Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, San Diego, CA, USA.
Drug Metab Dispos. 2011 Mar;39(3):383-93. doi: 10.1124/dmd.110.035857. Epub 2010 Nov 23.
The objective of this study was to assess the physiologically based pharmacokinetic (PBPK) model for predicting plasma concentration-time profiles of orally available cMet kinase inhibitors, (R)-3-[1-(2,6-dichloro-3-fluoro-phenyl)-ethoxy]-5-(1-piperidin-4-yl-1H-pyrazol-4-yl)-pyridin-2-ylamine (PF02341066) and 2-[4-(3-quinolin-6-ylmethyl-3H-[1,2,3]triazolo[4,5-b]pyrazin-5-yl)-pyrazol-1-yl]-ethanol (PF04217903), in humans. The prediction accuracy of pharmacokinetics (PK) by PBPK modeling was compared with that of a traditional one-compartment PK model based on allometric scaling. The predicted clearance values from allometric scaling with the correction for the interspecies differences in protein binding were used as a representative comparison, which showed more accurate PK prediction in humans than the other methods. Overall PBPK modeling provided better prediction of the area under the plasma concentration-time curves for both PF02341066 (1.2-fold error) and PF04217903 (1.3-fold error) compared with the one-compartment PK model (1.8- and 1.9-fold errors, respectively). Of more importance, the simulated plasma concentration-time profiles of PF02341066 and PF04217903 by PBPK modeling seemed to be consistent with the observed profiles showing multiexponential declines, resulting in more accurate prediction of the apparent half-lives (t(1/2)): the observed and predicted t(1/2) values were, respectively, 10 and 12 h for PF02341066 and 6.6 and 6.3 h for PF04217903. The predicted t(1/2) values by the one-compartment PK model were 17 h for PF02341066 and 1.9 h for PF04217903. Therefore, PBPK modeling has the potential to be more useful and reliable for the PK prediction of PF02341066 and PF04217903 in humans than the traditional one-compartment PK model. In summary, the present study has shown examples to indicate that the PBPK model can be used to predict PK profiles in humans.
本研究旨在评估基于生理的药代动力学(PBPK)模型预测口服 cMet 激酶抑制剂(R)-3-[1-(2,6-二氯-3-氟-苯基)-乙氧基]-5-(1-哌啶-4-基-1H-吡唑-4-基)-吡啶-2-胺(PF02341066)和 2-[4-(3-喹啉-6-基甲基-3H-[1,2,3]三唑并[4,5-b]吡嗪-5-基)-吡唑-1-基]-乙醇(PF04217903)在人体内的血浆浓度-时间曲线。通过 PBPK 建模与基于体表面积比例缩放的传统单室药代动力学模型进行比较,评估了药代动力学(PK)的预测准确性。使用基于体表面积比例缩放并校正种间蛋白结合差异的预测清除值作为代表性比较,结果表明该方法在人体中的 PK 预测更为准确。总体而言,与单室 PK 模型相比,PBPK 模型对 PF02341066(1.2 倍误差)和 PF04217903(1.3 倍误差)的血浆浓度-时间曲线下面积的预测更为准确(分别为 1.8-1.9 倍误差)。更重要的是,通过 PBPK 建模模拟的 PF02341066 和 PF04217903 的血浆浓度-时间曲线似乎与观察到的多指数下降曲线一致,从而更准确地预测表观半衰期(t(1/2)):观察到的和预测的 t(1/2)值分别为 PF02341066 的 10 和 12 h,PF04217903 的 6.6 和 6.3 h。单室 PK 模型预测的 PF02341066 的 t(1/2)值为 17 h,PF04217903 的 t(1/2)值为 1.9 h。因此,与传统的单室 PK 模型相比,PBPK 模型在预测 PF02341066 和 PF04217903 在人体中的 PK 方面具有更大的实用性和可靠性。总之,本研究提供了一些实例,表明 PBPK 模型可用于预测人体的 PK 曲线。