-
The American Journal of Managed Care Nov 2022Drug-drug interactions (DDIs) are among the most common causes of adverse drug reactions and are further complicated by genetic variants of drug-metabolizing enzymes....
OBJECTIVES
Drug-drug interactions (DDIs) are among the most common causes of adverse drug reactions and are further complicated by genetic variants of drug-metabolizing enzymes. The aim of this study is to quantify and describe potential DDIs, drug-gene interactions (DGIs), and drug-drug-gene interactions (DDGIs) in a community-based population.
STUDY DESIGN
This was an analysis of deidentified retail pharmacy prescription data for 4761 individuals.
METHODS
Data were first assessed for DDIs, and individuals were stratified to a risk category using the logic of a commercially available digital DDGI tool. To calculate the frequency of potential DGIs and DDGIs, genotypes were imputed and randomly allocated to the cohort 100 times via Monte Carlo simulation according to each variant's frequency in the general population.
RESULTS
The probability of a DDI of any impact was 26.0% and increased to 49.6% (95% CI, 48.4%-50.7%) when drug-metabolizing phenotypes were ascribed according to the distribution of variants of 11 genes as found in a Caucasian population. There was a 7.8% probability of major DDIs, which increased to a 10.1% (95% CI, 9.5%-10.8%) probability with the addition of genetic contributions. The probability of DDGIs of any impact was correlated with the number of medications. Antidepressants, antiemetics, blood products and modifiers, analgesics, and antipsychotics had the highest probability of DDGIs.
CONCLUSIONS
The probability of drug interaction risk increased when phenotypes associated with genetic polymorphisms were attributed to the population. These data suggest that pharmacogenomic assessment may be useful in predicting drug interactions and severity when evaluating patient medication profiles.
Topics: Humans; Pharmacies; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Genotype
PubMed: 36374614
DOI: 10.37765/ajmc.2022.89259 -
Pharmacology & Therapeutics Sep 2019In the United States, the evolving landscape of state-legal marijuana use for recreational and/or medical purposes has given rise to flourishing markets for marijuana... (Review)
Review
In the United States, the evolving landscape of state-legal marijuana use for recreational and/or medical purposes has given rise to flourishing markets for marijuana and derivative products. The popularity of these products highlights the relative absence of safety, pharmacokinetic, and drug interaction data for marijuana and its constituents, most notably the cannabinoids. This review articulates current issues surrounding marijuana terminology, taxonomy, and dosing; summarizes cannabinoid pharmacology and pharmacokinetics; and assesses the drug interaction risks associated with co-consuming marijuana with conventional medications. Existing pharmacokinetic data are currently insufficient to fully characterize potential drug interactions precipitated by marijuana constituents. As such, increasing awareness among researchers, clinicians, and federal agencies regarding the need to conduct well-designed in vitro and clinical studies is imperative. Mechanisms that help researchers navigate the legal and regulatory barriers to conducting these studies would promote rigorous evaluation of potential marijuana-drug interactions and inform health care providers and consumers about the possible risks of co-consuming marijuana products with conventional medications.
Topics: Animals; Cannabinoids; Drug Interactions; Humans; Marijuana Use
PubMed: 31071346
DOI: 10.1016/j.pharmthera.2019.05.001 -
Expert Review of Clinical Pharmacology Jul 2014Concomitant administration of multiple drugs can lead to unanticipated drug interactions and resultant adverse drug events with their associated costs. A more thorough... (Review)
Review
Concomitant administration of multiple drugs can lead to unanticipated drug interactions and resultant adverse drug events with their associated costs. A more thorough understanding of the different cytochrome P450 isoenzymes and drug transporters has led to new methods to try to predict and prevent clinically relevant drug interactions. There is also an increased recognition of the need to identify the impact of pharmacogenetic polymorphisms on drug interactions. More stringent regulatory requirements have evolved for industry to classify cytochrome inhibitors and inducers, test the effect of drug interactions in the presence of polymorphic enzymes, and evaluate multiple potentially interacting drugs simultaneously. In clinical practice, drug alert software programs have been developed. This review discusses drug interaction mechanisms and strategies for screening and minimizing exposure to drug interactions. We also provide future perspectives for reducing the risk of clinically significant drug interactions.
Topics: Cytochrome P-450 Enzyme System; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacogenetics; Risk
PubMed: 24745854
DOI: 10.1586/17512433.2014.910111 -
Journal of Clinical Pharmacy and... Oct 2022Antiretrovirals have a high drug interaction potential, which can lead to increased toxicity and/or decreased efficacy. Multiple databases are available to assess...
WHAT IS KNOWN AND OBJECTIVE
Antiretrovirals have a high drug interaction potential, which can lead to increased toxicity and/or decreased efficacy. Multiple databases are available to assess drug-drug interactions. The aim of our study was to compare interaction identification for commonly used ARVs and concomitant medications between six different online drug-drug interaction databases.
