College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L., M-S.K., J.K.); Laboratory of Quantitative System Pharmacokinetics/Pharmacodynamics, Josai International University, Tokyo, Japan (Y.A., Y.S.); and Drug Metabolism and Pharmacokinetics, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden (Y.A.)
College of Pharmacy and Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L., M-S.K., J.K.); Laboratory of Quantitative System Pharmacokinetics/Pharmacodynamics, Josai International University, Tokyo, Japan (Y.A., Y.S.); and Drug Metabolism and Pharmacokinetics, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden (Y.A.).
Drug Metab Dispos. 2023 Sep;51(9):1145-1156. doi: 10.1124/dmd.122.000968. Epub 2023 Mar 13.
Warfarin is well recognized for its high-affinity and capacity-limited binding to the pharmacological target and undergoes target-mediated drug disposition. Here, we developed a physiologically based pharmacokinetic (PBPK) model that incorporated saturable target binding and other reported hepatic disposition components of warfarin. The PBPK model parameters were optimized by fitting to the reported blood pharmacokinetic (PK) profiles of warfarin with no stereoisomeric separation after oral dosing of racemic warfarin (0.1, 2, 5, or 10 mg) using the Cluster Gauss-Newton method (CGNM). The CGNM-based analysis yielded multiple "accepted" sets for six optimized parameters, which were then used to simulate the warfarin blood PK and in vivo target occupancy (TO) profiles. When further analyses examined the impact of dose selection on uncertainty in parameter estimation by the PBPK modeling, the PK data from 0.1 mg dose (well below target saturation) was important in practically identifying the target binding-related parameters in vivo. When stereoselective differences were incorporated for both hepatic disposition and target interactions, our PBPK modeling predicted that R-warfarin (of slower clearance and lower target affinity than S-warfarin) contributes to TO prolongation after oral dosing of racemic warfarin. Our results extend the validity of the approach by which the PBPK-TO modeling of blood PK profiles can yield TO prediction in vivo (applicable to the drugs with targets of high affinity and abundance and limited distribution volume via nontarget interactions). Our findings support that model-informed dose selection and PBPK-TO modeling may aid in TO and efficacy assessment in preclinical and clinical phase 1 studies. SIGNIFICANCE STATEMENT: The current physiologically based pharmacokinetic modeling incorporated the reported hepatic disposition components and target binding of warfarin and analyzed the blood pharmacokinetic (PK) profiles from varying warfarin doses, practically identifying target binding-related parameters in vivo. By implementing the stereoselective differences between R- and S-warfarin, our analysis predicted the role of R-warfarin in prolonging overall target occupancy. Our results extend the validity of analyzing blood PK profiles to predict target occupancy in vivo, which may guide efficacy assessment.
华法林与药理学靶标具有高亲和力和容量限制结合，并经历靶介导的药物处置。在这里，我们开发了一种包含饱和靶结合和其他报道的华法林肝处置成分的生理相关药代动力学（PBPK）模型。通过使用聚类高斯-牛顿法（CGNM）拟合报道的华法林血药代动力学（PK）谱，优化 PBPK 模型参数，无需立体异构体分离，即可在口服外消旋华法林（0.1、2、5 或 10mg）后进行。CGNM 分析产生了六个优化参数的多个“接受”集，然后用于模拟华法林的血液 PK 和体内靶标占有率（TO）谱。当进一步的分析检查剂量选择对 PBPK 建模中参数估计的不确定性的影响时，PK 数据来自 0.1mg 剂量（远低于靶饱和度）在实际上确定体内靶结合相关参数方面非常重要。当纳入肝处置和靶相互作用的立体选择性差异时，我们的 PBPK 模型预测，在口服外消旋华法林后，R-华法林（比 S-华法林清除速度慢且靶亲和力低）有助于延长 TO。我们的结果扩展了通过 PBPK-TO 建模分析血 PK 谱可以在体内预测 TO 的方法的有效性（适用于具有高亲和力和丰度靶标以及通过非靶标相互作用限制分布容积的药物）。我们的发现支持模型指导的剂量选择和 PBPK-TO 建模可能有助于在临床前和临床 I 期研究中评估 TO 和疗效。意义声明：当前的生理相关药代动力学建模纳入了华法林的报道肝处置成分和靶结合，并分析了来自不同华法林剂量的血药代动力学（PK）谱，实际上确定了体内靶结合相关参数。通过实施 R-和 S-华法林之间的立体选择性差异，我们的分析预测了 R-华法林在延长整体靶标占有率中的作用。我们的结果扩展了分析血 PK 谱以预测体内靶标占有率的有效性，这可能指导疗效评估。
