Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Biotransformation and ADME, Research and Development, Orion Corporation, Espoo, Finland.
Drug Metab Rev. 2021 May;53(2):173-187. doi: 10.1080/03602532.2021.1910292. Epub 2021 May 11.
Many drug candidates fail during preclinical and clinical trials due to variable or unexpected metabolism which may lead to variability in drug efficacy or adverse drug reactions. The drug metabolism field aims to address this important issue from many angles which range from the study of drug-drug interactions, pharmacogenomics, computational metabolic modeling, and others. This manuscript aims to provide brief but comprehensive manuscript summaries highlighting the conclusions and scientific importance of seven exceptional manuscripts published in recent years within the field of drug metabolism. Two main topics within the field are reviewed: novel computational metabolic modeling approaches which provide complex outputs beyond site of metabolism predictions, and experimental approaches designed to discern the impacts of interindividual variability and species differences on drug metabolism. The computational approaches discussed provide novel outputs in metabolite structure and formation likelihood and/or extend beyond the saturated field of drug phase I metabolism, while the experimental metabolic pathways assessments aim to highlight the impacts of genetic polymorphisms and clinical animal model metabolic differences on human metabolism and subsequent health outcomes.
由于代谢的可变性或不可预测性,许多候选药物在临床前和临床试验中失败,这可能导致药物疗效或不良反应的差异。药物代谢领域旨在从多个角度解决这个重要问题,包括药物相互作用、药物基因组学、计算代谢建模等方面的研究。本文旨在提供简短但全面的文献综述,总结近年来药物代谢领域七篇杰出文献的结论和科学重要性。本文综述了该领域的两个主要主题:提供超出代谢部位预测的复杂输出的新型计算代谢建模方法,以及旨在辨别个体间变异性和物种差异对药物代谢影响的实验方法。所讨论的计算方法在代谢物结构和形成可能性方面提供了新颖的输出,或者扩展了药物 I 期代谢饱和领域,而实验代谢途径评估旨在强调遗传多态性和临床动物模型代谢差异对人类代谢和随后健康结果的影响。