayee, Ambika G; Grodzinsky, Alan J

2017-03-01

Current intra-articular drug delivery methods do not guarantee sufficient drug penetration into cartilage tissue to reach cell and matrix targets at the concentrations necessary to elicit the desired biological response. Here, we provide our perspective on the utilization of charge-charge (electrostatic) interactions to enhance drug penetration and transport into cartilage, and to enable sustained binding of drugs within the tissue's highly negatively charged extracellular matrix. By coupling drugs to positively charged nanocarriers that have optimal size and charge, cartilage can be converted from a drug barrier into a drug reservoir for sustained intra-tissue delivery. Alternatively, a wide variety of drugs themselves can be made cartilage-penetrating by functionalizing them with specialized positively charged protein domains. Finally, we emphasize that appropriate animal models, with cartilage thickness similar to that of humans, must be used for the study of drug transport and retention in cartilage.

Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

PubMed

Yu, Hui; Mao, Kui-Tao; Shi, Jian-Yu; Huang, Hua; Chen, Zhi; Dong, Kai; Yiu, Siu-Ming

2018-04-11

Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Computational approaches have exhibited their abilities to predict potential DDIs on a large scale by utilizing pre-market drug properties (e.g. chemical structure). Nevertheless, none of them can predict two comprehensive types of DDIs, including enhancive and degressive DDIs, which increases and decreases the behaviors of the interacting drugs respectively. There is a lack of systematic analysis on the structural relationship among known DDIs. Revealing such a relationship is very important, because it is able to help understand how DDIs occur. Both the prediction of comprehensive DDIs and the discovery of structural relationship among them play an important guidance when making a co-prescription. In this work, treating a set of comprehensive DDIs as a signed network, we design a novel model (DDINMF) for the prediction of enhancive and degressive DDIs based on semi-nonnegative matrix factorization. Inspiringly, DDINMF achieves the conventional DDI prediction (AUROC = 0.872 and AUPR = 0.605) and the comprehensive DDI prediction (AUROC = 0.796 and AUPR = 0.579). Compared with two state-of-the-art approaches, DDINMF shows it superiority. Finally, representing DDIs as a binary network and a signed network respectively, an analysis based on NMF reveals crucial knowledge hidden among DDIs. Our approach is able to predict not only conventional binary DDIs but also comprehensive DDIs. More importantly, it reveals several key points about the DDI network: (1) both binary and signed networks show fairly clear clusters, in which both drug degree and the difference between positive degree and negative degree show significant distribution; (2) the drugs having large degrees tend to have a larger difference between positive degree

Drug interactions with neuromuscular blockers.

PubMed

Feldman, S; Karalliedde, L

1996-10-01

Drugs administered to patients undergoing anaesthesia may complicate the use of the neuromuscular blockers that are given to provide good surgical conditions. The various sites of interaction include actions on motor nerve conduction and spinal reflexes, acetylcholine (ACh) synthesis, mobilisation and release, sensitivity of the motor end plate to ACh and the ease of propagation of the motor action potential. In addition, many drugs affect the pharmacokinetics of neuromuscular blockers, especially as most drugs depend to a greater or lesser extent upon renal excretion. The clinically significant interaction between nondepolarisers and depolarisers may be due to blockade of the pre-synaptic nicotinic receptors by the depolarisers, leading to decreased ACh mobilisation and release. Synergism between nondepolarisers probably results from post-synaptic receptor mechanisms. Volatile anaesthetic agents affect the sensitivity of the motor end-plate (post-synaptic receptor blockade) in addition to having effects on pre-synaptic nicotinic function. The effects of nondepolarisers are likely to be potentiated and their action prolonged by large doses of local anaesthetics due to depression of nerve conduction, depression of ACh formation, mobilisation and release, decreases in post-synaptic receptor channel opening times and reductions in muscular contraction. Most antibacterials have effects on pre-synaptic mechanisms. Procainamide and quinidine principally block nicotinic receptor channels. Magnesium has a marked inhibitory effect on ACh release. Calcium antagonists could theoretically interfere with neurotransmitter release and muscle contractility. Phenytoin and lithium decrease ACh release, whilst corticosteroids and furosemide (frusemide) tend to increase the release of the transmitter. Ecothiopate, tacrine, organophosphates, propanidid, metoclopramide and bambuterol depress cholinesterase activity and prolong the duration of the neuromuscular block. The probability of

Drug-target interaction prediction from PSSM based evolutionary information.

PubMed

Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-01-01

The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Is the clinical relevance of drug-food and drug-herb interactions limited to grapefruit juice and Saint-John's Wort?

PubMed

Mouly, Stéphane; Lloret-Linares, Célia; Sellier, Pierre-Olivier; Sene, Damien; Bergmann, J-F

2017-04-01

An interaction of drug with food, herbs, and dietary supplements is usually the consequence of a physical, chemical or physiologic relationship between a drug and a product consumed as food, nutritional supplement or over-the-counter medicinal plant. The current educational review aims at reminding to the prescribing physicians that the most clinically relevant drug-food interactions may not be strictly limited to those with grapefruit juice and with the Saint John's Wort herbal extract and may be responsible for changes in drug plasma concentrations, which in turn decrease efficacy or led to sometimes life-threatening toxicity. Common situations handled in clinical practice such as aging, concomitant medications, transplant recipients, patients with cancer, malnutrition, HIV infection and those receiving enteral or parenteral feeding may be at increased risk of drug-food or drug-herb interactions. Medications with narrow therapeutic index or potential life-threatening toxicity, e.g., the non-steroidal anti-inflammatory drugs, opioid analgesics, cardiovascular medications, warfarin, anticancer drugs and immunosuppressants may be at risk of significant drug-food interactions to occur. Despite the fact that considerable effort has been achieved to increase patient' and doctor's information and ability to anticipate their occurrence and consequences in clinical practice, a thorough and detailed health history and dietary recall are essential for identifying potential problems in order to optimize patient prescriptions and drug dosing on an individual basis as well as to increase the treatment risk/benefit ratio. Copyright © 2016 Elsevier Ltd. All rights reserved.

Microbiota-drug interactions: Impact on metabolism and efficacy of therapeutics.

PubMed

Wilkinson, Ellen M; Ilhan, Zehra Esra; Herbst-Kralovetz, Melissa M

2018-06-01

The microbiome not only represents a vital modifier of health and disease, but is a clinically important drug target. Therefore, study of the impact of the human microbiome on drug metabolism, toxicity and efficacy is urgently needed. This review focuses on gut and vaginal microbiomes, and the effect of those microbiomes or components thereof on the pharmacokinetics of specific chemotherapeutic agents, immunotherapies, anti-inflammatory and antimicrobial drugs. In some cases, the presence of specific bacterial species within the microbiome can alter the metabolism of certain drugs, such as chemotherapeutic agents and antiviral drugs. These microbiota-drug interactions are identified mostly through studies using germ-free or microbiome-depleted animal models, or by the administration of specific bacterial isolates. The biotransformation of drugs can cause drug-related toxicities; however, biotransformation also provides a mechanism by which drug developers could exploit host microbiota to create more site-specific drugs. Within this review we consider the importance of the route of drug administration and interactions with microbiota at various mucosal sites. Notably, we discuss the potential utility of bacterial therapeutics in altering the microbiome to enhance therapeutic efficacy and clinical outcomes in a personalized fashion. Based on the data to date, there is a clinically important relationship between microbiota and drug metabolism throughout the lifespan; therefore, profiling of the human microbiome will be essential in order to understand the mechanisms by which these microbiota-drug interactions occur and the degree to which this complex interplay affects drug efficacy. Copyright © 2018 Elsevier B.V. All rights reserved.

Food intake attenuates the drug interaction between new quinolones and aluminum.

PubMed

Imaoka, Ayuko; Abiru, Kosuke; Akiyoshi, Takeshi; Ohtani, Hisakazu

2018-01-01

Intestinal absorption of new quinolones is decreased by oral administration of polyvalent metal cations. Some clinical studies have demonstrated this drug - drug interaction is more prominent under fasted condition. However, the effect of food intake on the extent of drug - drug interaction between new quinolones and metal cations remains to be investigated quantitatively and systematically. The aim of this study was to develop an animal model that enables to evaluate the effect of food intake on the extent of drug - drug interaction in the gastrointestinal tract by chelation and to apply the model to evaluate quantitatively the effect of food intake on the drug - drug interaction between two new quinolones, ofloxacin or ciprofloxacin and sucralfate. The rats were orally administered new quinolones (5.3 mg/kg of ofloxacin or 10 mg/kg of ciprofloxacin) with or without 13.3 mg/kg of sucralfate under fasted or fed condition and plasma concentration profiles of new quinolones were monitored. To the fed group, standard breakfast used in human studies was pasted and administered at a dose of 8.8 g/kg. The area under the plasma concentration - time curves (AUC 0-6 ) of ofloxacin and ciprofloxacin under the fasted condition were significantly decreased to 28.8 and 17.1% by co-administration of sucralfate, respectively. On the contrary, sucralfate moderately decreased the AUC 0-6 of ofloxacin and ciprofloxacin to 54.9 and 33.2%, respectively, under fed condition. The effects of sucralfate and food intake on the kinetics of ofloxacin in this study were well consistent with the results of previous clinical trial. The developed animal model quantitatively reproduced the effect of food intake on the drug - drug interaction between ofloxacin and sucralfate. The similar influences were observed for the drug - drug interaction between ciprofloxacin and sucralfate, suggesting that the extent of drug - drug interaction caused by chelation is generally attenuated by food intake.

Potential intravenous drug interactions in intensive care.

PubMed

Moreira, Maiara Benevides; Mesquita, Maria Gefé da Rosa; Stipp, Marluci Andrade Conceição; Paes, Graciele Oroski

2017-07-20

To analyze potential intravenous drug interactions, and their level of severity associated with the administration of these drugs based on the prescriptions of an intensive care unit. Quantitative study, with aretrospective exploratory design, and descriptive statistical analysis of the ICU prescriptions of a teaching hospital from March to June 2014. The sample consisted of 319 prescriptions and subsamples of 50 prescriptions. The mean number of drugs per patient was 9.3 records, and a higher probability of drug interaction inherent to polypharmacy was evidenced. The study identified severe drug interactions, such as concomitant administration of Tramadol with selective serotonin reuptake inhibitor drugs (e.g., Metoclopramide and Fluconazole), increasing the risk of seizures due to their epileptogenic actions, as well as the simultaneous use of Ranitidine-Fentanyl®, which can lead to respiratory depression. A previous mapping of prescriptions enables the characterization of the drug therapy, contributing to prevent potential drug interactions and their clinical consequences. Analisar as potenciais interações medicamentosas intravenosas e seu grau de severidade associadas à administração desses medicamentos a partir das prescrições do Centro de Terapia Intensiva. Estudo quantitativo, tipologia retrospectiva exploratória, com análise estatística descritiva das prescrições medicamentosas do Centro de Terapia Intensiva de um Hospital Universitário, no período de março-junho/2014. A amostra foi composta de 319 prescrições e subamostras de 50 prescrições. Constatou-se que a média de medicamentos por paciente foi de 9,3 registros, e evidenciou-se maior probabilidade para ocorrência de interação medicamentosa inerente à polifarmácia. O estudo identificou interações medicamentosas graves, como a administração concomitante de Tramadol com medicamentos inibidores seletivos da recaptação da serotonina, (exemplo: Metoclopramida e Fluconazol

Simultaneous Assessment of Transporter-Mediated Drug-Drug Interactions Using a Probe Drug Cocktail in Cynomolgus Monkey.

PubMed

Kosa, Rachel E; Lazzaro, Sarah; Bi, Yi-An; Tierney, Brendan; Gates, Dana; Modi, Sweta; Costales, Chester; Rodrigues, A David; Tremaine, Larry M; Varma, Manthena V

2018-06-07

We aim to establish an in vivo preclinical model to enable simultaneous assessment of inhibition potential of an investigational drug on clinically relevant drug transporters, organic anion transporting polypeptide (OATP)1B, breast cancer resistance protein (BCRP), P-glycoprotein (P-gp) and organic anion transporter (OAT)3. Pharmacokinetics of substrate cocktail consisting of pitavastatin (OATP1B substrate), rosuvastatin (OATP1B/BCRP/OAT3), sulfasalazine (BCRP) and talinolol (P-gp) were obtained in cynomolgus monkey - alone or in combination with transporter inhibitors. Single dose rifampicin (30 mg/kg) significantly (p<0.01) increased the plasma exposure of all four drugs, with a marked effect on pitavastatin and rosuvastatin (AUC ratio ~21-39). Elacridar, BCRP/P-gp inhibitor, increased the AUC of sulfasalazine, talinolol, as well as rosuvastatin and pitavastatin. An OAT1/3 inhibitor (probenecid) significantly (p<0.05) impacted the renal clearance of rosuvastatin (~8-fold). In vitro, rifampicin (10μM) inhibited uptake of pitavastatin, rosuvastatin and sulfasalazine by monkey and human primary hepatocytes. Transport studies using membrane vesicles suggested that all probe substrates, except talinolol, are transported by cynoBCRP; while talinolol is a cynoP-gp substrate. Elacridar and rifampicin inhibited both cynoBCRP and cynoP-gp in vitro, indicating potential for in vivo intestinal efflux inhibition. In conclusion, a probe substrate cocktail was validated to simultaneously evaluate perpetrator impact on multiple clinically relevant transporters using the cynomolgus monkey. The results support the use of the cynomolgus monkey as a model that could enable drug-drug interaction risk assessment, before advancing a new molecular entity into clinical development, as well as providing mechanistic insights on transporter-mediated interactions. The American Society for Pharmacology and Experimental Therapeutics.

Studies on Pharmacokinetic Drug Interaction Potential of Vinpocetine

PubMed Central

Manda, Vamshi K.; Avula, Bharathi; Dale, Olivia R.; Chittiboyina, Amar G.; Khan, Ikhlas A.; Walker, Larry A.; Khan, Shabana I.

2015-01-01

Abstract Background Vinpocetine, a semi-synthetic derivative of vincamine, is a popular dietary supplement used for the treatment of several central nervous system related disorders. Despite its wide use, no pharmacokinetic drug interaction studies are reported in the literature. Due to increasing use of dietary supplements in combination with conventional drugs, the risk of adverse effects is on the rise. As a preliminary step to predict a possibility of drug interaction during concomitant use of vinpocetine and conventional drugs, this study was carried out to evaluate the effects of vinpocetine on three main regulators of pharmacokinetic drug interactions namely, cytochromes P450 (CYPs), P-glycoprotein (P-gp), and Pregnane X receptor (PXR). Methods Inhibition of CYPs was evaluated by employing recombinant enzymes. The inhibition of P-gp was determined by calcein-AM uptake method in transfected and wild type MDCKII cells. Modulation of PXR activity was monitored through a reporter gene assay in HepG2 cells. Results Vinpocetine showed a strong inhibition of P-gp (EC50 8 μM) and a moderate inhibition of recombinant CYP3A4 and CYP2D6 (IC50 2.8 and 6.5 μM) with no activity towards CYP2C9, CYP2C19 and CYP1A2 enzymes. In HLM, competitive inhibition of CYP3A4 (IC50 54 and Ki 19 μM) and non-competitive inhibition of CYP2D6 (IC50 19 and Ki 26 μM) was observed. Activation of PXR was observed only at the highest tested concentration of vinpocetine (30 μM) while lower doses were ineffective. Conclusion Strong inhibition of P-gp by vinpocetine is indicative of a possibility of drug interactions by altering the pharmacokinetics of drugs, which are the substrates of P-gp. However, the effects on CYPs and PXR indicate that vinpocetine may not affect CYP-mediated metabolism of drugs, as the inhibitory concentrations are much greater than the expected plasma concentrations in humans. PMID:28930203

Studies on Pharmacokinetic Drug Interaction Potential of Vinpocetine.

PubMed

Manda, Vamshi K; Avula, Bharathi; Dale, Olivia R; Chittiboyina, Amar G; Khan, Ikhlas A; Walker, Larry A; Khan, Shabana I

2015-06-05

Background: Vinpocetine, a semi-synthetic derivative of vincamine, is a popular dietary supplement used for the treatment of several central nervous system related disorders. Despite its wide use, no pharmacokinetic drug interaction studies are reported in the literature. Due to increasing use of dietary supplements in combination with conventional drugs, the risk of adverse effects is on the rise. As a preliminary step to predict a possibility of drug interaction during concomitant use of vinpocetine and conventional drugs, this study was carried out to evaluate the effects of vinpocetine on three main regulators of pharmacokinetic drug interactions namely, cytochromes P450 (CYPs), P-glycoprotein (P-gp), and Pregnane X receptor (PXR). Methods: Inhibition of CYPs was evaluated by employing recombinant enzymes. The inhibition of P-gp was determined by calcein-AM uptake method in transfected and wild type MDCKII cells. Modulation of PXR activity was monitored through a reporter gene assay in HepG2 cells. Results: Vinpocetine showed a strong inhibition of P-gp (EC 50 8 µM) and a moderate inhibition of recombinant CYP3A4 and CYP2D6 (IC 50 2.8 and 6.5 µM) with no activity towards CYP2C9, CYP2C19 and CYP1A2 enzymes. In HLM, competitive inhibition of CYP3A4 (IC 50 54 and K i 19 µM) and non-competitive inhibition of CYP2D6 (IC 50 19 and K i 26 µM) was observed. Activation of PXR was observed only at the highest tested concentration of vinpocetine (30 µM) while lower doses were ineffective. Conclusion: Strong inhibition of P-gp by vinpocetine is indicative of a possibility of drug interactions by altering the pharmacokinetics of drugs, which are the substrates of P-gp. However, the effects on CYPs and PXR indicate that vinpocetine may not affect CYP-mediated metabolism of drugs, as the inhibitory concentrations are much greater than the expected plasma concentrations in humans.

