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药物研发中的反应表型分析:能否满怀信心地前行?

Reaction phenotyping in drug discovery: moving forward with confidence?

作者信息

Williams J Andrew, Hurst Susan I, Bauman Jonathan, Jones Barry C, Hyland Ruth, Gibbs John P, Obach R Scott, Ball Simon E

机构信息

Department of Pharmacokinetics, Pfizer Global Research and Development, 2800 Plymouth Road, Ann Arbor, Michigan 48105, USA.

出版信息

Curr Drug Metab. 2003 Dec;4(6):527-34. doi: 10.2174/1389200033489235.

Abstract

For the pharmaceutical industry, one of the challenges in evaluating the risk of future compound attrition at the discovery stage is the successful prediction of the major routes of clearance in humans. For compounds cleared by metabolism, such information will help to avoid the development of compounds that will exhibit large interpatient differences in pharmacokinetics via 1). routes of metabolism catalyzed by functionally polymorphic enzymes and/or 2). clinically significant metabolic drug-drug interactions, in the later stages of development. The degree of intersubject variability that is acceptable for a drug candidate is uncertain in the discovery stage where knowledge of other important factors is limited or unavailable (i.e. therapeutic index, pharmacodynamic variability, etc). Reaction phenotyping is the semi-quantitative in vitro estimation of the relative contributions of specific drug-metabolizing enzymes to the metabolism of a test compound. However, reaction phenotyping in the discovery stage of drug development is complicated by the absence of radiolabelled parent compound or metabolite bioanalytical standards relative to later stages of development. In this commentary, some of the approaches, based on published data, which can be taken to overcome these challenges are discussed. In addition, knowledge of the molecular structure (i.e. specific chemical substituents), physicochemical properties, and routes of clearance in animals can all help in making a successful prediction for the routes of clearance in humans. In combination, the objective of these studies should be to reduce to a minimum the risk of finding significant inter-patient differences in pharmacokinetics at a later stage in development due to significant metabolism by polymorphic enzymes or drug-drug interactions. Consequently, this data should be used to avoid costly late stage attrition.

摘要

对于制药行业而言,在发现阶段评估未来化合物淘汰风险的挑战之一是成功预测人体中的主要清除途径。对于通过代谢清除的化合物,此类信息将有助于避免开发在后期开发阶段会因以下情况而在药代动力学上表现出较大患者间差异的化合物:1)由功能多态性酶催化的代谢途径和/或2)具有临床意义的代谢性药物相互作用。在发现阶段,由于对其他重要因素(即治疗指数、药效学变异性等)的了解有限或无法获取,候选药物可接受的受试者间变异性程度尚不确定。反应表型分析是对特定药物代谢酶对测试化合物代谢的相对贡献进行的半定量体外评估。然而,与药物开发的后期阶段相比,在药物开发的发现阶段,由于缺乏放射性标记的母体化合物或代谢物生物分析标准品,反应表型分析变得复杂。在本评论中,将讨论一些基于已发表数据可用于克服这些挑战的方法。此外,了解分子结构(即特定化学取代基)、理化性质以及动物体内的清除途径,都有助于成功预测人体中的清除途径。综合起来,这些研究的目标应该是将开发后期因多态性酶的显著代谢或药物相互作用而在药代动力学上发现显著患者间差异的风险降至最低。因此,应利用这些数据避免代价高昂的后期淘汰。

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