De Buck Stefan S, Sinha Vikash K, Fenu Luca A, Nijsen Marjoleen J, Mackie Claire E, Gilissen Ron A H J
Johnson and Johnson Pharmaceutical Research and Development, Discovery ADME-Tox Department, Beerse, Belgium.
Drug Metab Dispos. 2007 Oct;35(10):1766-80. doi: 10.1124/dmd.107.015644. Epub 2007 Jul 9.
The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics.
本研究的目的是评估不同的基于生理学的建模策略，用于预测人体药代动力学。对26种经临床测试的药物进行了静脉给药和口服给药后的血浆浓度曲线模拟。评估了两种基于物理化学输入的人体组织与血浆分配系数（P(tp)）的基于机制的预测方法（方法Vd1）描述人体稳态分布容积（V(ss)）的能力。将该方法与一种结合预测的和实验测定的体内大鼠P(tp)数据的策略（方法Vd2）进行了比较。使用方法Vd2可获得最佳的V(ss)预测结果，前提是对大鼠P(tp)输入进行血浆蛋白结合种间差异校正（2倍范围内84%）。仅基于物理化学输入的V(ss)预测较差（2倍范围内32%）。总体清除率（CL）预测为按比例缩放的大鼠肾清除率与根据体外代谢数据推算的肝清除率之和。通过忽略血液以及微粒体或肝细胞结合可获得最佳的CL预测结果（方法CL2，2倍范围内74%），而同时考虑血液以及微粒体或肝细胞结合时则存在较大偏差（方法CL1，2倍范围内53%）。结合方法Vd2和CL2的基于生理学的药代动力学（PBPK）模型对体内终末半衰期的预测最为准确（2倍范围内69%）。使用Gastroplus高级房室吸收和转运模型构建了吸收-处置模型，并对血浆浓度-时间曲线下面积、口服表观分布容积和口服给药后的最大血浆浓度进行了准确预测，分别在2倍范围内为74%、70%和65%。该评估表明，PBPK模型可对人体药代动力学进行合理预测。
