Laboratory of Molecular Pharmacokinetics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.
Laboratory of Quantitative System Pharmacokinetics/Pharmacodynamics, School of Pharmacy, Josai International University, Tokyo, Japan.
Clin Transl Sci. 2022 Jun;15(6):1519-1531. doi: 10.1111/cts.13272. Epub 2022 May 2.
The accurate prediction of OATP1B-mediated drug-drug interactions (DDIs) is challenging for drug development. Here, we report a physiologically-based pharmacokinetic (PBPK) model analysis for clinical DDI data generated in heathy subjects who received oral doses of cyclosporin A (CysA; 20 and 75 mg) as an OATP1B inhibitor, and the probe drugs (pitavastatin, rosuvastatin, and valsartan). PBPK models of CysA and probe compounds were combined assuming inhibition of hepatic uptake of endogenous coproporphyrin I (CP-I) by CysA. In vivo K of unbound CysA for OATP1B (K ), and the overall intrinsic hepatic clearance per body weight of CP-I (CL ) were optimized to account for the CP-I data (K , 0.536 ± 0.041 nM; CL , 41.9 ± 4.3 L/h/kg). DDI simulation using K reproduced the dose-dependent effect of CysA (20 and 75 mg) and the dosing interval (1 and 3 h) on the time profiles of blood concentrations of pitavastatin and rosuvastatin, but DDI simulation using in vitro K failed. The Cluster Gauss-Newton method was used to conduct parameter optimization using 1000 initial parameter sets for the seven pharmacokinetic parameters of CP-I (β, CL , F F , R , f , f , and v ), and K and K of CysA. Based on the accepted 546 parameter sets, the range of CL and K was narrowed, with coefficients of variation of 12.4% and 11.5%, respectively, indicating that these parameters were practically identifiable. These results suggest that PBPK model analysis of CP-I is a promising translational approach to predict OATP1B-mediated DDIs in drug development.
准确预测有机阴离子转运多肽 1B(OATP1B)介导的药物相互作用(DDI)对药物开发具有挑战性。在这里,我们报告了一种基于生理学的药代动力学(PBPK)模型分析,用于分析健康受试者接受环孢素 A(CysA;20 和 75mg)作为 OATP1B 抑制剂和探针药物(匹伐他汀、瑞舒伐他汀和缬沙坦)口服剂量时产生的临床 DDI 数据。假设 CysA 抑制内源性粪卟啉 I(CP-I)的肝摄取,将 CysA 和探针化合物的 PBPK 模型组合在一起。优化了未结合 CysA 对 OATP1B 的体内 K(K)和 CP-I 的整体内在肝清除率(CL),以解释 CP-I 数据(K,0.536±0.041nM;CL,41.9±4.3L/h/kg)。使用 K 进行 DDI 模拟再现了 CysA(20 和 75mg)和给药间隔(1 和 3h)对匹伐他汀和瑞舒伐他汀血药浓度时间曲线的剂量依赖性影响,但使用体外 K 进行 DDI 模拟失败。使用聚类高斯-牛顿法对 CP-I 的 7 个药代动力学参数(β、CL、FF、R、f、f和 v)和 CysA 的 K 和 K 进行了 1000 个初始参数集的参数优化。基于被接受的 546 个参数集,缩小了 CL 和 K 的范围,变异系数分别为 12.4%和 11.5%,表明这些参数具有实际可识别性。这些结果表明,CP-I 的 PBPK 模型分析是一种有前途的转化方法,可用于预测药物开发中的 OATP1B 介导的 DDI。