Hurel Corporation, Bervely Hills, CA 91201, USA.
Expert Opin Drug Metab Toxicol. 2010 Feb;6(2):189-98. doi: 10.1517/17425250903405622.
The use of intrinsic metabolic stability/clearance and other in vitro pharmacokinetic data for the selection of drug candidates for clinical evaluation during discovery lead optimization has become one of the primary focuses of research organizations involved in new drug discovery. Using intrinsic clearance determined from human liver microsomal preparations and/or hepatocyte to predict human clearance has become more acceptable.
This review focuses on the current methods for determining intrinsic clearance and scaling to predict human hepatic clearance, and novel physiologically-based models for improvement of human hepatic clearance prediction. Published microsomal metabolic stability data and in-house hepatocyte clearance data were compared with published in vivo human hepatic clearance data. Various scaling models and the effect of protein binding were examined.
Use of a novel microfluidic model and other physiologically-based models are presented. Microsomal metabolic clearance requires correction for protein binding and in vitro microsomal binding in order to better predict in vivo hepatic clearance of compounds that are mainly eliminated by hepatic metabolism.
Metabolic clearance obtained using hepatocytes may work well in combination with the well-stirred model. Novel models incorporating flow and protein binding in the system may be the most complete models for prediction of human in vivo metabolism.
在发现先导优化过程中，使用内在代谢稳定性/清除率和其他体外药代动力学数据来选择候选药物进行临床评估，已成为参与新药发现的研究机构的主要关注点之一。使用从人肝微粒体制剂和/或肝细胞中确定的内在清除率来预测人体清除率已变得更加可接受。
本综述重点介绍了目前用于确定内在清除率和缩放以预测人体肝清除率的方法，以及用于改善人体肝清除率预测的新型基于生理的模型。比较了发表的微粒体代谢稳定性数据和内部肝细胞清除率数据与已发表的体内人体肝清除率数据。检查了各种缩放模型和蛋白质结合的影响。
介绍了新型微流控模型和其他基于生理的模型。为了更好地预测主要通过肝代谢消除的化合物的体内肝清除率，需要对微粒体代谢清除率进行校正，以校正蛋白质结合和体外微粒体结合。
使用肝细胞获得的代谢清除率可能与完全混合模型结合使用效果良好。在系统中纳入流动和蛋白质结合的新型模型可能是预测人体体内代谢的最完整模型。