Polypharmacy, drug-drug interactions, and potentially inappropriate medications in older adults with human immunodeficiency virus infection.

PubMed

Greene, Meredith; Steinman, Michael A; McNicholl, Ian R; Valcour, Victor

2014-03-01

To describe the frequency of medication-related problems in older adults with human immunodeficiency virus (HIV) infection. Retrospective chart review. Community. HIV-positive individuals aged 60 and older and age- and sex-matched HIV-negative individuals. Total number of medications, potentially inappropriate medications (PIMs) according to the modified Beers Criteria, anticholinergic drug burden according to the Anticholinergic Risk Scale (ARS), and drug-drug interactions using the Lexi-Interact online drug interactions database. Of 89 HIV-positive participants, most were Caucasian (91%) and male (94%), with a median age of 64 (range 60-82). Common comorbidities included hyperlipidemia, hypertension, and depression. Participants were taking a median of 13 medications (range 2-38), of which only a median of four were antiretrovirals. At least one PIM was prescribed in 46 participants (52%). Sixty-two (70%) participants had at least one Category D (consider therapy modification) drug-drug interaction, and 10 (11%) had a Category X (avoid combination) interaction. One-third of these interactions were between two nonantiretroviral medications. Fifteen participants (17%) had an ARS score of 3 or greater. In contrast, HIV-negative participants were taking a median of six medications, 29% had at least one PIM, and 4% had an ARS score of 3 or greater (P < .05 for each comparison, except P = .07 for anticholinergic burden). HIV-positive older adults have a high frequency of medication-related problems, of which a large portion is due to medications used to treat comorbid diseases. These medication issues were substantially higher than HIV-negative participants. Attention to the principles of geriatric prescribing is needed as this population ages in order to minimize complications from multiple medication use. © Published 2014. This article is a U.S. Government work and is in the public domain in the U.S.A.

Administrative claims analysis of the relationship between warfarin use and risk of hemorrhage including drug-drug and drug-disease interactions.

PubMed

Zhang, Kui; Young, Christopher; Berger, Jan

2006-10-01

Despite the risk of hemorrhage, warfarin is the most commonly used oral anticoagulant today, both as monotherapy and when taken in combination with selected drugs. Warfarin is used most commonly for irregular heartbeat, after a heart attack, and after joint or heart valve replacement surgery. To evaluate the relative risk of hemorrhage in health plan members who received warfarin concomitant with a drug known to cause an interaction or after diagnosis of liver disease or heart failure (HF). A cohort study sample was drawn from an administrative database comprising medical and pharmacy claims for 1.7 million health plan members. A health plan member was defined as anyone who was eligible for pharmacy and medical benefits at any time from October 1, 2003, to September 30, 2004. To be included in the study, a member must have received at least 1 pharmacy claim for warfarin during the study period and been younger than 100 years. Hemorrhage was defined as a diagnosed bleeding episode recorded on a medical claim within 7 calendar days of a fill date for a pharmacy claim (new or refill) for warfarin. The following variables were used to predict the outcome measures: type of drug-drug or drug-disease interaction, patient age and gender, number of unique prescribers during the year for all drugs, specialty of the first prescriber for warfarin, average dose of warfarin, and days of warfarin therapy. Because individuals were followed only during the calendar year under study, the authors have interpreted the days of therapy measured primarily as a control on exposure. The outcome measures are prevalence of drug and disease interactions among members receiving warfarin therapy and the per-patient-per-year and per-member-per-month (PMPM) cost of medical treatment of hemorrhage associated with warfarin therapy including drug and disease interactions. Costs are defined as the total paid amount for a procedure or service after negotiated provider discounts and subtraction of

The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence.

PubMed

El Rawas, Rana; Saria, Alois

2016-03-01

Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug's effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or "agonistic" versus the hostile or "antagonistic" social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence.

[Molecular fundamentals of drug interactions in the therapy of colorectal cancer].

PubMed

Regulska, Katarzyna; Stanisz, Beata; Regulski, Miłosz; Gieremek, Paulina

2014-03-04

Rapid advances in the field of chemotherapy have resulted in the introduction of numerous antineoplastic drugs into clinical practice, which increased the efficiency of patient management. Also the prevalent use of combination treatment based on drug action synergy contributed to the improved clinical effect associated with cytotoxic drug administration. It seems, however, obvious that the multidirectional pharmacotherapy in oncology requires a thorough knowledge of drugs' pharmaceutical behavior in order to maximize their collective action and prevent the occurrence of unintended drug interactions that could potentially impair treatment effectiveness. In fact, drug interactions constitute a serious problem for current oncology primarily resulting from a narrow therapeutic index specific for the majority of anticancer drugs. This, in turn, indicates that even slight deviations of their pharmacokinetics could cause significant clinical consequences, manifested by alteration of the toxicological profile or reduction of therapeutic efficiency. Hence, the investigation of molecular aspects underlying the mechanisms of various drug interactions seems to be essential for proper and safe patient management. The present article is devoted to the extensive subject of drug interactions occurring in the therapy of colorectal cancer. It presents the available literature data on both positive and negative effects of interactions and it discusses their mechanisms complying with their classification into pharmacokinetic and pharmacodynamic ones.

iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking

PubMed Central

Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

2013-01-01

Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks. PMID:24015221

Recommendations for Selecting Drug-Drug Interactions for Clinical Decision Support

PubMed Central

Tilson, Hugh; Hines, Lisa E.; McEvoy, Gerald; Weinstein, David M.; Hansten, Philip D.; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T.; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L.; Huang, Shiew-Mei; Perre, Anthony; Bates, David W.; Poikonen, John; Wittie, Michael A.; Grizzle, Amy J.; Brown, Mary; Malone, Daniel C.

2016-01-01

Purpose To recommend principles for including drug-drug interactions (DDIs) in clinical decision support. Methods A conference series was conducted to improve clinical decision support (CDS) for DDIs. The Content Workgroup met monthly by webinar from January 2013 to February 2014, with two in-person meetings to reach consensus. The workgroup consisted of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information (IT) vendors, and healthcare organizations. Workgroup members addressed four key questions: (1) What process should be used to develop and maintain a standard set of DDIs?; (2) What information should be included in a knowledgebase of standard DDIs?; (3) Can/should a list of contraindicated drug pairs be established?; and (4) How can DDI alerts be more intelligently filtered? Results To develop and maintain a standard set of DDIs for CDS in the United States, we recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated, as only a small set of drug combinations are truly contraindicated. Finally, we recommend more research to identify methods to safely reduce repetitive and less relevant alerts. Conclusion A systematic ongoing process is necessary to select DDIs for alerting clinicians. We anticipate that our recommendations can lead to consistent and clinically relevant content for interruptive DDIs, and thus reduce alert fatigue and improve patient safety. PMID:27045070

Possible drug–drug interaction in dogs and cats resulted from alteration in drug metabolism: A mini review

PubMed Central

Sasaki, Kazuaki; Shimoda, Minoru

2015-01-01

Pharmacokinetic drug–drug interactions (in particular at metabolism) may result in fatal adverse effects in some cases. This basic information, therefore, is needed for drug therapy even in veterinary medicine, as multidrug therapy is not rare in canines and felines. The aim of this review was focused on possible drug–drug interactions in dogs and cats. The interaction includes enzyme induction by phenobarbital, enzyme inhibition by ketoconazole and fluoroquinolones, and down-regulation of enzymes by dexamethasone. A final conclusion based upon the available literatures and author’s experience is given at the end of the review. PMID:26257936

[Predictive factors of clinically significant drug-drug interactions among regimens based on protease inhibitors, non-nucleoside reverse transcriptase inhibitors and raltegravir].

PubMed

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

2016-04-15

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

Quantitative Prediction of Drug–Drug Interactions Involving Inhibitory Metabolites in Drug Development: How Can Physiologically Based Pharmacokinetic Modeling Help?

PubMed Central

Chen, Y; Mao, J; Lin, J; Yu, H; Peters, S; Shebley, M

2016-01-01

This subteam under the Drug Metabolism Leadership Group (Innovation and Quality Consortium) investigated the quantitative role of circulating inhibitory metabolites in drug–drug interactions using physiologically based pharmacokinetic (PBPK) modeling. Three drugs with major circulating inhibitory metabolites (amiodarone, gemfibrozil, and sertraline) were systematically evaluated in addition to the literature review of recent examples. The application of PBPK modeling in drug interactions by inhibitory parent–metabolite pairs is described and guidance on strategic application is provided. PMID:27642087

Timing and Duration of Drug Exposure Affects Outcomes of a Drug-Nutrient Interaction During Ontogeny.

PubMed

Ling, Binbing; Aziz, Caroline; Wojnarowicz, Chris; Olkowski, Andrew; Alcorn, Jane

2010-10-14

Significant drug-nutrient interactions are possible when drugs and nutrients share the same absorption and disposition mechanisms. During postnatal development, the outcomes of drug-nutrient interactions may change with postnatal age since these processes undergo ontogenesis through the postnatal period. Our study investigated the dependence of a significant drug-nutrient interaction (cefepime-carnitine) on the timing and duration of drug exposure relative to postnatal age. Rat pups were administered cefepime (5 mg/kg) twice daily subcutaneously according to different dosing schedules (postnatal day 1-4, 1-8, 8-11, 8-20, or 1-20). Cefepime significantly reduced serum and heart L-carnitine levels in postnatal day 1-4, 1-8 and 8-11 groups and caused severe degenerative changes in ventricular myocardium in these groups. Cefepime also altered the ontogeny of several key L-carnitine homeostasis pathways. The qualitative and quantitative changes in levels of hepatic γ-butyrobetaine hydroxylase mRNA and activity, hepatic trimethyllysine hydroxlase mRNA, intestinal organic cation/carnitine transporter (Octn) mRNA, and renal Octn2 mRNA depended on when during postnatal development the cefepime exposure occurred and duration of exposure. Despite lower levels of heart L-carnitine in earlier postnatal groups, levels of carnitine palmitoyltransferase mRNA and activity, heart Octn2 mRNA and ATP levels in all treatment groups remained unchanged with cefepime exposure. However, changes in other high energy phosphate substrates were noted and reductions in the phosphocreatine/ATP ratio were found in rat pups with normal serum L-carnitine levels. In summary, our data suggest a significant drug-nutrient transport interaction in developing neonates, the nature of which depends on the timing and duration of exposure relative to postnatal age.

Timing and Duration of Drug Exposure Affects Outcomes of a Drug-Nutrient Interaction During Ontogeny

PubMed Central

Ling, Binbing; Aziz, Caroline; Wojnarowicz, Chris; Olkowski, Andrew; Alcorn, Jane

2010-01-01

Significant drug-nutrient interactions are possible when drugs and nutrients share the same absorption and disposition mechanisms. During postnatal development, the outcomes of drug-nutrient interactions may change with postnatal age since these processes undergo ontogenesis through the postnatal period. Our study investigated the dependence of a significant drug-nutrient interaction (cefepime-carnitine) on the timing and duration of drug exposure relative to postnatal age. Rat pups were administered cefepime (5 mg/kg) twice daily subcutaneously according to different dosing schedules (postnatal day 1-4, 1-8, 8-11, 8-20, or 1-20). Cefepime significantly reduced serum and heart L-carnitine levels in postnatal day 1-4, 1-8 and 8-11 groups and caused severe degenerative changes in ventricular myocardium in these groups. Cefepime also altered the ontogeny of several key L-carnitine homeostasis pathways. The qualitative and quantitative changes in levels of hepatic γ-butyrobetaine hydroxylase mRNA and activity, hepatic trimethyllysine hydroxlase mRNA, intestinal organic cation/carnitine transporter (Octn) mRNA, and renal Octn2 mRNA depended on when during postnatal development the cefepime exposure occurred and duration of exposure. Despite lower levels of heart L-carnitine in earlier postnatal groups, levels of carnitine palmitoyltransferase mRNA and activity, heart Octn2 mRNA and ATP levels in all treatment groups remained unchanged with cefepime exposure. However, changes in other high energy phosphate substrates were noted and reductions in the phosphocreatine/ATP ratio were found in rat pups with normal serum L-carnitine levels. In summary, our data suggest a significant drug-nutrient transport interaction in developing neonates, the nature of which depends on the timing and duration of exposure relative to postnatal age. PMID:27721360

Organic Ion Transporters and Statin Drug Interactions.

PubMed

Kellick, Kenneth

2017-11-25

Statin drug-drug interactions (DDIs) are both troublesome to patients as well as costly to medical resources. The ability to predict and avoid these events could lead to improved outcomes as well as patient satisfaction. This review will explore efforts to better understand and predict these interactions specifically related to one drug transport system, the organic anion-transporting polypeptides (OATPs) specifically OATP1B1 and OATP1B3. Since the publication of the discovery of OATPs, there have been various pharmacokinetic models that have been proposed to explain the variation in pharmacokinetic and clinical effects related to the OATPs. The effects in transport activity appear to be partially related to the individual polymorphisms studied. Drug-drug interactions can occur when other drugs compete for the metabolic site on the OATPs. Various medications are identified as substrates and/or inhibitors of the OATPs, thereby complicating the ability to fully predict the impact on levels and effects. All of the models reviewed claim successes but show limited clinical utility. There are specific populations that have been identified, predominately various Asian descendants that require lower doses of statins to avoid adverse events. The concept of attributing these actions to the OATPs has been explored, but current models cannot accurately predict statin blood levels or elimination constants. The current research only points to the differences in the human genome and the single-nucleotide polymorphisms that exist between us. Based upon the currently available studies, there is beginning to be a glimmer in the understanding how different populations respond to statin transport and elimination. Additionally and unfortunately, there are other enzymes to be studied to better predict patient differences. Clearly, there has been much work completed, yet many more questions require answering to better understand these transport proteins.

Drug Interactions of Direct-Acting Oral Anticoagulants.

PubMed

Fitzgerald, John Leonard; Howes, Laurence Guy

2016-09-01

In recent years, new direct-acting oral anticoagulants (DOACs) have been introduced into clinical practice that specifically inhibit either factor Ia or Xa. These drugs have, to a large extent, replaced warfarin for the treatment of venous thrombosis, pulmonary embolism, and non-valvular atrial fibrillation. They have potential advantages over warfarin in providing more stable anticoagulation and the lack of a need for regular venesection to monitor activity. They also have the promise of less drug and food interactions. All of these drugs are substrates for the permeability glycoprotein (P-gp) excretion system, and several are metabolised, in part, by cytochrome P450 (CYP) 3A4. This current article assesses the interactions that do or may occur with the DOACs, particularly with respect to the P-gp and CYP3A4 systems.

The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence

PubMed Central

Rawas, Rana El

2016-01-01

Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug’s effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or “agonistic” versus the hostile or “antagonistic” social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence. PMID:26088685

Drug Interactions with Clinafloxacin

PubMed Central

Randinitis, Edward J.; Alvey, Christine W.; Koup, Jeffery R.; Rausch, George; Abel, Robert; Bron, Nicola J.; Hounslow, Neil J.; Vassos, Artemios B.; Sedman, Allen J.

2001-01-01

Many fluoroquinolone antibiotics are inhibitors of cytochrome P450 enzyme systems and may produce potentially important drug interactions when administered with other drugs. Studies were conducted to determine the effect of clinafloxacin on the pharmacokinetics of theophylline, caffeine, warfarin, and phenytoin, as well as the effect of phenytoin on the pharmacokinetics of clinafloxacin. Concomitant administration of 200 or 400 mg of clinafloxacin reduces mean theophylline clearance by approximately 50 and 70%, respectively, and reduces mean caffeine clearance by 84%. (R)-Warfarin concentrations in plasma during clinafloxacin administration are 32% higher and (S)-warfarin concentrations do not change during clinafloxacin treatment. An observed late pharmacodynamic effect was most likely due to gut flora changes. Phenytoin has no effect on clinafloxacin pharmacokinetics, while phenytoin clearance is 15% lower during clinafloxacin administration. PMID:11502527

Interaction between DNA and Drugs Having Protonable Basic Groups: Characterization through Affinity Constants, Drug Release Kinetics, and Conformational Changes

PubMed Central

Alarcón, Liliana P.; Baena, Yolima; Manzo, Rubén H.

2017-01-01

This paper reports the in vitro characterization of the interaction between the phosphate groups of DNA and the protonated species of drugs with basic groups through the determination of the affinity constants, the reversibility of the interaction, and the effect on the secondary structure of the macromolecule. Affinity constants of the counterionic condensation DNA–drug were in the order of 106. The negative electrokinetic potential of DNA decreased with the increase of the proportion of loading drugs. The drugs were slowly released from the DNA–drug complexes and had release kinetics consistent with the high degree of counterionic condensation. The circular dichroism profile of DNA was not modified by complexation with atenolol, lidocaine, or timolol, but was significantly altered by the more lipophilic drugs benzydamine and propranolol, revealing modifications in the secondary structure of the DNA. The in vitro characterization of such interactions provides a physicochemical basis that would contribute to identify the effects of this kind of drugs in cellular cultures, as well as side effects observed under their clinical use. Moreover, this methodology could also be projected to the fields of intracellular DNA transfection and the use of DNA as a carrier of active drugs. PMID:28054999

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

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

Transporter-mediated natural product-drug interactions for the treatment of cardiovascular diseases.

