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采用基于生理的药代动力学建模方法研究一系列黄素单加氧酶底物的血浆浓度-时间曲线预测及其个体间变异性。

An Investigation into the Prediction of the Plasma Concentration-Time Profile and Its Interindividual Variability for a Range of Flavin-Containing Monooxygenase Substrates Using a Physiologically Based Pharmacokinetic Modeling Approach.

机构信息

Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.)

Departments of Modelling and Simulation, Oncology Drug Metabolism and Pharmacokinetics (V.P.R.), Departments of Drug Metabolism and Pharmacokinetics and Oncology (B.C.J., N.C., J.W.), and Department of Drug Safety and Metabolism (A.S.), IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom; and Pharmaron, Beijing, China (D.L.).

出版信息

Drug Metab Dispos. 2018 Sep;46(9):1259-1267. doi: 10.1124/dmd.118.080648. Epub 2018 Jun 12.

Abstract

Our recent paper demonstrated the ability to predict in vivo clearance of flavin-containing monooxygenase (FMO) drug substrates using in vitro human hepatocyte and human liver microsomal intrinsic clearance with standard scaling approaches. In this paper, we apply a physiologically based pharmacokinetic (PBPK) modeling and simulation approach (M&S) to predict the clearance, area under the curve (AUC), and values together with the plasma profile of a range of drugs from the original study. The human physiologic parameters for FMO, such as enzyme abundance in liver, kidney, and gut, were derived from in vitro data and clinical pharmacogenetics studies. The drugs investigated include itopride, benzydamine, tozasertib, tamoxifen, moclobemide, imipramine, clozapine, ranitidine, and olanzapine. The fraction metabolized by FMO for these drugs ranged from 21% to 96%. The developed PBPK models were verified with data from multiple clinical studies. An attempt was made to estimate the scaling factor for recombinant FMO (rFMO) using a parameter estimation approach and automated sensitivity analysis within the PBPK platform. Simulated oral clearance using in vitro hepatocyte data and associated extrahepatic FMO data predicts the observed in vivo plasma concentration profile reasonably well and predicts the AUC for all of the FMO substrates within 2-fold of the observed clinical data; seven of the nine compounds fell within 2-fold when human liver microsomal data were used. rFMO overpredicted the AUC by approximately 2.5-fold for three of the nine compounds. Applying a calculated intersystem extrapolation scalar or tissue-specific scalar for the rFMO data resulted in better prediction of clinical data. The PBPK M&S results from this study demonstrate that human hepatocytes and human liver microsomes can be used along with our standard scaling approaches to predict human in vivo pharmacokinetic parameters for FMO substrates.

摘要

我们最近的一篇论文展示了使用体外人肝细胞和人肝微粒体内在清除率结合标准缩放方法预测黄素单加氧酶 (FMO) 药物底物体内清除率的能力。在本文中,我们应用基于生理的药代动力学 (PBPK) 建模和模拟方法 (M&S) 来预测一系列来自原始研究的药物的清除率、曲线下面积 (AUC) 和 值以及血浆谱。FMO 的人体生理参数,如肝脏、肾脏和肠道中的酶丰度,是从体外数据和临床药物遗传学研究中推导出来的。研究的药物包括伊托必利、苯佐卡因、托扎西替布、他莫昔芬、吗氯贝胺、丙咪嗪、氯氮平、雷尼替丁和奥氮平。这些药物中由 FMO 代谢的比例从 21%到 96%不等。所开发的 PBPK 模型已通过多项临床研究的数据进行了验证。尝试使用参数估计方法和 PBPK 平台内的自动敏感性分析来估算重组黄素单加氧酶 (rFMO) 的缩放因子。使用体外肝细胞数据和相关的肝外 FMO 数据模拟口服清除率,可以很好地预测体内观察到的血浆浓度谱,并预测所有 FMO 底物的 AUC 在观察到的临床数据的 2 倍以内;当使用人肝微粒体数据时,九种化合物中有七种在 2 倍以内。rFMO 对其中三种化合物的 AUC 预测过高约 2.5 倍。对于 rFMO 数据应用计算的系统间外推标度或组织特异性标度可导致对临床数据的更好预测。本研究的 PBPK M&S 结果表明,人肝细胞和人肝微粒体可与我们的标准缩放方法一起用于预测 FMO 底物的人体体内药代动力学参数。

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