Finding a needle in the haystack: ADME and pharmacokinetics/pharmacodynamics characterization and optimization toward orally available bifunctional protein degraders

干草堆 广告 药代动力学 药效学 药理学 医学 计算机科学 万维网
作者
Giulia Apprato,Giulia Caron,Gauri Deshmukh,Diego J. Jiménez,Robin Thomas Ulrich Haid,Andy Pike,Andreas Reichel,Caroline Rynn,Zhang Donglu,Matthias Wittwer
出处
期刊:Expert Opinion on Drug Discovery [Taylor & Francis]
被引量:2
标识
DOI:10.1080/17460441.2025.2467195
摘要

Degraders are an increasingly important sub-modality of small molecules as illustrated by an ever-expanding number of publications and clinical candidate molecules in human trials. Nevertheless, their preclinical optimization of ADME and PK/PD properties has remained challenging. Significant research efforts are being directed to elucidate underlying principles and to derive rational optimization strategies. In this review the authors summarize current best practices in terms of in vitro assays and in vivo experiments. Furthermore, the authors collate and comment on the current understanding of optimal physicochemical characteristics and their impact on absorption, distribution, metabolism and excretion properties including the current knowledge of Drug-Drug interactions. Finally, the authors describe the Pharmacokinetic prediction and Pharmacokinetic/Pharmacodynamic -concepts unique to degraders and how to best implement these in research projects. Despite many recent advances in the field, continued research will further our understanding of rational design regarding degrader optimization. Machine-learning and computational approaches will become increasingly important once larger, more robust datasets become available. Furthermore, tissue-targeting approaches (particularly regarding the Central Nervous System will be increasingly studied to elucidate efficacious drug regimens that capitalize on the catalytic mode of action. Finally, additional specialized approaches (e.g. covalent degraders, LOVdegs) can enrich the field further and offer interesting alternative approaches.
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