PubMed

Zha, Weibin

2018-04-01

The growing use of natural products in cardiovascular (CV) patients has been greatly raising the concerns about potential natural product-CV drug interactions. Some of these may lead to unexpected cardiovascular adverse effects and it is, therefore, essential to identify or predict potential natural product-CV drug interactions, and to understand the underlying mechanisms. Drug transporters are important determinants for the pharmacokinetics of drugs and alterations of drug transport has been recognized as one of the major causes of natural product-drug interactions. In last two decades, many CV drugs (e.g., angiotensin II receptor blockers, beta-blockers and statins) have been identified to be substrates and inhibitors of the solute carrier (SLC) transporters and the ATP-binding cassette (ABC) transporters, which are two major transporter superfamilies. Meanwhile, in vitro and in vivo studies indicate that a growing number of natural products showed cardioprotective effects (e.g., gingko biloba, danshen and their active ingredients) are also substrates and inhibitors of drug transporters. Thus, to understand transporter-mediated natural product-CV drug interactions is important and some transporter-mediated interactions have already shown to have clinical relevance. In this review, we review the current knowledge on the role of ABC and SLC transporters in CV therapy, as well as transporter modulation by natural products used in CV diseases and their induced natural product-CV drug interactions through alterations of drug transport. We hope our review will aid in a comprehensive summary of transporter-mediated natural product-CV drug interactions and help public and physicians understand these type of interactions. Copyright © 2017. Published by Elsevier B.V.

Electrostimulated Release of Neutral Drugs from Polythiophene Nanoparticles: Smart Regulation of Drug-Polymer Interactions.

PubMed

Puiggalí-Jou, Anna; Micheletti, Paolo; Estrany, Francesc; Del Valle, Luis J; Alemán, Carlos

2017-09-01

Poly(3,4-ethylenedioxythiophene) (PEDOT) nanoparticles are loaded with curcumin and piperine by in situ emulsion polymerization using dodecyl benzene sulfonic acid both as a stabilizer and a doping agent. The loaded drugs affect the morphology, size, and colloidal stability of the nanoparticles. Furthermore, kinetics studies of nonstimulated drug release have evidenced that polymer···drug interactions are stronger for curcumin than for piperine. This observation suggests that drug delivery systems based on combination of the former drug with PEDOT are much appropriated to show an externally tailored release profile. This is demonstrated by comparing the release profiles obtained in presence and absence of electrical stimulus. Results indicate that controlled and time-programmed release of curcumin is achieved in a physiological medium by applying a negative voltage of -1.25 V to loaded PEDOT nanoparticles. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drug-drug interactions and adverse drug reactions in polypharmacy among older adults: an integrative review 1

PubMed Central

Rodrigues, Maria Cristina Soares; de Oliveira, Cesar

2016-01-01

ABSTRACT Objective: to identify and summarize studies examining both drug-drug interactions (DDI) and adverse drug reactions (ADR) in older adults polymedicated. Methods: an integrative review of studies published from January 2008 to December 2013, according to inclusion and exclusion criteria, in MEDLINE and EMBASE electronic databases were performed. Results: forty-seven full-text studies including 14,624,492 older adults (≥ 60 years) were analyzed: 24 (51.1%) concerning ADR, 14 (29.8%) DDI, and 9 studies (19.1%) investigating both DDI and ADR. We found a variety of methodological designs. The reviewed studies reinforced that polypharmacy is a multifactorial process, and predictors and inappropriate prescribing are associated with negative health outcomes, as increasing the frequency and types of ADRs and DDIs involving different drug classes, moreover, some studies show the most successful interventions to optimize prescribing. Conclusions: DDI and ADR among older adults continue to be a significant issue in the worldwide. The findings from the studies included in this integrative review, added to the previous reviews, can contribute to the improvement of advanced practices in geriatric nursing, to promote the safety of older patients in polypharmacy. However, more research is needed to elucidate gaps. PMID:27598380

Chromatographic studies of drug interactions with alpha1-acid glycoprotein by ultrafast affinity extraction and peak profiling.

PubMed

Beeram, Sandya; Bi, Cong; Zheng, Xiwei; Hage, David S

2017-05-12

Interactions with serum proteins such as alpha 1 -acid glycoprotein (AGP) can have a significant effect on the behavior and pharmacokinetics of drugs. Ultrafast affinity extraction and peak profiling were used with AGP microcolumns to examine these processes for several model drugs (i.e., chlorpromazine, disopyramide, imipramine, lidocaine, propranolol and verapamil). The association equilibrium constants measured for these drugs with soluble AGP by ultrafast affinity extraction were in the general range of 10 4 -10 6 M -1 at pH 7.4 and 37°C and gave good agreement with literature values. Some of these values were dependent on the relative drug and protein concentrations that were present when using a single-site binding model; these results suggested a more complex mixed-mode interaction was actually present, which was also then used to analyze the data. The apparent dissociation rate constants that were obtained by ultrafast affinity extraction when using a single-site model varied from 0.14 to 7.0s -1 and were dependent on the relative drug and protein concentrations. Lower apparent dissociation rate constants were obtained by this approach as the relative amount of drug versus protein was decreased, with the results approaching those measured by peak profiling at low drug concentrations. This information should be useful in better understanding how these and other drugs interact with AGP in the circulation. In addition, the chromatographic approaches that were optimized and used in this report to examine these systems can be adapted for the analysis of other solute-protein interactions of biomedical interest. Copyright © 2017 Elsevier B.V. All rights reserved.

[Terbinafine : Relevant drug interactions and their management].

PubMed

Dürrbeck, A; Nenoff, P

2016-09-01

The allylamine terbinafine is the probably most frequently prescribed systemic antifungal agent in Germany for the treatment of dermatomycoses and onychomycoses. According to the German drug law, terbinafine is approved for patients who are 18 years and older; however, this antifungal agent is increasingly used off-label for treatment of onychomycoses and tinea capitis in children. Terbinafine is associated with only a few interactions with other drugs, which is why terbinafine can generally be used without problems in older and multimorbid patients. Nevertheless, some potential interactions of terbinafine with certain drug substances are known, including substances of the group of antidepressants/antipsychotics and some cardiovascular drugs. Decisive for the relevance of interactions is-along with the therapeutic index of the substrate and the possible alternative degradation pathways-the genetically determined type of metabolism. When combining terbinafine with tricyclic antidepressants or selective serotonin reuptake inhibitors and serotonin/noradrenalin reuptake inhibitors, the clinical response and potential side effects must be monitored. Problematic is the use of terbinafine with simultaneous treatment with tamoxifen. The administration of potent CYP2D6 inhibitors leads to a diminished efficacy of tamoxifen because one of its most important active metabolites-endoxifen-is not sufficiently available. Therefore, combination of tamoxifen and terbinafine should be avoided. In conclusion, the number of substances which are able to cause clinically relevant interactions in case of simultaneously administration with terbinafine is clear and should be manageable in the dermatological office with adequate monitoring.

Potential for interaction of kava and St. John's wort with drugs.

PubMed

Singh, Yadhu N

2005-08-22

The present interest and widespread use of herbal remedies has created the possibility of interaction between them and pharmaceutical drugs if they are used simultaneously. Before the recent reports of apparent hepatotoxicity associated with its use, kava (Piper methysticum Forst. F.), was one of the top 10 selling herbal remedies in Europe and North America. This adverse effect was not previously encountered with the traditional beverage which was prepared as a water infusion in contrast to the commercial products which are extracted with organic solvents. Kavalactones, the active principles in kava, are potent inhibitors of several of the CYP 450 enzymes, suggesting a high potential for causing pharmacokinetic interactions with drugs and other herbs which are metabolized by the same CYP 450 enzymes. Furthermore, some kavalactones have been shown to possess pharmacological effects, such as blockade of GABA receptors and sodium and calcium ion channels, which may lead to pharmacodynamic interactions with other substances which possess similar pharmacological proprieties. St. John's wort (Hypericum perforatum L.), used extensively for the treatment of mild to moderate clinical depression, has long been considered safer than the conventional pharmaceutical agents. However, its ability, through its active constituents hypericin, pseudohypericin and hyperforin, to induce intestinal P-glycoprotein/MRD1 and both intestinal and hepatic CYP3A4 enzyme, could markedly reduce the distribution and disposition of their co-substrates. In addition, St. John's wort is a potent uptake inhibitor of the neurotransmitters serotonin, norepinephrine and dopamine all of which have a role in mood control. Consequently, the very real potential for a pharmacodynamic interaction between the herb and pharmaceutical drugs which share this mechanism of action and, like St. John's wort, are used for mood elevation. However, presently there is very little evidence to substantiate actual

Computerized techniques pave the way for drug-drug interaction prediction and interpretation

PubMed Central

Safdari, Reza; Ferdousi, Reza; Aziziheris, Kamal; Niakan-Kalhori, Sharareh R.; Omidi, Yadollah

2016-01-01

Introduction: Health care industry also patients penalized by medical errors that are inevitable but highly preventable. Vast majority of medical errors are related to adverse drug reactions, while drug-drug interactions (DDIs) are the main cause of adverse drug reactions (ADRs). DDIs and ADRs have mainly been reported by haphazard case studies. Experimental in vivo and in vitro researches also reveals DDI pairs. Laboratory and experimental researches are valuable but also expensive and in some cases researchers may suffer from limitations. Methods: In the current investigation, the latest published works were studied to analyze the trend and pattern of the DDI modelling and the impacts of machine learning methods. Applications of computerized techniques were also investigated for the prediction and interpretation of DDIs. Results: Computerized data-mining in pharmaceutical sciences and related databases provide new key transformative paradigms that can revolutionize the treatment of diseases and hence medical care. Given that various aspects of drug discovery and pharmacotherapy are closely related to the clinical and molecular/biological information, the scientifically sound databases (e.g., DDIs, ADRs) can be of importance for the success of pharmacotherapy modalities. Conclusion: A better understanding of DDIs not only provides a robust means for designing more effective medicines but also grantees patient safety. PMID:27525223

Cognitive enhancers (nootropics). Part 3: drugs interacting with targets other than receptors or enzymes. disease-modifying drugs.

PubMed

Froestl, Wolfgang; Pfeifer, Andrea; Muhs, Andreas

2013-01-01

Cognitive enhancers (nootropics) are drugs to treat cognition deficits in patients suffering from Alzheimer's disease, schizophrenia, stroke, attention deficit hyperactivity disorder, or aging. Cognition refers to a capacity for information processing, applying knowledge, and changing preferences. It involves memory, attention, executive functions, perception, language, and psychomotor functions. The term nootropics was coined in 1972 when memory enhancing properties of piracetam were observed in clinical trials. In the meantime, hundreds of drugs have been evaluated in clinical trials or in preclinical experiments. To classify the compounds, a concept is proposed assigning drugs to 19 categories according to their mechanism(s) of action, in particular drugs interacting with receptors, enzymes, ion channels, nerve growth factors, re-uptake transporters, antioxidants, metal chelators, and disease modifying drugs, meaning small molecules, vaccines, and monoclonal antibodies interacting with amyloid-β and tau. For drugs, whose mechanism of action is not known, they are either classified according to structure, e.g., peptides, or their origin, e.g., natural products. The review covers the evolution of research in this field over the last 25 years.

Drug interactions among commonly used medications. Chart simplifies data from critical literature review.

PubMed Central

Crowther, N. R.; Holbrook, A. M.; Kenwright, R.; Kenwright, M.

1997-01-01

OBJECTIVE: To simplify risk assessment, we have developed a way to present critically appraised drug interaction information through a chart. DATA SOURCES: Fifty drugs most frequently prescribed by Canadian family physicians and 16 drugs and substances that frequently interact with these drugs were the basis for a literature review. Drug interaction textbooks and MEDLINE (from 1966 to 1994) were searched for documented interactions. Reports of additive effects and animal or in vitro studies were excluded. STUDY SELECTION: All reports of interactions were evaluated for clinical effect, clinical significance, and quality of evidence. SYNTHESIS: Of the 464 drug-drug or drug-substance pairs evaluated, 387 (83.4%) demonstrated an interaction, 59 (12.7%) documented no effect, and 18 (3.9%) pairs had conflicting evidence. Five percent of interactions were of major clinical significance; only 1.3% were of major clinical significance and supported by good-quality evidence. By using symbols, colours, and legends in a "grid-map" format, a large amount of drug interaction information was reduced to a single-page chart suitable for a desk reference or wall mounting. CONCLUSIONS: Our chart organizes a large amount of drug interaction information in a format that allows for rapid appreciation of outcome, clinical significance, and quality of evidence. PMID:9386884

Adverse drug reactions and drug–drug interactions with over-the-counter NSAIDs

PubMed Central

Moore, Nicholas; Pollack, Charles; Butkerait, Paul

2015-01-01

Nonsteroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen have a long history of safe and effective use as both prescription and over-the-counter (OTC) analgesics/antipyretics. The mechanism of action of all NSAIDs is through reversible inhibition of cyclooxygenase enzymes. Adverse drug reactions (ADRs) including gastrointestinal bleeding as well as cardiovascular and renal effects have been reported with NSAID use. In many cases, ADRs may occur because of drug–drug interactions (DDIs) between the NSAID and a concomitant medication. For example, DDIs have been reported when NSAIDs are coadministered with aspirin, alcohol, some antihypertensives, antidepressants, and other commonly used medications. Because of the pharmacologic nature of these interactions, there is a continuum of risk in that the potential for an ADR is dependent on total drug exposure. Therefore, consideration of dose and duration of NSAID use, as well as the type or class of comedication administered, is important when assessing potential risk for ADRs. Safety findings from clinical studies evaluating prescription-strength NSAIDs may not be directly applicable to OTC dosing. Health care providers can be instrumental in educating patients that using OTC NSAIDs at the lowest effective dose for the shortest required duration is vital to balancing efficacy and safety. This review discusses some of the most clinically relevant DDIs reported with NSAIDs based on major sites of ADRs and classes of medication, with a focus on OTC ibuprofen, for which the most data are available. PMID:26203254

Drug-nutrient interactions: a case and clinical guide.

PubMed

Plotnikoff, Gregory A

2011-10-01

Advances in pharmacokinetics and pharmacodynamics require new competencies related to pharmaceutical prescribing. First, both physicians and pharmacists need to recognize the potential negative impact of nutrients and dietary supplements on the absorption, metabolism, and utilization of prescription drugs. Second, physicians, even more than pharmacists, need to recognize the potential negative effects of pharmaceuticals on the absorption, metabolism, and utilization of nutrients. This article discusses common drug-nutrient interactions and presents a case that illustrates how unrecognized nutrient disruption may negatively affect a patient's health and potentially result in unnecessary prescribing of medications. In presenting the case, we also provide a conceptual framework for assessing and treating this patient and a summary of current knowledge regarding drug-nutrient interactions.

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.

New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.

PubMed

Peletier, Lambertus A; Gabrielsson, Johan

2018-05-14

In vivo analyses of pharmacological data are traditionally based on a closed system approach not incorporating turnover of target and ligand-target kinetics, but mainly focussing on ligand-target binding properties. This study incorporates information about target and ligand-target kinetics parallel to binding. In a previous paper, steady-state relationships between target- and ligand-target complex versus ligand exposure were derived and a new expression of in vivo potency was derived for a circulating target. This communication is extending the equilibrium relationships and in vivo potency expression for (i) two separate targets competing for one ligand, (ii) two different ligands competing for a single target and (iii) a single ligand-target interaction located in tissue. The derived expressions of the in vivo potencies will be useful both in drug-related discovery projects and mechanistic studies. The equilibrium states of two targets and one ligand may have implications in safety assessment, whilst the equilibrium states of two competing ligands for one target may cast light on when pharmacodynamic drug-drug interactions are important. The proposed equilibrium expressions for a peripherally located target may also be useful for small molecule interactions with extravascularly located targets. Including target turnover, ligand-target complex kinetics and binding properties in expressions of potency and efficacy will improve our understanding of within and between-individual (and across species) variability. The new expressions of potencies highlight the fact that the level of drug-induced target suppression is very much governed by target turnover properties rather than by the target expression level as such.

Regulation of drug-metabolizing enzymes in infectious and inflammatory disease: implications for biologics-small molecule drug interactions.

PubMed

Mallick, Pankajini; Taneja, Guncha; Moorthy, Bhagavatula; Ghose, Romi

2017-06-01

Drug-metabolizing enzymes (DMEs) are primarily down-regulated during infectious and inflammatory diseases, leading to disruption in the metabolism of small molecule drugs (smds), which are increasingly being prescribed therapeutically in combination with biologics for a number of chronic diseases. The biologics may exert pro- or anti-inflammatory effect, which may in turn affect the expression/activity of DMEs. Thus, patients with infectious/inflammatory diseases undergoing biologic/smd treatment can have complex changes in DMEs due to combined effects of the disease and treatment. Areas covered: We will discuss clinical biologics-SMD interaction and regulation of DMEs during infection and inflammatory diseases. Mechanistic studies will be discussed and consequences on biologic-small molecule combination therapy on disease outcome due to changes in drug metabolism will be highlighted. Expert opinion: The involvement of immunomodulatory mediators in biologic-SMDs is well known. Regulatory guidelines recommend appropriate in vitro or in vivo assessments for possible interactions. The role of cytokines in biologic-SMDs has been documented. However, the mechanisms of drug-drug interactions is much more complex, and is probably multi-factorial. Studies aimed at understanding the mechanism by which biologics effect the DMEs during inflammation/infection are clinically important.

Drug interaction of levothyroxine with infant colic drops.

