Systems Modeling and Simulation, Medicine Design (R.L., D.A.T., T.S.M.) and Pharmacokinetics, Dynamics, and Metabolism (A.F.E.-K.), Medicine Design, Pfizer Worldwide R&D, Cambridge, Massachusetts; and Pharmacokinetics, Dynamics, and Metabolism, Medicine Design, Pfizer Worldwide R&D, Groton, Connecticut (M.N., N.J., E.K., J.L., X.Y., K.A.R., S.R., L.M.T., L.D.)
Systems Modeling and Simulation, Medicine Design (R.L., D.A.T., T.S.M.) and Pharmacokinetics, Dynamics, and Metabolism (A.F.E.-K.), Medicine Design, Pfizer Worldwide R&D, Cambridge, Massachusetts; and Pharmacokinetics, Dynamics, and Metabolism, Medicine Design, Pfizer Worldwide R&D, Groton, Connecticut (M.N., N.J., E.K., J.L., X.Y., K.A.R., S.R., L.M.T., L.D.).
Drug Metab Dispos. 2018 Apr;46(4):346-356. doi: 10.1124/dmd.117.078790. Epub 2018 Jan 12.
Understanding liver exposure of hepatic transporter substrates in clinical studies is often critical, as it typically governs pharmacodynamics, drug-drug interactions, and toxicity for certain drugs. However, this is a challenging task since there is currently no easy method to directly measure drug concentration in the human liver. Using bosentan as an example, we demonstrate a new approach to estimate liver exposure based on observed systemic pharmacokinetics from clinical studies using physiologically based pharmacokinetic modeling. The prediction was verified to be both accurate and precise using sensitivity analysis. For bosentan, the predicted pseudo steady-state unbound liver-to-unbound systemic plasma concentration ratio was 34.9 (95% confidence interval: 4.2, 50). Drug-drug interaction (i.e., CYP3A and CYP2B6 induction) and inhibition of hepatic transporters (i.e., bile salt export pump, multidrug resistance-associated proteins, and sodium-taurocholate cotransporting polypeptide) were predicted based on the estimated unbound liver tissue or plasma concentrations. With further validation and refinement, we conclude that this approach may serve to predict human liver exposure and complement other methods involving tissue biopsy and imaging.
在临床研究中,了解肝转运体底物的肝脏暴露情况通常至关重要,因为它通常决定着某些药物的药效学、药物相互作用和毒性。然而,这是一项具有挑战性的任务,因为目前尚无直接测量人肝内药物浓度的简单方法。本文以波生坦为例,展示了一种新的方法,该方法基于临床研究中观察到的系统药代动力学,使用基于生理的药代动力学模型来估算肝脏暴露情况。通过敏感性分析验证了预测的准确性和精密度。对于波生坦,预测的假稳态游离肝脏与游离系统血浆浓度比为 34.9(95%置信区间:4.2,50)。根据估算的游离肝组织或血浆浓度,预测了药物相互作用(即 CYP3A 和 CYP2B6 诱导)和肝转运体的抑制(即胆汁盐输出泵、多药耐药相关蛋白和牛磺胆酸钠共转运多肽)。通过进一步验证和完善,我们得出结论,该方法可用于预测人体肝脏暴露情况,并补充其他涉及组织活检和成像的方法。