COMMENT
This was a cross-sectional review using each of the following six databases: LexiComp®, Clinical Pharmacology®, Micromedex®, Epocrates®, University of Liverpool, and University of Toronto. Sixteen antiretroviral drugs and 100 of the DrugStats Database "Top 200 of 2019" list of medications were included. Each of the six databases identified a different number of actual or potential interactions. The number of interactions ranged from 211 to 283.
WHAT IS NEW AND CONCLUSIONS
A variety of databases exist with inconsistent identification of actual or potential drug-drug interactions amongst them. It may be beneficial to cross-reference multiple databases prior to making decisions regarding patient care.
Topics: Anti-Retroviral Agents; Cross-Sectional Studies; Databases, Factual; Drug Interactions; HIV Infections; Humans
PubMed: 36059105
DOI: 10.1111/jcpt.13750 -
The AAPS Journal Jul 2013Recently, the US Food and Drug Administration and European Medicines Agency have issued new guidance for industry on drug interaction studies, which outline... (Review)
Review
Recently, the US Food and Drug Administration and European Medicines Agency have issued new guidance for industry on drug interaction studies, which outline comprehensive recommendations on a broad range of in vitro and in vivo studies to evaluate drug-drug interaction (DDI) potential. This paper aims to provide an overview of these new recommendations and an in-depth scientifically based perspective on issues surrounding some of the recommended approaches in emerging areas, particularly, transporters and complex DDIs. We present a number of theoretical considerations and several case examples to demonstrate complexities in applying (1) the proposed transporter decision trees and associated criteria for studying a broad spectrum of transporters to derive actionable information and (2) the recommended model-based approaches at an early stage of drug development to prospectively predict DDIs involving time-dependent inhibition and mixed inhibition/induction of drug metabolizing enzymes. We hope to convey the need for conducting DDI studies on a case-by-case basis using a holistic scientifically based interrogative approach and to communicate the need for additional research to fill in knowledge gaps in these areas where the science is rapidly evolving to better ensure the safety and efficacy of new therapeutic agents.
Topics: Animals; Drug Interactions; European Union; Humans; Pharmaceutical Preparations; Practice Guidelines as Topic; United States; United States Food and Drug Administration
PubMed: 23543602
DOI: 10.1208/s12248-013-9470-x -
American Journal of Veterinary Research Nov 2021To assess drug-drug interactions between cannabidiol (CBD) and phenobarbital (PB) when simultaneously administered to healthy dogs.
OBJECTIVE
To assess drug-drug interactions between cannabidiol (CBD) and phenobarbital (PB) when simultaneously administered to healthy dogs.
ANIMALS
9 healthy, purpose bred Beagles.
PROCEDURES
A 3-phase prospective, randomized pharmacokinetic (PK) interaction study of CBD and PB was performed as follows: phase 1, CBD PK determination and evaluation of CBD tolerability by 3 single-dose CBD (5 mg/kg, 10 mg/kg, and 20 mg/kg) protocols followed by 2-week CBD dosing; phase 2, a single-dose, 3-way, crossover PK study of CBD (10 mg/kg), PB (4 mg/kg), or CBD (10 mg/kg) administration plus PB (4 mg/kg); and phase 3, evaluation of chronic PB (4 mg/kg, q 30 d) administration followed by single-dose CBD (10 mg/kg) PK study.
RESULTS
Although there were variations in CBD PK variables in dogs receiving CBD alone or in conjunction with PB, significance differences in CBD PK variables were not found. No significant difference was observed in PB PK variables of dogs receiving PB alone or with CBD. During chronic CBD administration, mild gastrointestinal signs were observed in 5 dogs. At daily CBD doses of 10 to 20 mg/kg/d, hypoxia was observed in 5 dogs and increased serum alkaline phosphatase (ALP) activities (range, 301 to 978 U/L) was observed in 4 dogs. A significant increase in ALP activity was observed with chronic administration of CBD during phase 1 between day 0 and day 14.
CONCLUSIONS AND CLINICAL RELEVANCE
No significant PK interactions were found between CBD and PB. Dose escalation of CBD or adjustment of PB in dogs is not recommended on the basis of findings of this study.
Topics: Animals; Cannabidiol; Dogs; Drug Interactions; Pharmaceutical Preparations; Phenobarbital; Prospective Studies
PubMed: 34727050
DOI: 10.2460/ajvr.21.08.0120 -
British Journal of Clinical Pharmacology May 2022We aimed to investigate the effect of omeprazole on the pharmacokinetics (PK) of pyrotinib and determine the safety of this combination in healthy Chinese volunteers.