PubMed

Balapatabendi, Mihirani; Harris, David; Shenoy, Savitha D

2011-09-01

Infacol (Forest Laboratories UK, Kent, UK) is a widely available over-the-counter preparation used to relieve colic symptoms in neonates and infants. The active ingredient is simeticone. No drug interactions with simeticone are documented in the current summary of product characteristics. The authors report the case of an infant with confirmed congenital hypothyroidism on levothyroxine who experienced a possible drug interaction with simeticone. Despite adequate levothyroxine dosage, thyroid stimulating hormone (TSH) was high, suggesting undertreatment. Questioning revealed the child was taking Infacol drops before feeds while on levothyroxine. The colic drops were immediately discontinued and TSH promptly normalised with a reduction in thyroxine requirement to an age appropriate dosage. Drug interaction of thyroxine with simeticone has not been reported previously and is not listed in the British National Formulary for Children. Clinicians and parents need to be aware of this interaction to avoid unnecessary undertreatment and prevent potential long-term neurological sequelae.

Cognitive enhancers (nootropics). Part 2: drugs interacting with enzymes.

PubMed

Froestl, Wolfgang; Muhs, Andreas; Pfeifer, Andrea

2013-01-01

Cognitive enhancers (nootropics) are drugs to treat cognition deficits in patients suffering from Alzheimer's disease, schizophrenia, stroke, attention deficit hyperactivity disorder, or aging. Cognition refers to a capacity for information processing, applying knowledge, and changing preferences. It involves memory, attention, executive functions, perception, language, and psychomotor functions. The term nootropics was coined in 1972 when memory enhancing properties of piracetam were observed in clinical trials. In the meantime, hundreds of drugs have been evaluated in clinical trials or in preclinical experiments. To classify the compounds, a concept is proposed assigning drugs to 19 categories according to their mechanism(s) of action, in particular drugs interacting with receptors, enzymes, ion channels, nerve growth factors, re-uptake transporters, antioxidants, metal chelators, and disease modifying drugs meaning small molecules, vaccines, and monoclonal antibodies interacting with amyloid-β and tau. For drugs whose mechanism of action is not known, they are either classified according to structure, e.g., peptides, or their origin, e.g., natural products. This review covers the evolution of research in this field over the last 25 years.

Cognitive enhancers (nootropics). Part 1: drugs interacting with receptors.

PubMed

Froestl, Wolfgang; Muhs, Andreas; Pfeifer, Andrea

2012-01-01

Cognitive enhancers (nootropics) are drugs to treat cognition deficits in patients suffering from Alzheimer's disease, schizophrenia, stroke, attention deficit hyperactivity disorder, or aging. Cognition refers to a capacity for information processing, applying knowledge, and changing preferences. It involves memory, attention, executive functions, perception, language, and psychomotor functions. The term nootropics was coined in 1972 when memory enhancing properties of piracetam were observed in clinical trials. In the meantime, hundreds of drugs have been evaluated in clinical trials or in preclinical experiments. To classify the compounds, a concept is proposed assigning drugs to 18 categories according to their mechanism(s) of action, in particular drugs interacting with receptors, enzymes, ion channels, nerve growth factors, re-uptake transporters, antioxidants, metal chelators, and disease-modifying drugs meaning small molecules, vaccines, and monoclonal antibodies interacting with amyloid-β and tau. For drugs, whose mechanism of action is not known, they are either classified according to structure, e.g., peptides, or their origin, e.g., natural products. The review covers the evolution of research in this field over the last 25 years.

Interactions of dendrimers with biological drug targets: reality or mystery - a gap in drug delivery and development research.

PubMed

Ahmed, Shaimaa; Vepuri, Suresh B; Kalhapure, Rahul S; Govender, Thirumala

2016-07-21

Dendrimers have emerged as novel and efficient materials that can be used as therapeutic agents/drugs or as drug delivery carriers to enhance therapeutic outcomes. Molecular dendrimer interactions are central to their applications and realising their potential. The molecular interactions of dendrimers with drugs or other materials in drug delivery systems or drug conjugates have been extensively reported in the literature. However, despite the growing application of dendrimers as biologically active materials, research focusing on the mechanistic analysis of dendrimer interactions with therapeutic biological targets is currently lacking in the literature. This comprehensive review on dendrimers over the last 15 years therefore attempts to identify the reasons behind the apparent lack of dendrimer-receptor research and proposes approaches to address this issue. The structure, hierarchy and applications of dendrimers are briefly highlighted, followed by a review of their various applications, specifically as biologically active materials, with a focus on their interactions at the target site. It concludes with a technical guide to assist researchers on how to employ various molecular modelling and computational approaches for research on dendrimer interactions with biological targets at a molecular level. This review highlights the impact of a mechanistic analysis of dendrimer interactions on a molecular level, serves to guide and optimise their discovery as medicinal agents, and hopes to stimulate multidisciplinary research between scientific, experimental and molecular modelling research teams.

Characterization of the interaction forces in a drug carrier complex of doxorubicin with a drug-binding peptide.

PubMed

Gocheva, Gergana; Ilieva, Nina; Peneva, Kalina; Ivanova, Anela

2018-04-01

Polypeptide-based materials are used as building blocks for drug delivery systems aimed at toxicity decrease in chemotherapeutics. A molecular-level approach is adopted for investigating the non-covalent interactions between doxorubicin and a recently synthesized drug-binging peptide as a key part of a system for delivery to neoplastic cells. Molecular dynamics simulations in aqueous solution at room and body temperature are applied to investigate the structure and the binding modes within the drug-peptide complex. The tryptophans are outlined as the main chemotherapeutic adsorption sites, and the importance of their placement in the peptide sequence is highlighted. The drug-peptide binging energy is evaluated by density functional theory calculations. Principal component analysis reveals comparable importance of several types of interaction for the binding strength. π-Stacking is dominant, but other factors are also significant: intercalation, peptide backbone stacking, electrostatics, dispersion, and solvation. Intra- and intermolecular H-bonding also stabilizes the complexes. The influence of solvent molecules on the binding energy is mild. The obtained data characterize the drug-to-peptide attachment as a mainly attractive collective process with interactions spanning a broad range of values. These results explain with atomistic detail the experimentally registered doxorubicin-binging ability of the peptide and outline the complex as a prospective carrying unit that can be employed in design of drug delivery systems. © 2017 John Wiley & Sons A/S.

Drug-nutrient interactions in the intensive care unit: literature review and current recommendations.

PubMed

Heldt, Tatiane; Loss, Sergio Henrique

2013-01-01

To describe the interactions between drugs and nutrients and their frequency in the intensive care unit and to assess the professional team's awareness regarding this subject. The keywords "drug interactions" and "nutrition therapy" were searched in the PubMed (specifically MeSH) electronic database. The studies were systematically reviewed for descriptions of the types of interactions between drugs and nutrients, including their frequency and consequences. Sixty-seven articles were found. Among these, 20 articles were appropriate for the methodology adopted and accomplished the objectives of the study. Of these 20 articles, 14 articles described interactions between drugs and enteral nutrition, three described interactions between drugs and parenteral nutrition, and three described the importance and care required to avoid such interactions. The literature about drug and nutrient interactions is limited and suggests the inability of health care teams to recognize the potential for these interactions. Possibly, the elaboration of a protocol to evaluate drug-nutrient interactions will increase the safety and efficacy of therapeutics.

eDrug: a dynamic interactive electronic drug formulary for medical students

PubMed Central

Maxwell, Simon R J; McQueen, Daniel S; Ellaway, Rachel

2006-01-01

What is already known about this subject Delivering education about an ever-increasing number of prescribable drugs to medical students represents a major challenge. Drug names are generally not logical or intuitive, and many students find learning them akin to learning a foreign language. Pharmacology and therapeutics teaching is struggling for visibility in some integrated medical curricula. What this study adds Development of electronic tools allowing web delivery of a restricted student formulary facilitates dynamic access to core learning materials, improves the profile of this aspect of the curriculum and is highly appreciated by students. Aims Prescribing drugs is a key responsibility of a doctor and requires a solid grounding in the relevant scientific disciplines of pharmacology and therapeutics (PT). The move away from basic science disciplines towards a more system-based and integrated undergraduate curriculum has created difficulties in the delivery of PT teaching in some medical schools. We aimed to develop a web-based strategy to overcome these problems and improve the PT learning experience. Methods We designed and introduced ‘eDrug’, a dynamic interactive web-based student formulary, as an aid to teaching and learning of PT throughout a 5-year integrated medical curriculum in a UK medical school of 1300 students. This was followed by a prospective observational study of student-reported views about its impact on their PT learning experience. Results eDrug was rated highly by students and staff, with the main benefits being increased visibility of PT in the curriculum, clear identification of core drugs, regular sourcing of drug information via direct links to accredited sources including the British National Formulary, prioritization of learning, immediate access and responsiveness. It has also served as a focus of discussion concerning core PT learning objectives amongst staff and students. Conclusions Web-based delivery of PT learning

OTC analgesics and drug interactions: clinical implications

PubMed Central

Fendrick, A Mark; Pan, Deborah E; Johnson, Grace E

2008-01-01

The risk of drug interactions with concurrent use of multiple medications is a clinically relevant issue. Many patients are unaware that over-the-counter (OTC) analgesics can cause potentially serious adverse effects when used in combination with other common medications such as anticoagulants, corticosteroids, or antihypertensive agents. Of particular significance is the increased risk of upper abdominal gastrointestinal adverse events in patients who take traditional nonsteroidal anti-inflammatory drugs (NSAIDs). This risk is dose dependent and further increased in patients who take more than one NSAID or use NSAIDs in combination with certain other medications. Some NSAIDs may also mitigate the antiplatelet benefits of aspirin and may increase blood pressure in patients with hypertension. Clinicians should be aware of potential drug interactions with OTC analgesics when prescribing new medications. Additionally, patients should be properly counseled on the appropriate and safe use of OTC analgesics. PMID:18257920

A facile drug delivery system preparation through the interaction between drug and iron ion of transferrin

NASA Astrophysics Data System (ADS)

Zhou, Lin; Liu, Jihua; Wei, Shaohua; Ge, Xuefeng; Zhou, Jiahong; Yu, Boyang; Shen, Jian

2013-09-01

Many anticancer drugs have the capability to form stable complex with metal ions. Based on such property, a simple method to combine these drugs with transferrin, through the interaction between drug and Fe ion of transferrin, to improve their anticancer activity, is proposed. To demonstrate this technique, the complex of photosensitive anticancer drug hypocrellin A and transferrin was prepared by such facile method. The results indicated that the complex of hypocrellin A and transferrin can stabilize in aqueous solution. In vitro studies have demonstrated the superior cancer cell uptake ability of hypocrellin A-transferrin complex to the free hypocrellin A. Significant damage to such drug-impregnated tumor cells was observed upon irradiation and the cancer cells killing ability of hypocrellin A-transferrin was stronger than the free hypocrellin A within a certain range of concentrations. The above results demonstrated the validity and potential of our proposed strategy to prepare the drug delivery system of this type of anti-cancer drugs and transferrin.

Drug interactions: volatile anesthetics and opioids.

PubMed

Glass, P S; Gan, T J; Howell, S; Ginsberg, B

1997-09-01

Multiple drugs are used to provide anesthesia. Volatile anesthetics are commonly combined with opioids. Several studies have demonstrated that small doses of opioid (i.e., within the analgesic range) result in a marked reduction in minimum alveolar concentration (MAC) of the volatile anesthetic that will prevent purposeful movement in 50% of patients at skin incision). Further increases in opioid dose provide only a further small reduction in MAC. Thus, a ceiling effect of the opioid is observed at a MAC value of the volatile anesthetic equal to its MAC awake. Recovery from anesthesia when an opioid is combined with a volatile anesthetic is dependent on the rate of decrease of both drugs to their respective concentrations that are associated with adequate spontaneous ventilation and awakening. Through an understanding of the pharmacodynamic interaction of volatile anesthetics with opioids and the pharmacokinetic processes responsible for the recovery from drug effect, optimal dosing schemes can thus be developed. A review of these pharmacodynamic and pharmacokinetic principles that will allow clinicians to administer drugs to provide a more optimal anesthetic is provided.

Pre-Clinical Drug Prioritization via Prognosis-Guided Genetic Interaction Networks

PubMed Central

Xiong, Jianghui; Liu, Juan; Rayner, Simon; Tian, Ze; Li, Yinghui; Chen, Shanguang

2010-01-01

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies. PMID:21085674

Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

PubMed Central

Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

2015-01-01

Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

The drug-drug interaction potential of antiviral agents for the treatment of chronic hepatitis C infection.

PubMed

Garrison, Kimberly L; German, Polina; Mogalian, Erik; Mathias, Anita

2018-04-25

Several safe and highly-effective directly-acting antiviral drugs for chronic hepatitis C virus (HCV) have been developed and greatly increase the number of treatment options available to successfully treat HCV infection. However, as treatment regimens contain at least two drugs (e.g., sofosbuvir with daclatasvir, simeprevir, ledipasvir, or velpatasvir; elbasvir and grazoprevir) and up to five drugs (ombitasvir/paritaprevir/ritonavir+dasabuvir+ribavirin), the potential for drug-drug interactions (DDI) becomes an important consideration for HCV-infected individuals with comorbidities that require concomitant medications, such as HIV/HCV co-infection or immunosuppression following liver transplantation. This review details the pharmacokinetics and DDI potential of approved DAAs for the treatment of HCV infection. The American Society for Pharmacology and Experimental Therapeutics.

In vitro drug interaction of levocetirizine and diclofenac: Theoretical and spectroscopic studies.

PubMed

Abo Dena, Ahmed S; Abdel Gaber, Sara A

2017-06-15

Levocetirizine dihydrochloride is known to interact with some anti-inflammatory drugs. We report here a comprehensive integrated theoretical and experimental study for the in vitro drug interaction between levocetirizine dihydrochloride (LEV) and diclofenac sodium (DIC). The interaction of the two drugs was confirmed by the molecular ion peak obtained from the mass spectrum of the product. Moreover, FTIR and 1 HNMR spectra of the individual drugs and their interaction product were inspected to allocate the possible sites of interaction. In addition, quantum mechanical DFT calculations were performed to search for the interaction sites and to verify the types of interactions deduced from the spectroscopic studies such as charge-transfer and non-bonding π-π interactions. It was found that the studied drugs interact with each other in aqueous solution via four types of interactions, namely, ion-pair formation, three weak hydrogen bonds, non-bonding π-π interactions and charge-transfer from DIC to LEV. Copyright © 2017 Elsevier B.V. All rights reserved.

SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such as the bipartite local model (BLM), show promise, they often categorize unknown interactions as negative interaction. Therefore, these methods are not ideal for finding potential drug-target interactions that have not yet been validated as positive interactions. Thus, here we propose a method that integrates machine learning techniques, such as self-training support vector machine (SVM) and BLM, to develop a self-training bipartite local model (SELF-BLM) that facilitates the identification of potential interactions. The method first categorizes unlabeled interactions and negative interactions among unknown interactions using a clustering method. Then, using the BLM method and self-training SVM, the unlabeled interactions are self-trained and final local classification models are constructed. When applied to four classes of proteins that include enzymes, G-protein coupled receptors (GPCRs), ion channels, and nuclear receptors, SELF-BLM showed the best performance for predicting not only known interactions but also potential interactions in three protein classes compare to other related studies. The implemented software and supporting data are available at https://github.com/GIST-CSBL/SELF-BLM.

DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

PubMed Central

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets. Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

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.

Drug-nutrient interactions in the intensive care unit: literature review and current recommendations

PubMed Central

Heldt, Tatiane; Loss, Sergio Henrique

2013-01-01

Objective To describe the interactions between drugs and nutrients and their frequency in the intensive care unit and to assess the professional team's awareness regarding this subject. Methods The keywords "drug interactions" and "nutrition therapy" were searched in the PubMed (specifically MeSH) electronic database. The studies were systematically reviewed for descriptions of the types of interactions between drugs and nutrients, including their frequency and consequences. Results Sixty-seven articles were found. Among these, 20 articles were appropriate for the methodology adopted and accomplished the objectives of the study. Of these 20 articles, 14 articles described interactions between drugs and enteral nutrition, three described interactions between drugs and parenteral nutrition, and three described the importance and care required to avoid such interactions. Conclusions The literature about drug and nutrient interactions is limited and suggests the inability of health care teams to recognize the potential for these interactions. Possibly, the elaboration of a protocol to evaluate drug-nutrient interactions will increase the safety and efficacy of therapeutics. PMID:23917982

Pharmacokinetic Interactions between Drugs and Botanical Dietary Supplements.

PubMed

Sprouse, Alyssa A; van Breemen, Richard B

2016-02-01

The use of botanical dietary supplements has grown steadily over the last 20 years despite incomplete information regarding active constituents, mechanisms of action, efficacy, and safety. An important but underinvestigated safety concern is the potential for popular botanical dietary supplements to interfere with the absorption, transport, and/or metabolism of pharmaceutical agents. Clinical trials of drug-botanical interactions are the gold standard and are usually carried out only when indicated by unexpected consumer side effects or, preferably, by predictive preclinical studies. For example, phase 1 clinical trials have confirmed preclinical studies and clinical case reports that St. John's wort (Hypericum perforatum) induces CYP3A4/CYP3A5. However, clinical studies of most botanicals that were predicted to interact with drugs have shown no clinically significant effects. For example, clinical trials did not substantiate preclinical predictions that milk thistle (Silybum marianum) would inhibit CYP1A2, CYP2C9, CYP2D6, CYP2E1, and/or CYP3A4. Here, we highlight discrepancies between preclinical and clinical data concerning drug-botanical interactions and critically evaluate why some preclinical models perform better than others in predicting the potential for drug-botanical interactions. Gaps in knowledge are also highlighted for the potential of some popular botanical dietary supplements to interact with therapeutic agents with respect to absorption, transport, and metabolism. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Hyperforin in St. John's wort drug interactions.

