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临床前药代动力学和药效学数据转化的 和 模型的最新进展。

Recent developments in and models for improved translation of preclinical pharmacokinetics and pharmacodynamics data.

机构信息

Department of Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck & Co., Inc., Boston, MA, USA.

Faculty of Pharmacy, Université de Montréal, Montréal, Canada.

出版信息

Drug Metab Rev. 2021 May;53(2):207-233. doi: 10.1080/03602532.2021.1922435. Epub 2021 May 25.

Abstract

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new and strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

摘要

在药物开发的早期阶段,改善药代动力学/药效学(PK/PD)预测对于指导先导化合物优化策略和降低淘汰率至关重要。最近,在开发新的和改进的策略方面取得了重大进展,以更好地描述药物先导化合物的药代动力学性质和疗效。在此,我们综述了清除预测的实验和数学模型的进展,开发新工具以捕获代谢缓慢的药物的进展,以及为支持药物开发而捕获人类病因的模型开发,讨论了这些努力的局限性和差距,并对该领域的未来进行了展望。

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