Abstract

Drug interactions are a well-known cause of adverse drug events, and drug interaction databases can help the clinician to recognize and avoid such interactions and their adverse events. However, not every interaction leads to an adverse drug event. This is because the clinical relevance of drug–drug interactions also depends on the genetic profile of the patient. If inhibitors or inducers of drug metabolising enzymes (e.g., CYP and UGT) are added to the drug therapy, phenoconcversion can occur. This leads to a genetic phenotype that mismatches the observable phenotype. Drug–drug–gene and drug–gene–gene interactions influence the toxicity and/or ineffectivness of the drug therapy. To date, there have been limited published studies on the impact of genetic variations on drug–drug interactions. This review discusses the current evidence of drug–drug–gene interactions, as well as drug–gene–gene interactions. Phenoconversion is explained, the and methods to calculate the phenotypes are described. Clinical recommendations are given regarding the integratation of the PGx results in the assessment of the relevance of drug interactions in the future.

Highlights

  • Klinik für Psychische Gesundheit, Klinikum Frankfurt Höchst, 65929 Frankfurt, Germany; Abstract: Drug interactions are a well-known cause of adverse drug events, and drug interaction databases can help the clinician to recognize and avoid such interactions and their adverse events

  • We provide a framework for the classification of pharmacokinetic

  • For example, showed that there was an increase in the escitalopram levels of 95% and 30% in the poor and intermediate metabolizers of CYP2C19 compared to normal metabolizers, respectively

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Summary

Intoduction

Drug–Drug-Interactions (DDI) are a well-known cause of adverse drug events [1,2,3]. The number of potential drug interactions increases exponentially with the number of taken drugs, making it hard to consider all drug interactions in polypharmacy patients. Despite wide inter- and intra-genotype variability in the metabolic capacity, clinical responses are thought to be simple binary outcomes for genotype groups The aim of these studies was to examine the strength of the associations between genotype and clinical phenotype and, if shown to be strong, to develop a dosing regimen appropriate to each genotype. Most guidelines on DDIs neither consider the potential effect of genetic polymorphisms in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and DGI when there are multiple biotransformation pathways, referred to as DGGI. Not surprisingly those guidelines often contradict each other [8]. DDGIs and DGGIs caused by different mechanisms, and their potential impact on drug serum levels in the context of polypharmacy

Pharmacokinetic Drug–Drug Interactions
Drug–Gene Interactions
Explanation how transferaaSNP
Metabolism
DMEs of Phase 2 Metabolism
Findings
Conclusions
Full Text
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