Ke A, Barter Z, Rowland-Yeo K, Almond L
Simcyp Limited (a Certara Company), Sheffield, UK.
CPT Pharmacometrics Syst Pharmacol. 2016 Jul;5(7):367-76. doi: 10.1002/psp4.12088. Epub 2016 Jul 20.
In this study, we present efavirenz physiologically based pharmacokinetic (PBPK) model development as an example of our best practice approach that uses a stepwise approach to verify the different components of the model. First, a PBPK model for efavirenz incorporating in vitro and clinical pharmacokinetic (PK) data was developed to predict exposure following multiple dosing (600 mg q.d.). Alfentanil i.v. and p.o. drug-drug interaction (DDI) studies were utilized to evaluate and refine the CYP3A4 induction component in the liver and gut. Next, independent DDI studies with substrates of CYP3A4 (maraviroc, atazanavir, and clarithromycin) and CYP2B6 (bupropion) verified the induction components of the model (area under the curve [AUC] ratios within 1.0-1.7-fold of observed). Finally, the model was refined to incorporate the fractional contribution of enzymes, including CYP2B6, propagating autoinduction into the model (Racc 1.7 vs. 1.7 observed). This validated mechanistic model can now be applied in clinical pharmacology studies to prospectively assess both the victim and perpetrator DDI potential of efavirenz.
在本研究中，我们展示了依法韦仑基于生理的药代动力学（PBPK）模型的开发过程，以此作为我们最佳实践方法的一个示例，该方法采用逐步方式来验证模型的不同组成部分。首先，开发了一个纳入体外和临床药代动力学（PK）数据的依法韦仑PBPK模型，以预测多次给药（每日600毫克）后的暴露情况。利用阿芬太尼静脉注射和口服的药物相互作用（DDI）研究来评估和完善肝脏和肠道中的CYP3A4诱导成分。接下来，使用CYP3A4（马拉维若、阿扎那韦和克拉霉素）和CYP2B6（安非他酮）底物进行的独立DDI研究验证了模型的诱导成分（曲线下面积[AUC]比值在观察值的1.0至1.7倍范围内）。最后，对模型进行完善，纳入包括CYP2B6在内的酶的分数贡献，将自身诱导作用纳入模型（预测值与观察值的比值为1.7 vs. 1.7）。这个经过验证的机制模型现在可应用于临床药理学研究，以前瞻性地评估依法韦仑作为受害者和肇事者的DDI潜力。
