Mechanistic Pharmacokinetic Modeling for the Prediction of Transporter-Mediated Disposition in Humans from Sandwich Culture Human Hepatocyte Data
Mechanistic Pharmacokinetic Modeling for the Prediction of Transporter-Mediated Disposition in Humans from Sandwich Culture Human Hepatocyte Data
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DOI：
10.1124/dmd.111.042994
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发表时间：
2012-05-01
影响因子：
3.9
通讯作者：
Fenner, Katherine S.
中科院分区：
文献类型：
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作者：
Jones, Hannah M.;Barton, Hugh A.;Fenner, Katherine S.
随着在药物发现的早期阶段减少细胞色素p450介导的清除（CL）的努力，转运蛋白介导的CL机制变得越来越普遍。然而，与被动介导的药代动力学（PK）相比，使用基于生理的药代动力学（PBPK）模型预测这些化合物的血浆浓度-时间曲线的方法要少得多。在这项研究中，我们评估了七种有机阴离子转运多肽（OATP）底物（普伐他汀、西伐他汀、波生坦、氟伐他汀、瑞舒伐他汀、缬沙坦和瑞格列奈）对人体PK的可预测性，这些底物的临床静脉注射数据是可用的。从夹心培养的人肝细胞系统产生的体外数据同时拟合，以估计描述摄取和胆外排的参数。使用比例主动摄取、被动分布和胆道外排参数作为PBPK模型的输入，导致除了普伐他汀外，所有7种被调查药物的暴露量被高估。因此，对数据集中每种药物的体内数据进行拟合，以建立经验缩放因子，以准确捕获它们的血浆浓度-时间曲线。总体而言，主动摄取和胆外排被低估和高估，导致平均经验标度因子分别为58和0.061；被动扩散不需要比例因子。该研究阐明了体外摄取和外排数据在OATP底物人体PK预测中的机制和模型驱动应用。一个特别的优势是能够捕获多相血浆浓度-时间分布的这些化合物仅使用临床前数据。讨论了新型OATP底物的预测策略。
With efforts to reduce cytochrome P450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison with that for compounds with passively mediated pharmacokinetics (PK). In this study, we have assessed the predictability of human PK for seven organic anion-transporting polypeptide (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan, and repaglinide) for which clinical intravenous data were available. In vitro data generated from the sandwich culture human hepatocyte system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution, and biliary efflux parameters as inputs into a PBPK model resulted in the overprediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under- and overpredicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only preclinical data. A prediction strategy for novel OATP substrates is discussed.