A mechanistic physiologically based pharmacokinetic-enzyme turnover model involving both intestine and liver to predict CYP3A induction-mediated drug-drug interactions
A mechanistic physiologically based pharmacokinetic-enzyme turnover model involving both intestine and liver to predict CYP3A induction-mediated drug-drug interactions
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一种涉及肠道和肝脏的基于机械生理学的药代动力学酶周转模型，用于预测 CYP3A 诱导介导的药物相互作用
DOI：
10.1002/jps.23613
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发表时间：
2013-08-01
影响因子：
3.8
通讯作者：
Liu, Xiaodong
中科院分区：
文献类型：
--
作者：
Guo, Haifang;Liu, Can;Liu, Xiaodong
细胞色素P450（CYP）3A诱导介导的药物相互作用（DDI）是药物开发和临床实践中的主要关注点之一。本研究的目的是开发一种新的机制生理为基础的药代动力学（PBPK）-酶周转模型，涉及肠道和肝脏CYP 3A诱导定量预测CYP 3A诱导介导的DDI的体外数据的大小。肠道P-糖蛋白（P-gp）的贡献也被纳入PBPK模型。首先，使用开发的模型成功预测了3种诱导剂和14种CYP 3A底物的药代动力学曲线，预测的血浆浓度-时间曲线下面积（AUC）[血浆浓度-时间曲线下面积]和峰浓度（C-max）[峰浓度]与报告值一致。该模型进一步应用于预测三种诱导剂和14种CYP 3A底物之间的DDI。结果显示，在存在和不存在诱导剂的情况下，23项DDI研究中的17项（74%）和17项DDI研究中的14项（82%）的预测AUC和C-max比值分别在观察值的两倍范围内。以上结果表明，所建立的PBPK-酶周转模型在定量预测CYP 3A诱导介导的DDI方面具有很大的优势。(c)2013 Wiley Periodicals，Inc.和American Pharmacologist Association J Pharm Sci 102：2819-2836，2013
Cytochrome P450 (CYP) 3A induction-mediated drug-drug interaction (DDI) is one of the major concerns in drug development and clinical practice. The aim of the present study was to develop a novel mechanistic physiologically based pharmacokinetic (PBPK)-enzyme turnover model involving both intestinal and hepatic CYP3A induction to quantitatively predict magnitude of CYP3A induction-mediated DDIs from in vitro data. The contribution of intestinal P-glycoprotein (P-gp) was also incorporated into the PBPK model. First, the pharmacokinetic profiles of three inducers and 14 CYP3A substrates were predicted successfully using the developed model, with the predicted area under the plasma concentration-time curve (AUC) [area under the plasma concentration-time curve] and the peak concentration (C-max) [the peak concentration] in accordance with reported values. The model was further applied to predict DDIs between the three inducers and 14 CYP3A substrates. Results showed that predicted AUC and C-max ratios in the presence and absence of inducer were within twofold of observed values for 17 (74%) of the 23 DDI studies, and for 14 (82%) of the 17 DDI studies, respectively. All the results gave us a conclusion that the developed mechanistic PBPK-enzyme turnover model showed great advantages on quantitative prediction of CYP3A induction-mediated DDIs. (c) 2013 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 102:2819-2836, 2013