Department of Pharmacokinetics, Dynamics, and Drug Metabolism, Pfizer Global Research & Development, Pfizer Inc, Groton, Connecticut 06340, USA.
Mol Pharm. 2010 Jun 7;7(3):630-41. doi: 10.1021/mp9001574.
Previously we have reported that hepatobiliary transporter expressions in sandwich cultured hepatocytes (SCH) are altered 2- to 5-fold. This change could limit the model's predictive power for in vivo biliary clearance. The present study was designed to better establish in vitro to in vivo correlation (IVIVC) of biliary clearance. Eleven compounds representing the substrates of Mrp2/Abcc2, Bcrp/Abcg2 and Bsep/Abcb11 were tested in the sandwich cultured rat hepatocyte (SCRH) model. Simultaneously, the absolute difference of hepatobiliary transporters between rat livers and SCRH at day 5 post culture was determined by LC-MS/MS. This difference was integrated into the well-stirred hepatic prediction model. A correction factor named "g_factor" was mathematically defined to reflect the difference in hepatobiliary transporter expressions between the SCRH model and in vivo models, as well as the contribution of multiple transporters. When the g_factor correction was applied, the in vivo biliary clearance prediction was significantly improved. In addition, for those compounds which are poorly permeable and/or undergo transporter-dependent active uptake, the known intracellular concentrations of substrates were used to estimate intrinsic bile clearance. This led to further improvement in the prediction of in vivo bile secretion. While the rate-limiting processes of uptake transporters in the SCRH model remain to be further determined, we showed that integration of the absolute difference of hepatobiliary transporter proteins and transport contributions could improve the predictability of SCRH model. This integration is fundamental for increased confidence in the IVIVC of human biliary clearance.
先前我们已经报道过,三明治培养的肝细胞(SCH)中的肝胆转运体表达水平发生了 2-5 倍的改变。这种变化可能会限制该模型对体内胆汁清除率的预测能力。本研究旨在更好地建立体外至体内相关性(IVIVC)的胆汁清除率。我们在三明治培养的大鼠肝细胞(SCRH)模型中测试了 11 种代表 Mrp2/Abcc2、Bcrp/Abcg2 和 Bsep/Abcb11 底物的化合物。同时,通过 LC-MS/MS 测定了第 5 天培养后大鼠肝脏和 SCRH 之间肝胆转运体的绝对差异。该差异被整合到搅拌良好的肝脏预测模型中。通过数学定义了一个名为“g_factor”的校正因子,以反映 SCRH 模型与体内模型之间的肝胆转运体表达差异,以及多种转运体的贡献。当应用 g_factor 校正时,体内胆汁清除率的预测得到了显著改善。此外,对于那些渗透性差和/或经历转运体依赖性主动摄取的化合物,已知的底物细胞内浓度被用来估计内在胆汁清除率。这导致了对体内胆汁分泌的预测的进一步改善。虽然 SCRH 模型中摄取转运体的限速过程仍有待进一步确定,但我们表明,整合肝胆转运蛋白的绝对差异和转运贡献可以提高 SCRH 模型的可预测性。这种整合对于提高人类胆汁清除的 IVIVC 置信度至关重要。