PubMed

Madabushi, Rajanikanth; Frank, Bruno; Drewelow, Bernd; Derendorf, Hartmut; Butterweck, Veronika

2006-03-01

Recently, interactions of herbal medicines with synthetic drugs came into focus of particular interest. In the past 3 years, more than 50 papers were published regarding interactions between St. John's wort (Hypericum perforatum L.; SJW) and prescription drugs. Co-medication with SJW resulted in decreased plasma concentrations of a number of drugs including amitriptyline, cyclosporine, digoxin, indinavir, irinotecan, warfarin, phenprocoumon, alprazolam, dextrometorphane, simvastatin, and oral contraceptives. Sufficient evidence from interaction studies and case reports indicate that SJW is a potent inducer of cytochrome P450 enzymes (particularly CYP3A4) and/or P-glycoprotein. Recent studies could show that the degree of enzyme induction by SJW correlates strongly with the amount of hyperforin found in the product. Products that do not contain substantial amounts of hyperforin (<1%) have not been shown to produce clinically relevant enzyme induction. On the other hand, some evidence suggests that hyperforin may also contribute to the antidepressant activity of SJW. However, clinical studies using SJW preparations with a low hyperforin amount (<1%) clearly demonstrated the superiority of this plant extract over placebo and its equivalence to imipramine and fluoxetine in the treatment of mild to moderate forms of depression. In the present paper clinical significant SJW interactions are critically evaluated against the background of hyperforin.

[Prevalence of potential drug interactions with azithromycin in Colombia, 2012-2013].

PubMed

Machado-Alba, Jorge E; Martínez-Pulgarín, Dayron F; Gómez-Suta, Daniela

2015-05-01

Objective To determine the prevalence of potential drug interactions between azithromycin and different IA and III antiarrhythmic groups in a national database of drug prescriptions in 2012-2013. Methods Retrospective study based on a population database of medicine dispensation. Data from patients who received azithromycin between January 1, 2012 and June 30, 2013 were extracted along with data from patients who received azithromycin in combination with other medications shown to cause heart arrhythmias when used concomitantly. Frequencies and proportions were established. Results 13 859 patients receiving azithromycin alone or in combination with other drugs were identified. The average time of use was 4.5 ± 0.9 days. A total of 702 patients (5.1 %) received azithromycin plus 19 other potentially risky drugs. The most frequently associated were loratadine (77.1 %), diphenhydramine (16.5 %) and amitriptyline (8.1 %). Combinations with a single drug were the most frequent (n=533, 75.9 %), predominantly azithromycin+loratadine. The maximum number of combined drugs was six (n=2, 0.3 %). Conclusions Identification of drug prescriptions through population databases is an effective way to find potential drug interactions. The frequency of potential interactions between azithromycin and other drugs is common in Colombian patients. Future research should assess the risk of occurrence of adverse cardiac events.

Relationships of Changes in Pharmacokinetic Parameters of Substrate Drugs in Drug-Drug Interactions on Metabolizing Enzymes and Transporters.

PubMed

Yamazaki, Shinji

2018-05-03

A general objective of drug-drug interaction (DDI) studies is to determine whether potential interactions of new molecular entities with concomitantly administered other drugs exist and, if DDIs occur, whether dosage adjustments are required. A typical end point for DDI evaluations is the ratio of area under the plasma concentration-time curve (AUC) of substrate drugs (AUCR), whereas the ratios of maximal plasma concentration (C max ) and terminal half-life (t 1/2 ) are also important to understand DDI mechanisms (C max R and t 1/2 R, respectively). Because changes in substrate AUC by precipitant drugs ultimately result from alterations of C max and t 1/2 , AUCR can be considered a hybrid parameter of C max R and t 1/2 R, for example, AUCR ≈ C max R  ×  t 1/2 R. The primary objective of this study was to investigate the relationships between AUCR, C max R, and t 1/2 R in physiologically based pharmacokinetic model-predicted and clinically observed DDI results. First, the model-predicted results showed the excellent proportional relationship between AUCR and (C max R × t 1/2 R) in DDI results of virtual substrates having a wide range of oral bioavailability with coadministration of ketoconazole, ritonavir, and rifampin. Second, the reasonable proportional relationships were also observed in the clinically observed DDI results of midazolam and statins (atorvastatin, cerivastatin, fluvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin) with various inhibitors and inducers. Finally, these results suggest that utilization of the proportional relationship between AUCR and (C max R × t 1/2 R) can provide an additional framework to further interpret DDI results reasonably and clearly. Furthermore, the proportional relationship can be purposely used to assess study design and pharmacokinetic analyses in DDI studies. © 2018, The American College of Clinical Pharmacology.

Lipid-lipid and lipid-drug interactions in biological membranes

NASA Astrophysics Data System (ADS)

Martynowycz, Michael W.

Interactions between lipids and drug molecules in biological membranes help govern proper biological function in organisms. The mechanisms responsible for hydrophobic drug permeation remain elusive. Many small molecule drugs are hydrophobic. These drugs inhibit proteins in the cellular interior. The rise of antibiotic resistance in bacteria is thought to be caused by mutations in protein structure, changing drug kinetics to favor growth. However, small molecule drugs have been shown to have different mechanisms depending in the structure of the lipid membrane of the target cell. Biological membranes are investigated using Langmuir monolayers at the air-liquid interface. These offer the highest level of control in the mimetic system and allow them to be investigated using complementary techniques. Langmuir isotherms and insertion assays are used to determine the area occupied by each lipid in the membrane and the change in area caused by the introduction of a drug molecule, respectively. Specular X-ray reflectivity is used to determine the electron density of the monolayer, and grazing incidence X-ray diffraction is used to determine the in-plane order of the monolayer. These methods determine the affinity of the drug and the mechanism of action. Studies are presented on hydrophobic drugs with mammalian membrane mimics using warfarin along with modified analogues, called superwarfarins. Data shows that toxicity of these modified drugs are modulated by the membrane cholesterol content in cells; explaining several previously unexplained effects of the drugs. Membrane mimics of bacteria are investigated along with their interactions with a hydrophobic antibiotic, novobiocin. Data suggests that permeation of the drug is mediated by modifications to the membrane lipids, and completely ceases translocation under certain circumstances. Circumventing deficiencies in small, hydrophobic drugs is approached by using biologically mimetic oligomers. Peptoids, mimetic of host

An evaluation of the completeness of drug-drug interaction-related information in package inserts.

PubMed

Ng, Giok Qin; Sklar, Grant Edward; Chng, Hui Ting

2017-02-01

The project aimed to evaluate the completeness of drug-drug interaction (DDI)-related information in package inserts (PIs) and develop a systematic approach to conduct the evaluation. DDI-related information in the branded PIs of statins, macrolides, protease inhibitors and selected drugs of narrow therapeutic index (DNTI) were evaluated against the criteria distilled from the Food and Drug Administration (FDA) labelling recommendation guidance document. Decision trees were crafted and employed in the evaluation process. Scores were computed to give each PI an overall completeness score and individual criterion completeness score. The Kruskal-Wallis test and Dunn's multiple comparison test were used to assess the differences in the completeness scores. The mean overall completeness score of the 21 PIs was 35.7 ± 13.4 % (range 12.2-62 %). Eight out of the 11 individual evaluation criterion had a mean completeness score below 50 %. A subclass analysis conducted revealed that PIs from the different drug classes differed in the type of DDI-related information, such that they are more complete or less complete. The completeness score of DDI-related information in the PIs varied extensively amongst and within drug classes. A consensus between the authorities and drug companies on the type and quality of DDI-related information to be included could improve their completeness in PIs and make PIs a valuable source of DDI reference. Decision trees, albeit not validated yet, lay the groundwork for a valuable tool to evaluate DDI-related or other drug information.

Drug-target interaction prediction using ensemble learning and dimensionality reduction.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2017-10-01

Experimental prediction of drug-target interactions is expensive, time-consuming and tedious. Fortunately, computational methods help narrow down the search space for interaction candidates to be further examined via wet-lab techniques. Nowadays, the number of attributes/features for drugs and targets, as well as the amount of their interactions, are increasing, making these computational methods inefficient or occasionally prohibitive. This motivates us to derive a reduced feature set for prediction. In addition, since ensemble learning techniques are widely used to improve the classification performance, it is also worthwhile to design an ensemble learning framework to enhance the performance for drug-target interaction prediction. In this paper, we propose a framework for drug-target interaction prediction leveraging both feature dimensionality reduction and ensemble learning. First, we conducted feature subspacing to inject diversity into the classifier ensemble. Second, we applied three different dimensionality reduction methods to the subspaced features. Third, we trained homogeneous base learners with the reduced features and then aggregated their scores to derive the final predictions. For base learners, we selected two classifiers, namely Decision Tree and Kernel Ridge Regression, resulting in two variants of ensemble models, EnsemDT and EnsemKRR, respectively. In our experiments, we utilized AUC (Area under ROC Curve) as an evaluation metric. We compared our proposed methods with various state-of-the-art methods under 5-fold cross validation. Experimental results showed EnsemKRR achieving the highest AUC (94.3%) for predicting drug-target interactions. In addition, dimensionality reduction helped improve the performance of EnsemDT. In conclusion, our proposed methods produced significant improvements for drug-target interaction prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

Wide variation and patterns of physicians' responses to drug-drug interaction alerts.

PubMed

Cho, Insook; Lee, Yura; Lee, Jae-Ho; Bates, David W

2018-05-08

Providing physicians with alerts about potentially harmful drug-drug interactions (DDIs) is only moderately effective due to high alert override rates. To understand high override behavior on DDI alerts, we investigated how physicians respond to DDIs and their behavior patterns and variations. Retrospective system log data analysis and records review (sampling 2% of total overrides). A large tertiary academic hospital. About 560 physicians and their override responses to DDI alerts generated from 1 September to 31 December 2014. Not applicable. DDI alert frequency and override rate. We found significant variation in both the number of alerts and override rates at the levels of physicians, departments and drug-class pairs. Physician-level variations were wider for residents than for faculty staff (number of alerts: t = 254.17, P = 0.011; override rates: t = -4.77, P < 0.0001). Using the number of alerts and their override rate, we classified physicians into four groups: inexperienced incautious users, inexperienced cautious users, experienced cautious users and experienced incautious users. Medical department influenced both alert numbers and override rates. Nearly 90% of the overrides involved only five drug-class combinations, which had a wide range of appropriateness in the chart review. The variations at drug-class levels suggest issues with system design and the DDI rules. Department-level variation may be best addressed at the department level, and the rest of the variation appears related to individual physician responses, suggesting the need for interventions at an individual level.

Drug-nutrient interactions in three long-term-care facilities.

PubMed

Lewis, C W; Frongillo, E A; Roe, D A

1995-03-01

To assess the risk of drug-nutrient interactions (DNIs) in three long-term-care facilities. Retrospective audit of charts. Three long-term-care facilities in central New York State. Fifty-three patients selected randomly from each facility. Data were collected from the medical record of each patient for a period of 6 months. A computerized algorithm was used to assess the risk for DNIs. Mean drug use, most frequently consumed drugs, incidence of potential DNIs, and the most commonly observed potential DNIs are reported. In facilities A, B, and C, respectively, patients consumed a mean of 4.86, 4.04, and 5.27 drugs per patient per month and were at risk for a mean of 1.43, 2.69, and 1.43 potential DNIs per patient per month. The most commonly observed potential DNIs were gastrointestinal interactions affecting drug bioavailability and interactions affecting electrolyte status. Patients in long-term-care facilities, who are primarily elderly and chronically ill and who consume multiple medications, are at notable risk for certain DNIs. Efforts need to be made to ensure appropriate pharmacologic and nutrition therapies as well as adequate and timely monitoring of patients in these facilities. Dietitians can play an important role in training other health professionals and in designing policies to prevent DNIs.

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions-an Industry Perspective.

PubMed

Bohnert, Tonika; Patel, Aarti; Templeton, Ian; Chen, Yuan; Lu, Chuang; Lai, George; Leung, Louis; Tse, Susanna; Einolf, Heidi J; Wang, Ying-Hong; Sinz, Michael; Stearns, Ralph; Walsky, Robert; Geng, Wanping; Sudsakorn, Sirimas; Moore, David; He, Ling; Wahlstrom, Jan; Keirns, Jim; Narayanan, Rangaraj; Lang, Dieter; Yang, Xiaoqing

2016-08-01

Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (fCL), estimation of fractional contribution of metabolizing enzyme toward metabolism (fm), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify fCL and fm, 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Potential drug interactions in patients given antiretroviral therapy.

PubMed

Santos, Wendel Mombaque Dos; Secoli, Silvia Regina; Padoin, Stela Maris de Mello

2016-11-21

to investigate potential drug-drug interactions (PDDI) in patients with HIV infection on antiretroviral therapy. a cross-sectional study was conducted on 161 adults with HIV infection. Clinical, socio demographic, and antiretroviral treatment data were collected. To analyze the potential drug interactions, we used the software Micromedex(r). Statistical analysis was performed by binary logistic regression, with a p-value of ≤0.05 considered statistically significant. of the participants, 52.2% were exposed to potential drug-drug interactions. In total, there were 218 potential drug-drug interactions, of which 79.8% occurred between drugs used for antiretroviral therapy. There was an association between the use of five or more medications and potential drug-drug interactions (p = 0.000) and between the time period of antiretroviral therapy being over six years and potential drug-drug interactions (p < 0.00). The clinical impact was prevalent sedation and cardiotoxicity. the PDDI identified in this study of moderate and higher severity are events that not only affect the therapeutic response leading to toxicity in the central nervous and cardiovascular systems, but also can interfere in tests used for detection of HIV resistance to antiretroviral drugs. investigar potenciais interações droga-droga (PDDI) em pacientes infectados com HIV em terapia de antirretroviral. um estudo de corte transversal foi conduzido em 161 pessoas infectadas com o HIV. Dados de tratamentos clínicos, sociodemográficos e antirretrovirais foram coletados. Para analisar a possível interação medicamentosa, nós usamos o software Micromedex(r). A análise estatística foi feita por regressão logística binária, com um valor P de ≤0.05, considerado estatisticamente significativo. dos participantes, 52.2% foram expostos a potenciais interações droga-droga. No total, houve 218 interações droga-droga, das quais 79.8% ocorreram entre drogas usadas para a terapia antirretroviral

CYP3A4 substrate selection and substitution in the prediction of potential drug-drug interactions.

PubMed

Galetin, Aleksandra; Ito, Kiyomi; Hallifax, David; Houston, J Brian

2005-07-01

The complexity of in vitro kinetic phenomena observed for CYP3A4 substrates (homo- or heterotropic cooperativity) confounds the prediction of drug-drug interactions, and an evaluation of alternative and/or pragmatic approaches and substrates is needed. The current study focused on the utility of the three most commonly used CYP3A4 in vitro probes for the prediction of 26 reported in vivo interactions with azole inhibitors (increase in area under the curve ranged from 1.2 to 24, 50% in the range of potent inhibition). In addition to midazolam, testosterone, and nifedipine, quinidine was explored as a more "pragmatic" substrate due to its kinetic properties and specificity toward CYP3A4 in comparison with CYP3A5. Ki estimates obtained in human liver microsomes under standardized in vitro conditions for each of the four probes were used to determine the validity of substrate substitution in CYP3A4 drug-drug interaction prediction. Detailed inhibitor-related (microsomal binding, depletion over incubation time) and substrate-related factors (cooperativity, contribution of other metabolic pathways, or renal excretion) were incorporated in the assessment of the interaction potential. All four CYP3A4 probes predicted 69 to 81% of the interactions with azoles within 2-fold of the mean in vivo value. Comparison of simple and multisite mechanistic models and interaction prediction accuracy for each of the in vitro probes indicated that midazolam and quinidine in vitro data provided the best assessment of a potential interaction, with the lowest bias and the highest precision of the prediction. Further investigations with a wider range of inhibitors are required to substantiate these findings.

Knowledge Integration and Use-Case Analysis for a Customized Drug-Drug Interaction CDS Service

NASA Astrophysics Data System (ADS)

Kam, Hye Jin; Park, Man Young; Kim, Woojae; Yoon, Duk Yong; Ahn, Eun Kyoung; Park, Rae Woong

Clinical decision support systems (CDSSs) are thought to reduce adverse drug events (ADEs) by monitoring drug-drug interactions(DDIs). However, clinically improper or excessive alerts can result in high alert overrides. A tailored CDS service, which is appropriate for clinicians and their ordering situations, is required to increase alert acceptance. In this study, we conducted a 12-week pilot project adopting a tailed CDSS at an emergency department. The new CDSS was conducted via a stepwise integration of additional new rules. The alert status with changes in acceptance rate was analyzed. The most frequent DDI alerts were related to prescriptions of anti-inflammatory drugs. The percentages of alert overrides for each stage were 98.0%, 96.0%, 96.9%, and 98.1%, respectively. 91.5% of overridden alerts were related to discharge medications. To reduce the potential hazards of ADEs, the development of an effective customized DDI CDSS is required, via in-depth analysis on alert patterns and overridden reasons.

A survey of attitudes, practices, and knowledge regarding drug-drug interactions among medical residents in Iran.

