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Recent advances in preclinical in?vitro approaches towards quantitative prediction of hepatic clearance and drug-drug interactions involving organic anion transporting polypeptide (OATP) 1B transporters

机译:临床前进的临床前进的临床前进的定量预测肝脏清除和药物 - 药物相互作用的定量预测,涉及有机阴离子输送多肽(OATP)1B转运蛋白

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Hepatic uptake mediated by organic anion transporting polypeptide (OATP) 1B1 and 1B3 can serve as a major elimination pathway for various anionic drugs and as a site of drug-drug interactions (DDIs). This article provides an overview of the in?vitro approaches used to predict human hepatic clearance (CLsubh/sub) and the risk of DDIs involving OATP1Bs. On the basis of the so-called extended clearance concept, in vitro–in vivo extrapolation methods using human hepatocytes as in?vitro systems have been used to predict the CLsubh/sub involving OATP1B-mediated hepatic uptake. CLsubh/sub can be quantitatively predicted using human donor lots possessing adequate OATP1B activities. The contribution of OATP1Bs to hepatic uptake can be estimated by the relative activity factor, the relative expression factor, or selective inhibitor approaches, which offer generally consistent outcomes. In OATP1B1 inhibition assays, substantial substrate dependency was observed. The time-dependent inhibition of OATP1B1 was also noted and may be a mechanism underlying the in vitro–in vivo differences in the inhibition constant of cyclosporine A. Although it is still challenging to quantitatively predict CLsubh/sub and DDIs involving OATP1Bs from only preclinical data, understanding the utility and limitation of the current in?vitro methods will pave the way for better prediction.
机译:由有机阴离子输送多肽(OATP)1B1和1B3介导的肝脏摄取可作为各种阴离子药物的主要消除途径,作为药物 - 药物相互作用(DDIS)的部位。本文概述了用于预测人类肝脏间隙(Cl H )的体外方法以及涉及oatp1bs的DDI的风险。基于所谓的延伸间隙概念,在体外使用人肝细胞的体内外推方法已经用于预测涉及oatp1b介导的肝摄取的Cl h 。 CL H 可以使用具有足够的oatp1b活动的人体供体批次定量预测。可以通过相对活动因子,相对表达因子或选择性抑制剂方法估算OATP1BS至肝脏摄取的贡献,其提供通常一致的结果。在oATP1B1抑制测定中,观察到基本基底依赖性。还注意到oATP1B1对oATP1B1的时间依赖性抑制,并且可以是环孢素A的抑制常数在体外差异的机制。尽管定量预测CL H 和DDIS仍然挑战仍然具有挑战性涉及oatp1bs从临床前数据,了解电流的实用性和限制的体外方法将为更好的预测铺平。

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