Ke Alice Ban, Nallani Srikanth C, Zhao Ping, Rostami-Hodjegan Amin, Unadkat Jashvant D
Department of Pharmaceutics, University of Washington, Seattle, WA, USA; Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Br J Clin Pharmacol. 2014 Mar;77(3):554-70. doi: 10.1111/bcp.12207.
Conducting PK studies in pregnant women is challenging. Therefore, we asked if a physiologically-based pharmacokinetic (PBPK) model could be used to predict the disposition in pregnant women of drugs cleared by multiple CYP enzymes.
We expanded and verified our previously published pregnancy PBPK model by incorporating hepatic CYP2B6 induction (based on in vitro data), CYP2C9 induction (based on phenytoin PK) and CYP2C19 suppression (based on proguanil PK), into the model. This model accounted for gestational age-dependent changes in maternal physiology and hepatic CYP3A, CYP1A2 and CYP2D6 activity. For verification, the pregnancy-related changes in the disposition of methadone (cleared by CYP2B6, 3A and 2C19) and glyburide (cleared by CYP3A, 2C9 and 2C19) were predicted.
Predicted mean post-partum to second trimester (PP : T2 ) ratios of methadone AUC, Cmax and Cmin were 1.9, 1.7 and 2.0, vs. observed values 2.0, 2.0 and 2.6, respectively. Predicted mean post-partum to third trimester (PP : T3 ) ratios of methadone AUC, Cmax and Cmin were 2.1, 2.0 and 2.4, vs. observed values 1.7, 1.7 and 1.8, respectively. Predicted PP : T3 ratios of glyburide AUC, Cmax and Cmin were 2.6, 2.2 and 7.0 vs. observed values 2.1, 2.2 and 3.2, respectively.
Our PBPK model integrating prior physiological knowledge, in vitro and in vivo data, allowed successful prediction of methadone and glyburide disposition during pregnancy. We propose this expanded PBPK model can be used to evaluate different dosing scenarios, during pregnancy, of drugs cleared by single or multiple CYP enzymes.
在孕妇中开展药代动力学(PK)研究具有挑战性。因此,我们探讨了基于生理学的药代动力学(PBPK)模型是否可用于预测经多种细胞色素P450(CYP)酶清除的药物在孕妇体内的处置情况。
我们通过将肝脏CYP2B6诱导(基于体外数据)、CYP2C9诱导(基于苯妥英PK)和CYP2C19抑制(基于氯胍PK)纳入模型,对我们之前发表的妊娠PBPK模型进行了扩展和验证。该模型考虑了孕龄相关的母体生理学变化以及肝脏CYP3A、CYP1A2和CYP2D6活性。为进行验证,预测了美沙酮(经CYP2B6、3A和2C19清除)和格列本脲(经CYP3A、2C9和2C19清除)处置过程中与妊娠相关的变化。
预测的美沙酮曲线下面积(AUC)、最大血药浓度(Cmax)和最小血药浓度(Cmin)产后至孕中期(PP∶T2)比值分别为1.9、1.7和2.0,而观察值分别为2.0、2.0和2.6。预测的美沙酮AUC、Cmax和Cmin产后至孕晚期(PP∶T3)比值分别为2.1、2.0和2.4,而观察值分别为1.7、1.7和1.8。预测的格列本脲AUC、Cmax和Cmin的PP∶T3比值分别为2.6、2.2和7.0,而观察值分别为2.1、2.2和3.2。
我们整合了先前生理学知识、体外和体内数据的PBPK模型成功预测了妊娠期间美沙酮和格列本脲的处置情况。我们建议,这个扩展的PBPK模型可用于评估孕期经单一或多种CYP酶清除的药物的不同给药方案。