Pharmacogenetic guided drug therapy - how to deal with phenoconversion in polypharmacy.

Julia Carolin Stingl, Roberto Viviani
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Abstract

Introduction: The prevalence of polypharmacy and the increasing availability of pharmacogenetic information in clinical practice have raised the prospect of data-driven clinical decision-making when addressing the issues of drug-drug interactions and genetic polymorphisms in metabolizing enzymes. Inhibition of metabolizing enzymes in drug interactions can lead to genotype-phenotype discrepancies (phenoconversion) that reduce the relevance of individual pharmacogenetic information.

Areas covered: The aim of this review is to provide an overview of existing models of phenoconversion, and we discuss how phenoconversion models may be developed to estimate joint drug-interactions and genetic effects. Based on a literature search in PubMed, Google Scholar, and reference lists from review articles, we provide an overview of the current models of phenoconversion. The currently applied phenoconversion models are presented and discussed to predict the effects of drug-drug interactions while accounting for the pharmacogenetic status of patients.

Expert opinion: While pharmacogenetic-dose recommendations alone are most relevant for rare and extreme genotypes, phenoconversion may increase the prevalence of these phenotypes. Therefore, in polypharmacy conditions, phenoconversion assessment is especially important for personalized drug therapy.

药物遗传学引导药物治疗-如何处理多药的表型转化?
导言:多药的流行和临床实践中药物遗传信息的日益可用性,在解决药物-药物相互作用和代谢酶遗传多态性问题时,提高了数据驱动的临床决策的前景。药物相互作用中代谢酶的抑制可导致基因型-表型差异(表型转化),从而降低个体药物遗传信息的相关性。涵盖领域:本综述的目的是概述现有的表型转化模型,并讨论如何开发表型转化模型来估计联合药物相互作用和遗传效应。基于PubMed、b谷歌Scholar和综述文章的参考文献列表,我们对表型转化的当前模型进行了概述。介绍了目前应用的表型转换模型,并讨论了预测药物-药物相互作用的影响,同时考虑了患者的药理学状态。专家意见:虽然药物遗传剂量建议单独与罕见和极端基因型最相关,但表型转化可能会增加这些表型的患病率。因此,在多药条件下,表型转化评估对个性化药物治疗尤为重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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