The Influence of NSAIDs on Coumarin Sensitivity in Patients with CYP2C9 Polymorphism After Total Hip Replacement Surgery

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Risk prediction of drug-drug interaction potential of phenytoin and miconazole topical formulations

The drug-drug interaction (DDI) risk of phenytoin with several topical formulations of miconazole is still unclear. The present investigation conducted in vitro-in vivo extrapolation to predict the potential risks. Our data indicated that miconazole potently inhibited phenytoin hydroxylation in both pooled human liver microsomes (HLMs) and recombinant cytochrome P450 2C9 (CYP2C9) with the K_i values of 125 ± 7 nM and 30 ± 2 nM, respectively. Quantitative prediction of DDI risk suggests that, beside intravenous administration or swallowed tablet, combination of phenytoin and miconazole high dose oral gel or buccal tablet may also result in a clinically significant increase of phenytoin AUC (>53%) by the inhibition of miconazole against phenytoin hydroxylation, consequently a higher frequency of adverse events, while the coadministration of miconazole vaginal formulation and phenytoin will be safe.

Optimising Seniors' Metabolism of Medications and Avoiding Adverse Drug Events Using Data on How Metabolism by Their P450 Enzymes Varies with Ancestry and Drug-Drug and Drug-Drug-Gene Interactions

Many individuals ≥65 have multiple illnesses and polypharmacy. Primary care physicians prescribe >70% of their medications and renew specialists’ prescriptions. Seventy-five percent of all medications are metabolised by P450 cytochrome enzymes. This article provides unique detailed tables how to avoid adverse drug events and optimise prescribing based on two key databases. DrugBank is a detailed database of 13,000 medications and both the P450 and other complex pathways that metabolise them. The Flockhart Tables are detailed lists of the P450 enzymes and also include all the medications which inhibit or induce metabolism by P450 cytochrome enzymes, which can result in undertreatment, overtreatment, or potentially toxic levels. Humans have used medications for a few decades and these enzymes have not been subject to evolutionary pressure. Thus, there is enormous variation in enzymatic functioning and by ancestry. Differences for ancestry groups in genetic metabolism based on a worldwide meta-analysis are discussed and this article provides advice how to prescribe for individuals of different ancestry. Prescribing advice from two key organisations, the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium is summarised. Currently, detailed pharmacogenomic advice is only available in some specialist clinics in major hospitals. However, this article provides detailed pharmacogenomic advice for primary care and other physicians and also physicians working in rural and remote areas worldwide. Physicians could quickly search the tables for the medications they intend to prescribe.

Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC) for CYP2C9 and Nonsteroidal Anti-Inflammatory Drugs

Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most commonly used analgesics due to their lack of addictive potential. However, NSAIDs have the potential to cause serious gastrointestinal, renal, and cardiovascular adverse events. CYP2C9 polymorphisms influence metabolism and clearance of several drugs in this class, thereby affecting drug exposure and potentially safety. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for NSAIDs based on CYP2C9 genotype (updates at www.cpicpgx.org).

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

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.

Impact of CYP2C9 polymorphisms on the vulnerability to pharmacokinetic drug-drug interactions during acenocoumarol treatment

AIM

The objective of this study was to investigate the impact of CYP2C9 polymorphisms and drug-drug interactions on the risk of overanticoagulation in patients treated with acenocoumarol, a vitamin K antagonist.

MATERIALS & METHODS

A prospective observational study was performed on patients starting acenocoumarol (n = 115). CYP2C9 genotypes were assessed. Data on International Normalized Ratio, comedications and doses of acenocoumarol were collected during the first 35 days of therapy. Overanticoagulation was defined as the occurrence of at least one International Normalized Ratio ≥4.

RESULTS

The presence of a CYP2C9 inhibitor or a CYP2C9 polymorphisms statistically increased the risk of overanticoagulation (hazard ratio [HR]: 2.8, p < 0.001 and HR: 1.7, p = 0.04, respectively). The presence of CYP2C9 polymorphisms almost tripled the risk of overanticoagulation (HR: 2.91, p = 0.01) in the presence of a clinically significant drug-drug interaction.

CONCLUSION

These findings support the fact that CYP2C9 genotyping could be useful to identify patients requiring closer monitoring, especially when a drug-drug interaction is expected.

Polypharmacy and food-drug interactions among older persons: a review

Polypharmacy is generally defined as the use of 5 or more prescription medications on a regular basis. The average number of prescribed and over-the-counter medications used by community-dwelling older adults per day in the United States is 6 medications, and the number used by institutionalized older persons is 9 medications. Almost all medications affect nutriture, either directly or indirectly, and nutriture affects drug disposition and effect. This review will highlight the issues surrounding polypharmacy, food-drug interactions, and the consequences of these interactions for the older adult.

Genetic polymorphism and toxicology--with emphasis on cytochrome p450

Individual susceptibility to environmental, chemical, and drug toxicity is to some extent determined by polymorphism in drug-metabolizing enzymes, in particular the cytochromes P450 (CYPs). This polymorphism is in particular translated into risk differences concerning drugs metabolized by the highly polymorphic enzymes CYP2C9, CYP2C19, and CYP2D6, whereas CYP enzymes active in procarcinogen activation are relatively well conserved without important functional polymorphisms. Examples of drug toxicities that can be predicted by P450 polymorphism include those exerted by codeine, tramadol, warfarin, acenocoumarol, and clopidogrel. The polymorphic CYP2A6 has a role in nicotine metabolism and smoking behavior. Besides this genetic variation, genome-wide association studies now allow for the identification of an increasing number of predictive genetic biomarkers among, e.g., human leukocyte antigens and to some extent drug transporters that provide useful information regarding the choice of the drug and drug dosage in order to avoid toxicity. The translation of this information into the clinical practice has been slow; however, an increasing number of pharmacogenomic drug labels are assigned, where the predictive genotyping before drug treatment can be mandatory, recommended, or only for informational purposes. In this review, we provide an update of the field with emphasis on CYP polymorphism.