AIMS
We aimed to investigate the effect of omeprazole on the pharmacokinetics (PK) of pyrotinib and determine the safety of this combination in healthy Chinese volunteers.
METHODS
Eighteen healthy volunteers were enrolled in this single-dose and self-controlled study. Pyrotinib (400 mg per oral) was administered 30 minutes after the standard meal. Omeprazole was administered from day 6 (D6) to D10 (40 mg, per oral). On D10, the subjects took omeprazole under fasting conditions, followed by pyrotinib 30 minutes after the standard meal. Blood samples for PK analyses in each phase were collected for analysing the drug concentration. Safety was assessed via clinical laboratory tests and physical examinations.
RESULTS
Compared with a single dose of pyrotinib, pyrotinib coadministered with omeprazole showed no significant difference in exposure, elimination, half-life and apparent clearance rate. The mixed-effects model revealed that the least-squares geometric mean ratios of area under the concentration-time curve (AUC) , AUC and maximum plasma concentration (C 90% confidence intervals) of pyrotinib alone and pyrotinib coadministered with omeprazole were 0.94 (0.82, 1.08), 0.94 (0.83, 1.08) and 0.91 (0.806, 1.038), respectively, indicating the absence of significant differences in AUC , AUC and C . During the treatment period, 6 subjects (33.3%) reported 8 adverse events during pyrotinib monotherapy and omeprazole administration, respectively; 10 subjects (55.6%) reported 34 adverse events in the combined administration phase.
CONCLUSION
Omeprazole, a proton-pump inhibitor, did not significantly impact the PK properties of pyrotinib, and a good safety profile was observed on coadministration.
Topics: Acrylamides; Aminoquinolines; Area Under Curve; Cross-Over Studies; Drug Interactions; Humans; Omeprazole
PubMed: 34873745
DOI: 10.1111/bcp.15169 -
Advances in Clinical and Experimental... Aug 2023The majority of Americans, accounting for 51% of the population, take 2 or more drugs daily. Unfortunately, nearly 100,000 people die annually as a result of adverse...
The majority of Americans, accounting for 51% of the population, take 2 or more drugs daily. Unfortunately, nearly 100,000 people die annually as a result of adverse drug reactions (ADRs), making it the 4th most common cause of mortality in the USA. Drug-drug interactions (DDls) and their impact on patients represent critical challenges for the healthcare system. To reduce the incidence of ADRs, this study focuses on identifying DDls using a machine-learning approach. Drug-related information was obtained from various free databases, including DrugBank, BioGRID and Comparative Toxicogenomics Database. Eight similarity matrices between drugs were created as covariates in the model in order to assess their infiuence on DDls. Three distinct machine learning algorithms were considered, namely, logistic regression (LR), extreme Gradient Boosting (XGBoost) and neural network (NN). Our study examined 22 notable drugs and their interactions with 841 other drugs from DrugBank. The accuracy of the machine learning approaches ranged from 68% to 78%, while the F1 scores ranged from 78% to 83%. Our study indicates that enzyme and target similarity are the most significant parameters in identifying DDls. Finally, our data-driven approach reveals that machine learning methods can accurately predict DDls and provide additional insights in a timely and cost-effective manner.
Topics: Humans; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Algorithms; Databases, Factual; Machine Learning
PubMed: 37589227
DOI: 10.17219/acem/169852 -
Journal of Food and Drug Analysis Apr 2018Medicinal 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... (Review)
Review
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.
Topics: Animals; Drugs, Chinese Herbal; Herb-Drug Interactions; Humans; Plants, Medicinal; Pregnane X Receptor
PubMed: 29703383
DOI: 10.1016/j.jfda.2017.11.007 -
Health Informatics Journal 2022Drug-drug interaction (DDI) alerts are frequently included in electronic medical record (eMR) systems to provide users with relevant information and guidance at the...
Drug-drug interaction (DDI) alerts are frequently included in electronic medical record (eMR) systems to provide users with relevant information and guidance at the point of care. In this study, we aimed to examine views of DDI alerts among prescribers, including junior doctors, registrars and senior doctors, across Australia. A validated survey for assessing prescribers' reported acceptance and use of DDI alerts was distributed among researcher networks and in newsletters. Fifty useable responses were received, more than half ( = 28) from senior doctors. Prescribers at all levels expected DDI alerts to improve performance but junior doctors reported that this was at a high cost, with respect to time and effort. Senior doctors and registrars reported rarely reading alerts and rarely changing prescribing decisions based on alerts. Respondents identified a number of problems with current alerts including limited relevance, repetition, and poor design, highlighting some clear areas for alert improvement.
Topics: Australia; Decision Support Systems, Clinical; Drug Interactions; Humans; Medical Order Entry Systems; Physicians; Surveys and Questionnaires
PubMed: 35531625
DOI: 10.1177/14604582221100678