PubMed

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

2017-06-01

Background When prescribing medications, physicians should recognize clinically relevant potential drug-drug interactions (DDIs). To improve medication safety, it is important to understand prescribers' knowledge and opinions pertaining to DDIs. Objective To determine the current DDI information sources used by medical residents, their knowledge of DDIs, their opinions about performance feedback on co-prescription of interacting drugs. Setting Academic hospitals of Mashhad University of Medical Sciences (MUMS) in Iran. Methods A questionnaire containing questions regarding demographic and practice characteristics, DDI information sources, ability to recognize DDIs, and opinions about performance feedback was distributed to medical residents of 22 specialties in eight academic hospitals in Iran. We analyzed their perception pertaining to DDIs, their performance on classifying drug pairs, and we used a linear regression model to assess the association of potential determinants on their DDI knowledge. Main Outcome Measure prescribers' knowledge and opinions pertaining to DDIs. Results The overall response rate and completion rate for 315 distributed questionnaires were 90% (n = 295) and 86% (n = 281), respectively. Among DDI information sources, books, software on mobile phone or tablet, and Internet were the most commonly-used references. Residents could correctly classify only 41% (5.7/14) of the drug pairs. The regression model showed no significant association between residents' characteristics and their DDI knowledge. An overwhelming majority of the respondents (n = 268, 95.4%) wished to receive performance feedback on co-prescription of interacting drugs in their prescriptions. They mostly selected information technology-based tools (i.e. short text message and email) as their preferred method of receiving feedback. Conclusion Our findings indicate that prescribers may have poor ability to prevent clinically relevant potential DDI occurrence, and they

Molecular Insights into the Effects of Media-Drug and Carrier-Drug Interactions on pH-Responsive Drug Carriers.

PubMed

Katiyar, Ratna S; Jha, Prateek K

2018-05-10

We have performed two sets of all atom molecular dynamics (MD) simulations of poly(acrylic acid) (PAA) oligomers, considered as a model pH-responsive drug carrier. In the first set, multiple oligomers of PAA are simulated in model gastric and intestinal fluids, where the degree of deprotonation of PAA oligomers is varied with the medium pH. Since the gastric fluid has a pH substantially lower than that of intestinal fluid, PAA is relatively lesser ionized in gastric fluid and forms aggregates. In the second set, we simulated multiple oligomers of PAA with multiple molecules of a cationic anticancer drug, doxorubicin (DOX), for a range of pH values representative of various physiological conditions. The diffusion coefficient of DOX decreases with an increase in pH due to an increase in the ionic complexation of PAA with DOX, despite a decrease in PAA aggregation. Our findings are in agreement with recent experimental reports on pH-triggered targeting of tumor cells by the PAA-DOX system. Results of these two sets of studies establish that both carrier aggregation and carrier-drug interactions are competing influences that together determine the drug release from pH-responsive polymers.

Drug interactions between buprenorphine, methadone and hepatitis C therapeutics.

PubMed

Ogbuagu, Onyema; Friedland, Gerald; Bruce, R Douglas

2016-07-01

People who inject drugs (PWID) and other individuals with opioid use disorders have a dramatically higher prevalence of hepatitis C virus (HCV) infection than the general population. The availability of novel direct acting antivirals (DAAs) for the treatment of HCV infection with very high efficacy, improved tolerability and shortened treatment durations have led to global efforts to ramp up treatment for all HCV-infected individuals to prevent or delay complications of the disease. Individuals with opioid use disorders, including those on medication-assisted therapy such as methadone or buprenorphine, are a key demographic group that can benefit from HCV treatment given their high HCV prevalence; however, pharmacokinetic and pharmacodynamic drug interactions could blunt their utility. We performed a comprehensive literature review of published and unpublished data from PubMed database, relevant conference abstracts/proceedings and FDA approved drug package inserts, to review the pharmacokinetic (PK) profile and drug interactions between currently approved HCV DAAs and methadone and buprenorphine. The paper highlights specific drug combinations which result in altered opioid drug levels including telaprevir/methadone, daclatasvir/buprenorphine, and Abbvie 3D combination regimen (paritaprevir, ritonavir, ombitasvir and dasabuvir)/buprenorphine. However, concurrent pharmacodynamics assessments did not reveal significant signs and symptoms of opioid withdrawal or toxicity that would preclude concurrent administration.

Recommendations for selecting drug-drug interactions for clinical decision support.

PubMed

Tilson, Hugh; Hines, Lisa E; McEvoy, Gerald; Weinstein, David M; Hansten, Philip D; Matuszewski, Karl; le Comte, Marianne; Higby-Baker, Stefanie; Hanlon, Joseph T; Pezzullo, Lynn; Vieson, Kathleen; Helwig, Amy L; Huang, Shiew-Mei; Perre, Anthony; Bates, David W; Poikonen, John; Wittie, Michael A; Grizzle, Amy J; Brown, Mary; Malone, Daniel C

2016-04-15

Recommendations for including drug-drug interactions (DDIs) in clinical decision support (CDS) are presented. A conference series was conducted to improve CDS for DDIs. A work group consisting of 20 experts in pharmacology, drug information, and CDS from academia, government agencies, health information vendors, and healthcare organizations was convened to address (1) the process to use for developing and maintaining a standard set of DDIs, (2) the information that should be included in a knowledge base of standard DDIs, (3) whether a list of contraindicated drug pairs can or should be established, and (4) how to more intelligently filter DDI alerts. We recommend a transparent, systematic, and evidence-driven process with graded recommendations by a consensus panel of experts and oversight by a national organization. We outline key DDI information needed to help guide clinician decision-making. We recommend judicious classification of DDIs as contraindicated and more research to identify methods to safely reduce repetitive and less-relevant alerts. An expert panel with a centralized organizer or convener should be established to develop and maintain a standard set of DDIs for CDS in the United States. The process should be evidence driven, transparent, and systematic, with feedback from multiple stakeholders for continuous improvement. The scope of the expert panel's work should be carefully managed to ensure that the process is sustainable. Support for research to improve DDI alerting in the future is also needed. Adoption of these steps may lead to consistent and clinically relevant content for interruptive DDIs, thus reducing alert fatigue and improving patient safety. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Drug-nutrient interactions: a broad view with implications for practice.

PubMed

Boullata, Joseph I; Hudson, Lauren M

2012-04-01

The relevance of drug?nutrient interactions in daily practice continues to grow with the widespread use of medication. Interactions can involve a single nutrient, multiple nutrients, food in general, or nutrition status. Mechanistically, drug?nutrient interactions occur because of altered intestinal transport and metabolism, or systemic distribution, metabolism and excretion, as well as additive or antagonistic effects. Optimal patient care includes identifying, evaluating, and managing these interactions. This task can be supported by a systematic approach for categorizing interactions and rating their clinical significance. This review provides such a broad framework using recent examples, as well as some classic drug?nutrient interactions. Pertinent definitions are presented, as is a suggested approach for clinicians. This important and expanding subject will benefit tremendously from further clinician involvement. Copyright © 2012 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

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

Evaluation of Drug-Drug Interaction Potential Between Sacubitril/Valsartan (LCZ696) and Statins Using a Physiologically Based Pharmacokinetic Model.

PubMed

Lin, Wen; Ji, Tao; Einolf, Heidi; Ayalasomayajula, Surya; Lin, Tsu-Han; Hanna, Imad; Heimbach, Tycho; Breen, Christopher; Jarugula, Venkateswar; He, Handan

2017-05-01

Sacubitril/valsartan (LCZ696) has been approved for the treatment of heart failure. Sacubitril is an in vitro inhibitor of organic anion-transporting polypeptides (OATPs). In clinical studies, LCZ696 increased atorvastatin C max by 1.7-fold and area under the plasma concentration-time curve by 1.3-fold, but had little or no effect on simvastatin or simvastatin acid exposure. A physiologically based pharmacokinetics modeling approach was applied to explore the underlying mechanisms behind the statin-specific LCZ696 drug interaction observations. The model incorporated OATP-mediated clearance (CL int,T ) for simvastatin and simvastatin acid to successfully describe the pharmacokinetic profiles of either analyte in the absence or presence of LCZ696. Moreover, the model successfully described the clinically observed drug effect with atorvastatin. The simulations clarified the critical parameters responsible for the observation of a low, yet clinically relevant, drug-drug interaction DDI between sacubitril and atorvastatin and the lack of effect with simvastatin acid. Atorvastatin is administered in its active form and rapidly achieves C max that coincide with the low C max of sacubitril. In contrast, simvastatin requires a hydrolysis step to the acid form and therefore is not present at the site of interactions at sacubitril concentrations that are inhibitory. Similar models were used to evaluate the drug-drug interaction risk for additional OATP-transported statins which predicted to maximally result in a 1.5-fold exposure increase. Copyright © 2017. Published by Elsevier Inc.

Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

PubMed Central

2017-01-01

The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target's homologue set containing 102 potential target proteins is predicted in the paper. PMID:28691014

Surface mediated cooperative interactions of drugs enhance mechanical forces for antibiotic action

NASA Astrophysics Data System (ADS)

Ndieyira, Joseph W.; Bailey, Joe; Patil, Samadhan B.; Vögtli, Manuel; Cooper, Matthew A.; Abell, Chris; McKendry, Rachel A.; Aeppli, Gabriel

2017-02-01

The alarming increase of pathogenic bacteria that are resistant to multiple antibiotics is now recognized as a major health issue fuelling demand for new drugs. Bacterial resistance is often caused by molecular changes at the bacterial surface, which alter the nature of specific drug-target interactions. Here, we identify a novel mechanism by which drug-target interactions in resistant bacteria can be enhanced. We examined the surface forces generated by four antibiotics; vancomycin, ristomycin, chloroeremomycin and oritavancin against drug-susceptible and drug-resistant targets on a cantilever and demonstrated significant differences in mechanical response when drug-resistant targets are challenged with different antibiotics although no significant differences were observed when using susceptible targets. Remarkably, the binding affinity for oritavancin against drug-resistant targets (70 nM) was found to be 11,000 times stronger than for vancomycin (800 μM), a powerful antibiotic used as the last resort treatment for streptococcal and staphylococcal bacteria including methicillin-resistant Staphylococcus aureus (MRSA). Using an exactly solvable model, which takes into account the solvent and membrane effects, we demonstrate that drug-target interactions are strengthened by pronounced polyvalent interactions catalyzed by the surface itself. These findings further enhance our understanding of antibiotic mode of action and will enable development of more effective therapies.

Non-steroidal anti-inflammatory drugs: What is the actual risk of liver damage?

PubMed Central

Bessone, Fernando

2010-01-01

Non-steroidal anti-inflammatory drugs (NSAIDs) constitute a family of drugs, which taken as a group, represents one of the most frequently prescribed around the world. Thus, not surprisingly NSAIDs, along with anti-infectious agents, list on the top for causes of Drug-Induced Liver Injury (DILI). The incidence of liver disease induced by NSAIDs reported in clinical studies is fairly uniform ranging from 0.29/100 000 [95% confidence interval (CI): 0.17-051] to 9/100 000 (95% CI: 6-15). However, compared with these results, a higher risk of liver-related hospitalizations was reported (3-23 per 100 000 patients). NSAIDs exhibit a broad spectrum of liver damage ranging from asymptomatic, transient, hyper-transaminasemia to fulminant hepatic failure. However, under-reporting of asymptomatic, mild cases, as well as of those with transient liver-tests alteration, in conjunction with reports non-compliant with pharmacovigilance criteria to ascertain DILI and flawed epidemiological studies, jeopardize the chance to ascertain the actual risk of NSAIDs hepatotoxicity. Several NSAIDs, namely bromfenac, ibufenac and benoxaprofen, have been withdrawn from the market due to hepatotoxicity; others like nimesulide were never marketed in some countries and withdrawn in others. Indeed, the controversy concerning the actual risk of severe liver disease persists within NSAIDs research. The present work intends (1) to provide a critical analysis of the dissimilar results currently available in the literature concerning the epidemiology of NSAIDS hepatotoxicity; and (2) to review the risk of hepatotoxicity for each one of the most commonly employed compounds of the NSAIDs family, based on past and recently published data. PMID:21128314

Mechanisms Underlying Food-Drug Interactions: Inhibition of Intestinal Metabolism and Transport

PubMed Central

Won, Christina S.; Oberlies, Nicholas H.; Paine, Mary F.

2012-01-01

Food-drug interaction studies are critical to evaluate appropriate dosing, timing, and formulation of new drug candidates. These interactions often reflect prandial-associated changes in the extent and/or rate of systemic drug exposure. Physiologic and physicochemical mechanisms underlying food effects on drug disposition are well-characterized. However, biochemical mechanisms involving drug metabolizing enzymes and transport proteins remain underexplored. Several plant-derived beverages have been shown to modulate enzymes and transporters in the intestine, leading to altered pharmacokinetic (PK) and potentially negative pharmacodynamic (PD) outcomes. Commonly consumed fruit juices, teas, and alcoholic drinks contain phytochemicals that inhibit intestinal cytochrome P450 and phase II conjugation enzymes, as well as uptake and efflux transport proteins. Whereas myriad phytochemicals have been shown to inhibit these processes in vitro, translation to the clinic has been deemed insignificant or undetermined. An overlooked prerequisite for elucidating food effects on drug PK is thorough knowledge of causative bioactive ingredients. Substantial variability in bioactive ingredient composition and activity of a given dietary substance poses a challenge in conducting robust food-drug interaction studies. This confounding factor can be addressed by identifying and characterizing specific components, which could be used as marker compounds to improve clinical trial design and quantitatively predict food effects. Interpretation and integration of data from in vitro, in vivo, and in silico studies require collaborative expertise from multiple disciplines, from botany to clinical pharmacology (i.e., plant to patient). Development of more systematic methods and guidelines is needed to address the general lack of information on examining drug-dietary substance interactions prospectively. PMID:22884524

Evaluation of community pharmacists' knowledge and awareness of food-drug interactions in Palestine.

PubMed

Radwan, Asma; Sweileh, Anwar; Shraim, We'am; Hroub, Amr; Elaraj, Josephean; Shraim, Naser

2018-05-02

Background Food-drug interactions can produce undesirable outcomes during the therapy process. The pharmacist is responsible for providing patients counseling about common food-drug interactions. Knowledge of such interactions is important to avoid their occurrence. Objective This study aimed to assess the knowledge and awareness of community pharmacists about common food-drug interactions. Setting Pharmacists working in community pharmacies across Northern Palestine. Method This is a cross-sectional study, which involved a convenience sample of 259 pharmacists working in community pharmacies in Palestine. A self-administered questionnaire consisted of 29 questions (mainly yes/no questions) was used to assess pharmacists' knowledge towards the most common and clinically significant interactions between food and medicines. Main outcome measure Pharmacists' issues related to the knowledge of food drug interactions were evaluated. Results A total of 320 questionnaires were distributed of which 259 were completed providing a response rate 80.9%. One pharmacist from each community pharmacy was asked to complete the questionnaire. The overall knowledge score of food-drug interactions for the pharmacists was 17.9 (61.7%) out of a possible maximum of 29. The pharmacists surveyed in this study have demonstrated good knowledge of some interactions; but poor knowledge of others. Conclusion Pharmacists' knowledge about common food-drug interactions is inadequate. These findings support the need for training and educational courses for pharmacists regarding food-drug interactions.

Chemotherapy drugs form ion pores in membranes due to physical interactions with lipids.

PubMed

Ashrafuzzaman, Mohammad; Tseng, Chih-Yuan; Duszyk, Marek; Tuszynski, Jack A

2012-12-01

We demonstrate the effects on membrane of the tubulin-binding chemotherapy drugs: thiocolchicoside and taxol. Electrophysiology recordings across lipid membranes in aqueous phases containing drugs were used to investigate the drug effects on membrane conductance. Molecular dynamics simulation of the chemotherapy drug-lipid complexes was used to elucidate the mechanism at an atomistic level. Both drugs are observed to induce stable ion-flowing pores across membranes. Discrete pore current-time plots exhibit triangular conductance events in contrast to rectangular ones found for ion channels. Molecular dynamics simulations indicate that drugs and lipids experience electrostatic and van der Waals interactions for short periods of time when found within each other's proximity. The energies from these two interactions are found to be similar to the energies derived theoretically using the screened Coulomb and the van der Waals interactions between peptides and lipids due to mainly their charge properties while forming peptide-induced ion channels in lipid bilayers. Experimental and in silico studies together suggest that the chemotherapy drugs induce ion pores inside lipid membranes due to drug-lipid physical interactions. The findings reveal cytotoxic effects of drugs on the cell membrane, which may aid in novel drug development for treatment of cancer and other diseases. © 2012 John Wiley & Sons A/S.

Busulfan and metronidazole: an often forgotten but significant drug interaction.

PubMed

Gulbis, Alison M; Culotta, Kirk S; Jones, Roy B; Andersson, Borje S

2011-07-01

To report the case of a clinically significant drug interaction between intravenous busulfan and oral metronidazole observed through busulfan therapeutic drug monitoring (TDM). A 7-year-old boy with a history of myelodysplasia that progressed to acute myeloid leukemia received busulfan with therapeutic drug monitoring (TDM), clofarabine, and thiotepa as a pretransplant conditioning regimen for a cord blood transplant. The patient received metronidazole the day after a busulfan test dose of 0.5 mg/kg was administered. On the day of the first busulfan therapeutic dose, TDM was performed and the clearance of busulfan was significantly decreased by 46%. After 2 doses of busulfan therapy, the course area under the curve was exceeded, requiring discontinuation of busulfan. Metronidazole is not known to affect glutathione or the glutathione S-transferase A1 (GSTA1) enzyme system or cytochrome P450 (CYP) 3A4. Busulfan is a bifunctional alkylating agent widely used in pretransplant conditioning regimens in patients undergoing stem cell transplantation for hematologic malignancies. Busulfan metabolism is best described by hepatic conjugation to glutathione by GSTA1, although some CYP-dependent pathways have been described. Currently there is 1 publication describing the drug interaction between oral busulfan and oral metronidazole, in which concomitant use of metronidazole resulted in higher busulfan trough concentrations and higher risk of veno-occlusive disease. Our case represents a possible drug interaction based on the Horn Drug Interaction Probability Scale. Though the mechanistic basis for this interaction is unknown, the risks and benefits of using metronidazole during and in close proximity to busulfan should be carefully considered and therapeutic alternatives to metronidazole should be used when appropriate.

