Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland.
Drug Metab Dispos. 2020 Oct;48(10):849-860. doi: 10.1124/dmd.120.000133. Epub 2020 Aug 1.
In vitro to in vivo extrapolation (IVIVE) to predict human hepatic clearance, including metabolism and transport, requires extensive experimental resources. In addition, there may be technical challenges to measure low clearance values. Therefore, prospective identification of rate-determining step(s) in hepatic clearance through application of the Extended Clearance Classification System (ECCS) could be beneficial for optimal compound characterization. IVIVE for hepatic intrinsic clearance (CLint,h) prediction is conducted for a set of 36 marketed drugs with low-to-high in vivo clearance, which are substrates of metabolic enzymes and active uptake transporters in the liver. The compounds were assigned to the ECCS classes, and CLint,h, estimated with HepatoPac (a micropatterned hepatocyte coculture system), was compared with values calculated based on suspended hepatocyte incubates. An apparent permeability threshold (apical to basal) of 50 nm/s in LLC-PK1 cells proved optimal for ECCS classification. A reasonable performance of the IVIVE for compounds across multiple classes using HepatoPac was achieved (with 2-3-fold error), except for substrates of uptake transporters (class 3b), for which scaling of uptake clearance using plated hepatocytes is more appropriate. Irrespective of the ECCS assignment, metabolic clearance can be estimated well using HepatoPac. The validation and approach elaborated in the present study can result in proposed decision trees for the selection of the optimal in vitro assays guided by ECCS class assignment, to support compound optimization and candidate selection. SIGNIFICANCE STATEMENT: Characterization of the rate-determining step(s) in hepatic elimination could be on the critical path of compound optimization during drug discovery. This study demonstrated that HepatoPac and plated hepatocytes are suitable tools for the estimation of metabolic and active uptake clearance, respectively, for a larger set of marketed drugs, supporting a comprehensive strategy to select optimal in vitro tools and to achieve Extended Clearance Classification System-dependent in vitro to in vivo extrapolation for human clearance prediction.
体外到体内外推（IVIVE）预测人体肝清除率，包括代谢和转运，需要广泛的实验资源。此外，测量低清除率值可能存在技术挑战。因此，通过应用扩展清除分类系统（ECCS）前瞻性地识别肝清除率的限速步骤（s）可能有助于优化化合物特征。对一组具有低至高体内清除率的 36 种市售药物进行 IVIVE 预测，这些药物是肝脏代谢酶和主动摄取转运体的底物。这些化合物被分配到 ECCS 类别中，并使用 HepatoPac（一种微图案化肝细胞共培养系统）估计 CLint,h，并与基于悬浮肝细胞孵育计算的值进行比较。在 LLC-PK1 细胞中，50nm/s 的表观渗透阈值（顶底）被证明是 ECCS 分类的最佳选择。使用 HepatoPac 对多个类别中的化合物进行 IVIVE 的性能良好（误差为 2-3 倍），除了摄取转运体的底物（类别 3b），对于这些底物，使用贴壁肝细胞进行摄取清除的缩放更为合适。无论 ECCS 分类如何，使用 HepatoPac 都可以很好地估计代谢清除率。本研究中验证和阐述的方法可以为基于 ECCS 分类的最佳体外测定选择提出决策树，以支持化合物优化和候选物选择。意义：在药物发现过程中，特征化肝消除的限速步骤（s）可能是化合物优化的关键路径。本研究表明，HepatoPac 和贴壁肝细胞分别是估计较大一组市售药物的代谢和主动摄取清除率的合适工具，支持选择最佳体外工具的综合策略，并实现基于扩展清除分类系统的体外到体内外推，以预测人体清除率。
