Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California
Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California.
Drug Metab Dispos. 2021 Jul;49(7):530-539. doi: 10.1124/dmd.120.000315. Epub 2021 May 6.
Accurately predicting the pharmacokinetics of compounds that are transporter substrates has been notoriously challenging using traditional in vitro systems and physiologically based pharmacokinetic (PBPK) modeling. The objective of this study was to use PBPK modeling to understand the translational accuracy of data generated with human embryonic kidney 293 (HEK293) cells overexpressing the hepatic uptake transporters organic anion transporting polypeptide (OATP) 1B1/3 with and without plasma while accounting for transporter expression. Models of four OATP substrates, two with low protein binding (pravastatin and rosuvastatin) and two with high protein binding (repaglinide and pitavastatin) were explored, and the OATP in vitro data generated in plasma incubations were used for a plasma model, and in buffer incubations for a buffer model. The pharmacokinetic parameters and concentration-time profiles of pravastatin and rosuvastatin were similar and well predicted (within 2-fold of observed values) using the plasma and buffer models without needing an empirical scaling factor, whereas the dispositions of the highly protein bound repaglinide and pitavastatin were more accurately simulated with the plasma models than the buffer models. This work suggests that data from HEK293 overexpressing transporter cells corrected for transporter expression represent a valid approach to improve bottom-up PBPK modeling for highly protein bound OATP substrates with plasma incubations and low protein binding OATP substrates with or without plasma incubations. SIGNIFICANCE STATEMENT: This work demonstrates the bottom-up approach of using in vitro data directly without employing empirical scaling factors to predict the intravenous pharmacokinetic (PK) profiles reasonably well for four organic anion transporting polypeptide (OATP) substrates. Based on these results, using HEK293 overexpressing cells, examining the impact of plasma for highly bound compounds, and incorporating transporter quantitation for the lot in which the in vitro data were generated represents a valid approach to achieve more accurate prospective PK predictions for OATP substrates.
使用传统的体外系统和基于生理的药代动力学（PBPK）模型准确预测作为转运体底物的化合物的药代动力学一直是具有挑战性的。本研究的目的是使用 PBPK 模型来理解用过度表达肝摄取转运体有机阴离子转运多肽（OATP）1B1/3 的人胚肾 293（HEK293）细胞在有或没有血浆的情况下生成的数据的转化准确性，同时考虑转运体的表达。研究了四种 OATP 底物的模型，其中两种蛋白结合率低（普伐他汀和瑞舒伐他汀），两种蛋白结合率高（瑞格列奈和匹伐他汀），并用血浆孵育中生成的 OATP 体外数据建立了血浆模型，并用缓冲液孵育建立了缓冲液模型。普伐他汀和瑞舒伐他汀的药代动力学参数和浓度-时间曲线相似，并且使用血浆和缓冲液模型可以很好地预测（在观察值的 2 倍以内），而无需使用经验缩放因子，而高蛋白结合的瑞格列奈和匹伐他汀的处置则可以更准确地用血浆模型模拟，而不是缓冲液模型。这项工作表明，对于具有血浆孵育的高蛋白结合 OATP 底物和具有或不具有血浆孵育的低蛋白结合 OATP 底物，通过校正转运体表达，从过度表达转运体的 HEK293 细胞中获得的数据代表了一种改进自下而上的 PBPK 建模的有效方法。
这项工作表明，对于具有血浆孵育的高蛋白结合 OATP 底物和具有或不具有血浆孵育的低蛋白结合 OATP 底物，通过校正转运体表达，从过度表达转运体的 HEK293 细胞中获得的数据代表了一种改进自下而上的 PBPK 建模的有效方法。