Characterization of the Pharmacokinetics of Vilaprisan: Bioavailability, Excretion, Biotransformation, and Drug-Drug Interaction Potential.

PubMed

Schultze-Mosgau, Marcus-Hillert; Höchel, Joachim; Prien, Olaf; Zimmermann, Torsten; Brooks, Ashley; Bush, Jim; Rottmann, Antje

2018-01-12

In-vitro data suggest that clearance of vilaprisan is mediated by cytochrome P450 3A4 (oxidation) and aldoketoreductases (reduction). To fully understand the elimination and biotransformation pathways of vilaprisan, a selective progesterone receptor modulator, and to quantify the impact of cytochrome P450 3A4 inhibition on the pharmacokinetics of vilaprisan, two clinical studies in healthy postmenopausal women were conducted. In study 1, pharmacokinetics, mass balance, and metabolite patterns were determined after single oral administration of 5 mg of [ 14 C]-labeled vilaprisan in six subjects. In study 2, pharmacokinetics were determined after single oral administration of 4 mg of vilaprisan without and with concomitant administration of the strong cytochrome P450 3A4 inhibitor itraconazole (200 mg/day) in 14 subjects. In addition, a microtracer dose of vilaprisan was given intravenously to determine absolute bioavailability, clearance, and volume of distribution. The dominant single compound in plasma was vilaprisan. No plasma metabolites exceeding 10% of total drug-related area under the concentration-time curve were detected. The absolute oral bioavailability of vilaprisan was ~ 60%. The mean clearance was ~ 7 L/h and the volume of distribution at steady state was ~ 360 L. Excretion occurred primarily via feces (73.5 ± 3.70% of dose; urine: 13.1 ± 1.71%; total recovery: 86.6 ± 2.81%), mostly in a metabolized form. Only small amounts of the parent drug were found in excreta. When vilaprisan was administered together with itraconazole, exposure to vilaprisan was increased 6.2-fold (90% confidence interval 5.4-7.2). Vilaprisan is predominantly metabolized in the liver to a complex variety of metabolites, which are mainly excreted with feces. The pivotal role of cytochrome P450 3A4 in the metabolism of vilaprisan was confirmed. EudraCT numbers 2013-000707-16 (mass balance study) and 2014-004929-41 (drug-drug interaction/microtracer study); NCT

'Trafficking' or 'personal use': do people who regularly inject drugs understand Australian drug trafficking laws?

PubMed

Hughes, Caitlin E; Ritter, Alison; Cowdery, Nicholas; Sindicich, Natasha

2014-11-01

Legal thresholds for drug trafficking, over which possession of an illicit drug is deemed 'trafficking' as opposed to 'personal use', are employed in all Australian states and territories excepting Queensland. In this paper, we explore the extent to which people who regularly inject drugs understand such laws. Participants from the seven affected states/territories in the 2012 Illicit Drug Reporting System (n = 823) were asked about their legal knowledge of trafficking thresholds: whether, if arrested, quantity possessed would affect legal action taken; and the quantities of heroin, methamphetamine, cocaine and cannabis that would constitute an offence of supply. Data were compared against the actual laws to identify the accuracy of knowledge by drug type and state, and sociodemographics, use and purchasing patterns related to knowledge. Most Illicit Drug Reporting System participants (77%) correctly said that quantity possessed would affect charge received. However, only 55.8% nominated any specific quantity that would constitute an offence of supply, and of those 22.6% nominated a wrong quantity, namely a quantity that was larger than the actual quantity for supply (this varied by state and drug). People who regularly inject drugs have significant gaps in knowledge about Australian legal thresholds for drug trafficking, particularly regarding the actual threshold quantities. This suggests that there may be a need to improve education for this population. Necessity for accurate knowledge would also be lessened by better design of Australian drug trafficking laws. © 2014 Australasian Professional Society on Alcohol and other Drugs.

Warfarin-acetaminophen drug interaction revisited.

PubMed

Shek, K L; Chan, L N; Nutescu, E

1999-10-01

Physicians and pharmacists routinely advise patients receiving warfarin to take acetaminophen for pain or fever because of its relative safety; however, a recent study questioned the safety of such practice. A comprehensive search of MEDLINE and IPA for human studies and case reports from 1966-1999 revealed evidence that acetaminophen may potentiate the effect of warfarin by a mechanism that has yet to be elucidated. Due to lack of a safer alternative, acetaminophen still should be the analgesic and antipyretic of choice in patients taking warfarin, as long as excessive amounts and prolonged administration (> 1.3 g acetaminophen/day for > 2 wks) are avoided. With the high degree of interpatient variability and the unpredictability of various drug-drug interactions with warfarin, close and frequent monitoring of international normalized ratios is the key for safe oral anticoagulation therapy.

Mechanistic modeling to predict the transporter- and enzyme-mediated drug-drug interactions of repaglinide.

PubMed

Varma, Manthena V S; Lai, Yurong; Kimoto, Emi; Goosen, Theunis C; El-Kattan, Ayman F; Kumar, Vikas

2013-04-01

Quantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide. In vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-β-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data. In vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-β-glucuronide. This study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.

Drug-vitamin D interactions: A systematic review of the literature

PubMed Central

Oppeneer, Sarah J.; Kelly, Julia A.; Hamilton-Reeves, Jill M.

2017-01-01

Extensive media coverage of the potential health benefits of vitamin D supplementation has translated into substantial increases in supplement sales over recent years. Yet, the potential for drug-vitamin D interactions is rarely considered. This systematic review of the literature was conducted to evaluate the extent to which drugs affect vitamin D status or supplementation alters drug effectiveness or toxicity in humans. Electronic databases were used to identify eligible peer-reviewed studies published through September 1, 2010. Study characteristics and findings were abstracted, and quality was assessed for each study. A total of 109 unique reports met the inclusion criteria. The majority of eligible studies were classified as Class C (non-randomized trials, case-control studies, or time series) or D (cross-sectional, trend, case report/series, or before-and-after studies). Only two Class C and three Class D studies were of positive quality. Insufficient evidence was available to determine whether lipase inhibitors, antimicrobial agents, antiepileptic drugs, highly active antiretroviral agents or H2 receptor antagonists alter serum 25(OH)D concentrations. Atorvastatin appears to increase 25(OH)D concentrations, while concurrent vitamin D supplementation decreases concentrations of atorvastatin. Use of thiazide diuretics in combination with calcium and vitamin D supplements may cause hypercalcemia in the elderly, or those with compromised renal function or hyperparathyroidism. Larger studies with stronger study designs are needed to clarify potential drug-vitamin D interactions, especially for drugs metabolized by cytochrome P450 3A4 (CYP3A4). Health care providers should be aware of the potential for drug-vitamin D interactions. PMID:23307906

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.

Interaction in the Research Interview and Drug-Related Disclosures among Respondents.

ERIC Educational Resources Information Center

Myers, Vincent

1979-01-01

Interviewers and respondents judged interview interactions during a survey of drug-related sentiments. Pronounced variability in interviewer-respondent judgements occurred in unanticipated ways related to gender, role, and ethnicity of participants. Positive interaction yielded different respondent cognitions and reports of illicit drug ingestion…

Prevalence of Potential and Clinically Relevant Statin-Drug Interactions in Frail and Robust Older Inpatients.

PubMed

Thai, Michele; Hilmer, Sarah; Pearson, Sallie-Anne; Reeve, Emily; Gnjidic, Danijela

2015-10-01

A significant proportion of older people are prescribed statins and are also exposed to polypharmacy, placing them at increased risk of statin-drug interactions. To describe the prevalence rates of potential and clinically relevant statin-drug interactions in older inpatients according to frailty status. A cross-sectional study of patients aged ≥65 years who were prescribed a statin and were admitted to a teaching hospital between 30 July and 10 October 2014 in Sydney, Australia, was conducted. Data on socio-demographics, comorbidities and medications were collected using a standardized questionnaire. Potential statin-drug interactions were defined if listed in the Australian Medicines Handbook and three international drug information sources: the British National Formulary, Drug Interaction Facts and Drug-Reax(®). Clinically relevant statin-drug interactions were defined as interactions with the highest severity rating in at least two of the three international drug information sources. Frailty was assessed using the Reported Edmonton Frail Scale. A total of 180 participants were recruited (median age 78 years, interquartile range 14), 35.0% frail and 65.0% robust. Potential statin-drug interactions were identified in 10% of participants, 12.7% of frail participants and 8.5% of robust participants. Clinically relevant statin-drug interactions were identified in 7.8% of participants, 9.5% of frail participants and 6.8% of robust participants. Depending on the drug information source used, the prevalence rates of potential and clinically relevant statin-drug interactions ranged between 14.4 and 35.6% and between 14.4 and 20.6%, respectively. In our study of frail and robust older inpatients taking statins, the overall prevalence of potential statin-drug interactions was low and varied significantly according to the drug information source used.

Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs

PubMed Central

White, Cynthia; Mao, Zhiyuan; Savage, Van M.

2016-01-01

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions—ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions. PMID:27278366

Identification and evaluation of drug-supplement interactions in Hungarian hospital patients.

PubMed

Végh, Anna; Lankó, Erzsébet; Fittler, András; Vida, Róbert György; Miseta, Ildikó; Takács, Gábor; Botz, Lajos

2014-04-01

The increasing number of patients taking supplementary products together with prescribed medicines has become a new challenge for health care systems. These products may influence therapy outcomes by inducing unwanted effects. Particularly concerning is the potential for harmful interactions between prescribed medicines and supplementary products. The aims of the study were to evaluate supplement use, to identify and analyse potential interactions, and to assess the efficiency of computerised interaction screening. Participants of the study were inpatients and outpatients of a Hungarian university hospital. A cross-sectional point-of-care survey of 200 patients was carried out. Data was collected through personal interviews and a review of the medical records. Drug-drug, drug-supplement and supplement-supplement interactions were analysed with three interaction databases (Lexi-Interact Online, Medscape Drug Interaction Checker and Mediris). Prevalence of supplementary product use, number of medicines and supplementary products per patient, procurement sources of products, number of potentially severe interactions. There was a marked difference between data obtained from patient interviews and the medical records. 85.5 % of the surveyed patients took supplementary products during the 2 weeks prior to the interview. The average number of prescribed medicines and supplementary products were 7.8 and 2.5, respectively. Women were more likely to take supplements than men. There was no significant difference in supplement use between patients under or over 60 years, between inpatients and outpatients and among patients in various wards. 39.4 % of supplementary products were purchased outside a regulated pharmacy environment. Potentially severe drug-supplement interactions were detected with 45.2 % of supplement users; however the majority of interactions were not included in one or the other of the three databases. In addition to that the risk ratings of the same

The concomitant prescribing of ethinyl estradiol/drospirenone and potentially interacting drugs.

PubMed

McAdams, Mara; Staffa, Judy A; Dal Pan, Gerald J

2007-10-01

Ethinyl estradiol 0.03 mg/drospirenone 3 mg (EE/DRSP) contains a progestin drospirenone with antimineralocorticoid properties that may cause potassium retention leading to hyperkalemia. We estimated the percentage of EE/DRSP users prescribed concomitant potassium-sparing drugs [nonsteroidal antiinflammatory drugs, diuretics, angiotensin-converting enzyme inhibitors (with diuretics), angiotensin II agonists (with diuretics), and potassium chloride] between January 1, 2002, and March 31, 2005. We analyzed a population-based data set of 62,527 EE/DRSP users (Dimension Rx, Caremark). We compared the fill date and end date for each prescription (Rx) for an interacting drug to the start and end date for each EE/DRSP episode (linked Rxs). If a day of an interacting Rx overlapped with an EE/DRSP episode, concomitant prescribing was recorded. A total of 17.6% of the women concomitantly used EE/DRSP and an interacting drug. Twenty-nine percent of concomitant use occurred within a month of EE/DRSP initiation. Nonsteroidal antiinflammatory drugs and diuretics were most frequently used concomitantly with EE/DRSP. Forty percent of the women with concomitant use were 35 yearsof age or older at EE/DRSP initiation compared with 29% without concomitant use (p<.001). Obstetricians/gynecologists and family practitioners were the most common prescribers of EE/DRSP and potassium-sparing drugs, respectively. Concomitant prescribing of EE/DRSP and potassium-sparing drugs occurred frequently in our study population. As EE/DRSP becomes more widely used, physicians prescribing it should monitor patients for potassium-sparing drug use.

Interaction Patterns among Drug Dealers. Drug Abuse Information Research Project.

ERIC Educational Resources Information Center

Atkyns, Robert L.; Hanneman, Gerhard J.

Drug dealers are often popularly stereotyped as "pushers" who actively engage in enticing young people into the drug habit, but there have been no scientific studies of their behavior or their attitudes on drug abuse or public health. In an attempt to gain information about behavior characteristics and communication patterns of middle…

ITC commentary on the prediction of digoxin clinical drug-drug interactions from in vitro transporter assays.

PubMed

Lee, C A; Kalvass, J C; Galetin, A; Zamek-Gliszczynski, M J

2014-09-01

The "P-glycoprotein" IC50 working group reported an 18- to 796-fold interlaboratory range in digoxin transport IC50 (inhibitor concentration achieving 50% of maximal inhibition), raising concerns about the predictability of clinical transporter-based drug-drug interactions (DDIs) from in vitro data. This Commentary describes complexities of digoxin transport, which involve both uptake and efflux processes. We caution against attributing digoxin transport IC50 specifically to P-glycoprotein (P-gp) or extending this composite uptake/efflux IC50 variability to individual transporters. Clinical digoxin interaction studies should be interpreted as evaluation of digoxin safety, not P-gp DDIs.

Predicting Drug-Target Interactions Based on Small Positive Samples.

PubMed

Hu, Pengwei; Chan, Keith C C; Hu, Yanxing

2018-01-01

A basic task in drug discovery is to find new medication in the form of candidate compounds that act on a target protein. In other words, a drug has to interact with a target and such drug-target interaction (DTI) is not expected to be random. Significant and interesting patterns are expected to be hidden in them. If these patterns can be discovered, new drugs are expected to be more easily discoverable. Currently, a number of computational methods have been proposed to predict DTIs based on their similarity. However, such as approach does not allow biochemical features to be directly considered. As a result, some methods have been proposed to try to discover patterns in physicochemical interactions. Since the number of potential negative DTIs are very high both in absolute terms and in comparison to that of the known ones, these methods are rather computationally expensive and they can only rely on subsets, rather than the full set, of negative DTIs for training and validation. As there is always a relatively high chance for negative DTIs to be falsely identified and as only partial subset of such DTIs is considered, existing approaches can be further improved to better predict DTIs. In this paper, we present a novel approach, called ODT (one class drug target interaction prediction), for such purpose. One main task of ODT is to discover association patterns between interacting drugs and proteins from the chemical structure of the former and the protein sequence network of the latter. ODT does so in two phases. First, the DTI-network is transformed to a representation by structural properties. Second, it applies a oneclass classification algorithm to build a prediction model based only on known positive interactions. We compared the best AUROC scores of the ODT with several state-of-art approaches on Gold standard data. The prediction accuracy of the ODT is superior in comparison with all the other methods at GPCRs dataset and Ion channels dataset. Performance

Target-Independent Prediction of Drug Synergies Using Only Drug Lipophilicity

PubMed Central

2015-01-01

Physicochemical properties of compounds have been instrumental in selecting lead compounds with increased drug-likeness. However, the relationship between physicochemical properties of constituent drugs and the tendency to exhibit drug interaction has not been systematically studied. We assembled physicochemical descriptors for a set of antifungal compounds (“drugs”) previously examined for interaction. Analyzing the relationship between molecular weight, lipophilicity, H-bond donor, and H-bond acceptor values for drugs and their propensity to show pairwise antifungal drug synergy, we found that combinations of two lipophilic drugs had a greater tendency to show drug synergy. We developed a more refined decision tree model that successfully predicted drug synergy in stringent cross-validation tests based on only lipophilicity of drugs. Our predictions achieved a precision of 63% and allowed successful prediction for 58% of synergistic drug pairs, suggesting that this phenomenon can extend our understanding for a substantial fraction of synergistic drug interactions. We also generated and analyzed a large-scale synergistic human toxicity network, in which we observed that combinations of lipophilic compounds show a tendency for increased toxicity. Thus, lipophilicity, a simple and easily determined molecular descriptor, is a powerful predictor of drug synergy. It is well established that lipophilic compounds (i) are promiscuous, having many targets in the cell, and (ii) often penetrate into the cell via the cellular membrane by passive diffusion. We discuss the positive relationship between drug lipophilicity and drug synergy in the context of potential drug synergy mechanisms. PMID:25026390

Medication Interactions: Food, Supplements and Other Drugs

MedlinePlus

... for Heart.org CPR & ECC for Heart.org Shop for Heart.org Causes for Heart.org Advocate ... Aneurysm More Medication Interactions: Food, Supplements and Other Drugs Updated:Oct 15,2014 Some foods — even healthy ...

A high-speed drug interaction search system for ease of use in the clinical environment.

