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从体外数据预测人体清除率。

Predicting clearance in humans from in vitro data.

机构信息

Pharmacokinetics, Dynamics, and Drug Metabolism, Pfizer Inc., Groton, CT 06340, USA.

出版信息

Curr Top Med Chem. 2011;11(4):334-9. doi: 10.2174/156802611794480873.

Abstract

The use of in vitro metabolism in scaling to predict human clearance of new chemical entities has become a commonplace activity in the research and development of new drugs. The measurement of in vitro lability in human liver microsomes, a rich source of drug metabolizing cytochrome P450 enzymes, has become a high throughput screen in many research organizations which is a testament to its usefulness in drug design. In this chapter, the methods used to scale in vitro clearance data to predict in vivo clearance are described. Importantly, the numerous assumptions that are required in order to use in vitro data in this manner are laid out. These include assumptions regarding the scaling process as well as technical aspects of the generation of the in vitro data. Finally, some other drug clearance processes that have been emerging as important are described with regard to ongoing research efforts to develop clearance prediction methods.

摘要

在新药研发中,将体外代谢用于预测新化学实体的人体清除率已成为一种常见的活动。在许多研究机构中,测量人肝微粒体中的体外不稳定性(药物代谢细胞色素 P450 酶的丰富来源)已成为高通量筛选,这证明了其在药物设计中的有用性。在本章中,描述了将体外清除率数据外推以预测体内清除率的方法。重要的是,列出了为以这种方式使用体外数据而需要的众多假设。这些假设包括关于外推过程以及体外数据生成的技术方面的假设。最后,描述了一些作为重要的其他药物清除过程,以及正在努力开发清除预测方法的相关研究进展。

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