PubMed

Takada, Masahiro; Inada, Hiroshi; Nakazawa, Kazuo; Tani, Shoko; Iwata, Michiaki; Sugimoto, Yoshihisa; Nagata, Satoru

2012-12-01

With the advancement of pharmaceutical development, drug interactions have become increasingly complex. As a result, a computer-based drug interaction search system is required to organize the whole of drug interaction data. To overcome problems faced with the existing systems, we developed a drug interaction search system using a hash table, which offers higher processing speeds and easier maintenance operations compared with relational databases (RDB). In order to compare the performance of our system and MySQL RDB in terms of search speed, drug interaction searches were repeated for all 45 possible combinations of two out of a group of 10 drugs for two cases: 5,604 and 56,040 drug interaction data. As the principal result, our system was able to process the search approximately 19 times faster than the system using the MySQL RDB. Our system also has several other merits such as that drug interaction data can be created in comma-separated value (CSV) format, thereby facilitating data maintenance. Although our system uses the well-known method of a hash table, it is expected to resolve problems common to existing systems and to be an effective system that enables the safe management of drugs.

Herbal medicines in Brazil: pharmacokinetic profile and potential herb-drug interactions

PubMed Central

Mazzari, Andre L. D. A.; Prieto, Jose M.

2014-01-01

A plethora of active compounds found in herbal medicines can serve as substrate for enzymes involved in the metabolism of xenobiotics. When a medicinal plant is co-administered with a conventional drug and little or no information is known about the pharmacokinetics of the plant metabolites, there is an increased risk of potential herb-drug interactions. Moreover, genetic polymorphisms in a population may act to predispose individuals to adverse reactions. The use of herbal medicines is rapidly increasing in many countries, particularly Brazil where the vast biodiversity is a potential source of new and more affordable treatments for numerous conditions. Accordingly, the Brazilian Unified Public Health System (SUS) produced a list of 71 plant species of interest, which could be made available to the population in the near future. Physicians at SUS prescribe a number of essential drugs and should herbal medicines be added to this system the chance of herb-drug interactions further increases. A review of the effects of these medicinal plants on Phase 1 and Phase 2 metabolic mechanisms and the transporter P-glycoprotein was conducted. The results have shown that approximately half of these medicinal plants lack any pharmacokinetic data. Moreover, most of the studies carried out are in vitro. Only a few reports on herb-drug interactions with essential drugs prescribed by SUS were found, suggesting that very little attention is being given to the safety of herbal medicines. Here we have taken this information to discuss the potential interactions between herbal medicines and essential drugs prescribed to Brazilian patients whilst taking into account the most common polymorphisms present in the Brazilian population. A number of theoretical interactions are pinpointed but more pharmacokinetic studies and pharmacovigilance data are needed to ascertain their clinical significance. PMID:25071580

Pharmacokinetic properties and drug interactions of apigenin, a natural flavone.

PubMed

Tang, Ding; Chen, Keli; Huang, Luqi; Li, Juan

2017-03-01

Apigenin, a natural flavone, is widely distributed in plants such as celery, parsley and chamomile. It is present principally as glycosylated in nature. Higher intake of apigenin could reduce the risk of chronic diseases. It has gained particular interest in recent years as a beneficial, health-promoting agent with low intrinsic toxicity. Areas covered: This review summarizes and the absorption, distribution, metabolism and excretion (ADME) properties of apigenin, and drug-drug interaction of apigenin. Expert opinion: Since apigenin is a bioactive plant flavone and is widely distributed in common food, its consumption through the diet is recommended. Apigenin-enriched drugs are better for some chronic diseases, but may affect animal and human health if present in the daily diet. Dietary or therapeutic apigenin has value as a good cellular regulator in cancer, especially cancers of the gastrointestinal tract. Due to apigenin's limitations on absorption and bioavailability, novel carriers would need to be developed to enhance the oral bioavailability of apigenin. Further research about its ADME properties and drug-drug interactions are needed before apigenin can be brought to clinical trials.

Variable Linezolid Exposure in Intensive Care Unit Patients-Possible Role of Drug-Drug Interactions.

PubMed

Töpper, Christoph; Steinbach, Cathérine L; Dorn, Christoph; Kratzer, Alexander; Wicha, Sebastian G; Schleibinger, Michael; Liebchen, Uwe; Kees, Frieder; Salzberger, Bernd; Kees, Martin G

2016-10-01

Standard doses of linezolid may not be suitable for all patient groups. Intensive care unit (ICU) patients in particular may be at risk of inadequate concentrations. This study investigated variability of drug exposure and its potential sources in this population. Plasma concentrations of linezolid were determined by high-performance liquid chromatography in a convenience sample of 20 ICU patients treated with intravenous linezolid 600 mg twice daily. Ultrafiltration applying physiological conditions (pH 7.4/37°C) was used to determine the unbound fraction. Individual pharmacokinetic (PK) parameters were estimated by population PK modeling. As measures of exposure to linezolid, area under the concentration-time curve (AUC) and trough concentrations (Cmin) were calculated and compared with published therapeutic ranges (AUC 200-400 mg*h/L, Cmin 2-10 mg/L). Coadministered inhibitors or inducers of cytochrome P450 and/or P-glycoprotein were noted. Data from 18 patients were included into the PK evaluation. Drug exposure was highly variable (median, range: AUC 185, 48-618 mg*h/L, calculated Cmin 2.92, 0.0062-18.9 mg/L), and only a minority of patients had values within the target ranges (6 and 7, respectively). AUC and Cmin were linearly correlated (R = 0.98), and classification of patients (underexposed/within therapeutic range/overexposed) according to AUC or Cmin was concordant in 15 cases. Coadministration of inhibitors was associated with a trend to higher drug exposure, whereas 3 patients treated with levothyroxine showed exceedingly low drug exposure (AUC ∼60 mg*h/L, Cmin <0.4 mg/L). The median unbound fraction in all 20 patients was 90.9%. Drug exposure after standard doses of linezolid is highly variable and difficult to predict in ICU patients, and therapeutic drug monitoring seems advisable. PK drug-drug interactions might partly be responsible and should be further investigated; protein binding appears to be stable and irrelevant.

Interaction of injectable neurotropic drugs with the red cell membrane.

PubMed

Reinhart, Walter H; Lubszky, Szabina; Thöny, Sandra; Schulzki, Thomas

2014-10-01

The normal red blood cell (RBC) shape is a biconcave discocyte. An intercalation of a drug in the outer half of the membrane lipid bilayer leads to echinocytosis, an intercalation in the inner half to stomatocytosis. We have used the shape transforming capacity of RBCs as a model to analyse the membrane interaction potential of various neurotropic drugs. Chlorpromazine, clomipramine, citalopram, clonazepam, and diazepam induced a reversible stomatocytosis, phenytoin induced echinocytosis, while the anticonvulsants levetiracetam, valproic acid and phenobarbital had no effect. This diversity of RBC shape transformations suggests that the pharmacological action is not linked to the membrane interaction. We conclude that this simple RBC shape transformation assay could be a useful tool to screen for potential drug interactions with cell membranes. Copyright © 2014. Published by Elsevier Ltd.

Drug drug interaction extraction from the literature using a recursive neural network

PubMed Central

Lim, Sangrak; Lee, Kyubum

2018-01-01

Detecting drug-drug interactions (DDI) is important because information on DDIs can help prevent adverse effects from drug combinations. Since there are many new DDI-related papers published in the biomedical domain, manually extracting DDI information from the literature is a laborious task. However, text mining can be used to find DDIs in the biomedical literature. Among the recently developed neural networks, we use a Recursive Neural Network to improve the performance of DDI extraction. Our recursive neural network model uses a position feature, a subtree containment feature, and an ensemble method to improve the performance of DDI extraction. Compared with the state-of-the-art models, the DDI detection and type classifiers of our model performed 4.4% and 2.8% better, respectively, on the DDIExtraction Challenge’13 test data. We also validated our model on the PK DDI corpus that consists of two types of DDIs data: in vivo DDI and in vitro DDI. Compared with the existing model, our detection classifier performed 2.3% and 6.7% better on in vivo and in vitro data respectively. The results of our validation demonstrate that our model can automatically extract DDIs better than existing models. PMID:29373599

A Population-Based Assessment of the Drug Interaction Between Levothyroxine and Warfarin

PubMed Central

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

2013-01-01

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

[Antineoplastic oral agents and drug-nutrient interactions: a sistematic review].

PubMed

Jiménez Torres, N V; Romero Crespo, I; Ballester Solaz, M; Albert Marí, A; Jiménez Arenas, V

2009-01-01

Studies on bioavailability are part of the clinical development of drugs for oral use in order to identify potential drug-food interactions. For oral antitumor drugs, their clinical importance is currently recognized although regrettably the information available presents variability concerning the scientific evidence. To review the available scientific evidence about oral anti-tumor medications and establish the recommendations for their administration with foods. We carried out a bibliographic search in Medline and The Cochrane Library for the period January of 1966 to March of 2008, focused on identifying those publications about drug-food interactions with oral antitumor medications. The bibliographical analysis was made in two steps. During the first phase, we excluded those articles in which the title or their content did not correspond with the objective settled; during the second phase, we deleted all the references duplicated in both databases. The inclusion criteria to select the articles were: design (systematic reviews, meta-analysis, Phase I and Phase II randomized clinical trials), population (adult patients; >19 years of age), intervention evaluated (administration of oral anti-tumor drugs under fasting conditions or with food) and measurement of the iFA results (calculation of the 90% CI of the odds ratio between the geometric mean of the values under the curve of the plasma concentrations (ABC) or the maximal plasma concentration (Cmax) with and without foods). We excluded those publications that did not make reference to the bioequivalence dictamen established by the Food and Drugs Administration (FDA) in their outcomes measurement. A critical appraisal of the selected articles was done according to the recommendations that the FDA established to be met by these studies. At the initial search we obtained 850 references (98.5% Medline + and 1.4% Cochrane). During the first phase, we excluded 87.7% (746) of the articles, 100% of them corresponding

Drugs in hair. Part I. Metabolisms of major drug classes.

PubMed

White, R M

2017-01-01

Currently, hair can be reliably tested for the presence of drugs. However, one major drawback to the use of parent drugs is the question of potential external or environmental contamination. The analysis of metabolites to confirm the use of the parent drugs was proposed in this short review. The development of hair as a test matrix and the incorporation of xenobiotics, in general, into the hair matrix were discussed. What constitutes an appropriate metabolite for drug testing to mirror the use of a parent drug was proposed and discussed. The use of metabolites rather than parent drugs to indicate unequivocal use rather than external exposure was also discussed for amphetamines, cannabinoids, cocaine, opiates (codeine, morphine, 6-acetylmorphine, hydrocodone, hydromorphone, oxycodone, oxymorphone), phencyclidine, fentanyl, benzodiazepines, and ethanol. This, however, was discussed in terms of class and/or individual drug. In addition, selection or potential selection of appropriate metabolites was reviewed. The actual incorporation of drug metabolites into hair versus the metabolism of drugs which was incorporated into hair were also considered. Copyright © 2017 Central Police University.

Drug-nutrient interaction counseling programs in upper midwestern hospitals: 1986 survey results.

PubMed

Jones, C M; Reddick, J E

1989-02-01

A mail survey was conducted to determine the characteristics of drug-nutrient counseling programs provided to hospitalized patients. The survey population included general medical-surgical type hospitals with 175 or more bed capacity in five upper Midwestern states: Illinois, Iowa, Michigan, Minnesota, and Wisconsin. The average return from 289 surveys was 75%. A mean of 64% of responding hospitals provide patient counseling on drug-nutrient interactions. All statistical analysis was by chi-square. Calculations revealed that less than 50% of hospitals require a physician's order to provide drug-nutrient interaction counseling. More than 50% involve a registered dietitian in providing such counseling. The monoamine oxidase inhibitor drugs were cited most frequently as the group of drugs for which counseling was needed. Other drug groups for which patient counseling is needed include: diuretics, anticoagulants, tetracyclines, oral hypoglycemics, insulin, antihypertensives and/or cardiac drugs, antibiotics, and corticosteroids. Having the dietitian or other dietary personnel scan the patient chart was cited most often as the preferred method for detection of patients taking the drugs. A final statistical calculation revealed that there is no difference between teaching and nonteaching hospitals in the number providing a drug-nutrient counseling program.

Bile Acid-Based Drug Delivery Systems for Enhanced Doxorubicin Encapsulation: Comparing Hydrophobic and Ionic Interactions in Drug Loading and Release.

PubMed

Cunningham, Alexander J; Robinson, Mattieu; Banquy, Xavier; Leblond, Jeanne; Zhu, X X

2018-03-05

Doxorubicin (Dox) is a drug of choice in the design of drug delivery systems directed toward breast cancers, but is often limited by loading and control over its release from polymer micelles. Bile acid-based block copolymers present certain advantages over traditional polymer-based systems for drug delivery purposes, since they can enable a higher drug loading via the formation of a reservoir through their aggregation process. In this study, hydrophobic and electrostatic interactions are compared for their influence on Dox loading inside cholic acid based block copolymers. Poly(allyl glycidyl ether) (PAGE) and poly(ethylene glycol) (PEG) were grafted from the cholic acid (CA) core yielding a star-shaped block copolymer with 4 arms (CA-(PAGE- b-PEG) 4 ) and then loaded with Dox via a nanoprecipitation technique. A high Dox loading of 14 wt % was achieved via electrostatic as opposed to hydrophobic interactions with or without oleic acid as a cosurfactant. The electrostatic interactions confer a pH responsiveness to the system. 50% of the loaded Dox was released at pH 5 in comparison to 12% at pH 7.4. The nanoparticles with Dox loaded via hydrophobic interactions did not show such a pH responsiveness. The systems with Dox loaded via electrostatic interactions showed the lowest IC 50 and highest cellular internalization, indicating the pre-eminence of this interaction in Dox loading. The blank formulations are biocompatible and did not show cytotoxicity up to 0.17 mg/mL. The new functionalized star block copolymers based on cholic acid show great potential as drug delivery carriers.

HPLC-high-resolution mass spectrometry with polarity switching for increasing throughput of human in vitro cocktail drug-drug interaction assay.

PubMed

Ramanathan, Ragu; Ghosal, Anima; Ramanathan, Lakshmi; Comstock, Kate; Shen, Helen; Ramanathan, Dil

2018-05-01

Evaluation of HPLC-high-resolution mass spectrometry (HPLC-HRMS) full scan with polarity switching for increasing throughput of human in vitro cocktail drug-drug interaction assay. Microsomal incubates were analyzed using a high resolution and high mass accuracy Q-Exactive mass spectrometer to collect integrated qualitative and quantitative (qual/quant) data. Within assay, positive-to-negative polarity switching HPLC-HRMS method allowed quantification of eight and two probe compounds in the positive and negative ionization modes, respectively, while monitoring for LOR and its metabolites. LOR-inhibited CYP2C19 and showed higher activity for CYP2D6, CYP2E1 and CYP3A4. Overall, LC-HRMS-based nontargeted full scan quantitation allowed to improve the throughput of the in vitro cocktail drug-drug interaction assay.

Extracting sets of chemical substructures and protein domains governing drug-target interactions.

PubMed

Yamanishi, Yoshihiro; Pauwels, Edouard; Saigo, Hiroto; Stoven, Véronique

2011-05-23

The identification of rules governing molecular recognition between drug chemical substructures and protein functional sites is a challenging issue at many stages of the drug development process. In this paper we develop a novel method to extract sets of drug chemical substructures and protein domains that govern drug-target interactions on a genome-wide scale. This is made possible using sparse canonical correspondence analysis (SCCA) for analyzing drug substructure profiles and protein domain profiles simultaneously. The method does not depend on the availability of protein 3D structures. From a data set of known drug-target interactions including enzymes, ion channels, G protein-coupled receptors, and nuclear receptors, we extract a set of chemical substructures shared by drugs able to bind to a set of protein domains. These two sets of extracted chemical substructures and protein domains form components that can be further exploited in a drug discovery process. This approach successfully clusters protein domains that may be evolutionary unrelated but that bind a common set of chemical substructures. As shown in several examples, it can also be very helpful for predicting new protein-ligand interactions and addressing the problem of ligand specificity. The proposed method constitutes a contribution to the recent field of chemogenomics that aims to connect the chemical space with the biological space.

Information on actual medication use and drug-related problems in older patients: questionnaire or interview?

PubMed

Willeboordse, Floor; Grundeken, Lucienne H; van den Eijkel, Lisanne P; Schellevis, François G; Elders, Petra J M; Hugtenburg, Jacqueline G

2016-04-01

Information on medication use and drug-related problems is important in the preparation of clinical medication reviews. Critical information can only be provided by patients themselves, but interviewing patients is time-consuming. Alternatively, patient information could be obtained with a questionnaire. In this study the agreement between patient information on medication use and drug-related problems in older patients obtained with a questionnaire was compared with information obtained during an interview. General practice in The Netherlands. A questionnaire was developed to obtain information on actual medication use and drug-related problems. Two patient groups ≥65 years were selected based on general practitioner electronic medical records in nine practices; I. polypharmacy and II. ≥1 predefined general geriatric problems. Eligible patients were asked to complete the questionnaire and were interviewed afterwards. Agreement on information on medication use and drug-related problems collected with the questionnaire and interview was calculated. Ninety-seven patients participated. Of all medications used, 87.6 % (95 % CI 84.7-90.5) was reported identically in the questionnaire and interview. Agreement for the complete medication list was found for 45.4 % (95 % CI 35.8-55.3) of the patients. On drug-related problem level, agreement between questionnaire and interview was 75 %. Agreement tended to be lower in vulnerable patients characterized by ≥4 chronic diseases, ≥10 medications used and low health literacy. Information from a questionnaire showed reasonable agreement compared with interviewing. The patients reported more medications and drug-related problems in the interview than the questionnaire. Taking the limitations into account, a questionnaire seems a suitable tool for medication reviews that may replace an interview for most patients.

Acute kidney injury during concomitant use of valacyclovir and loxoprofen: detecting drug-drug interactions in a spontaneous reporting system.

PubMed