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基于生理学的 CYP2D6 探针阿托西汀药代动力学模型:特殊人群和药物相互作用的外推。

Physiologically Based Pharmacokinetic Model of the CYP2D6 Probe Atomoxetine: Extrapolation to Special Populations and Drug-Drug Interactions.

机构信息

Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington.

Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington

出版信息

Drug Metab Dispos. 2017 Nov;45(11):1156-1165. doi: 10.1124/dmd.117.076455. Epub 2017 Aug 31.

Abstract

Physiologically based pharmacokinetic (PBPK) modeling of drug disposition and drug-drug interactions (DDIs) has become a key component of drug development. PBPK modeling has also been considered as an approach to predict drug disposition in special populations. However, whether models developed and validated in healthy populations can be extrapolated to special populations is not well established. The goal of this study was to determine whether a drug-specific PBPK model validated using healthy populations could be used to predict drug disposition in specific populations and in organ impairment patients. A full PBPK model of atomoxetine was developed using a training set of pharmacokinetic (PK) data from CYP2D6 genotyped individuals. The model was validated using drug-specific acceptance criteria and a test set of 14 healthy subject PK studies. Population PBPK models were then challenged by simulating the effects of ethnicity, DDIs, pediatrics, and renal and hepatic impairment on atomoxetine PK. Atomoxetine disposition was successfully predicted in 100% of healthy subject studies, 88% of studies in Asians, 79% of DDI studies, and 100% of pediatric studies. However, the atomoxetine area under the plasma concentration versus time curve (AUC) was overpredicted by 3- to 4-fold in end stage renal disease and hepatic impairment. The results show that validated PBPK models can be extrapolated to different ethnicities, DDIs, and pediatrics but not to renal and hepatic impairment patients, likely due to incomplete understanding of the physiologic changes in these conditions. These results show that systematic modeling efforts can be used to further refine population models to improve the predictive value in this area.

摘要

基于生理学的药物处置和药物相互作用(DDI)的药代动力学(PBPK)建模已成为药物开发的关键组成部分。PBPK 建模也被认为是预测特殊人群中药物处置的一种方法。然而,在健康人群中开发和验证的模型是否可以外推到特殊人群尚不清楚。本研究的目的是确定使用健康人群验证的特定药物 PBPK 模型是否可用于预测特殊人群和器官损伤患者的药物处置。使用 CYP2D6 基因分型个体的药代动力学(PK)数据的训练集开发了阿托西汀的全 PBPK 模型。使用药物特异性接受标准和 14 项健康受试者 PK 研究的测试集对模型进行了验证。然后,通过模拟种族、DDI、儿科和肾肝损伤对阿托西汀 PK 的影响来挑战人群 PBPK 模型。在 100%的健康受试者研究、88%的亚洲人研究、79%的 DDI 研究和 100%的儿科研究中,阿托西汀的处置情况均得到了成功预测。然而,在终末期肾病和肝损伤患者中,阿托西汀的血药浓度-时间曲线下面积(AUC)被高估了 3-4 倍。结果表明,经过验证的 PBPK 模型可以外推到不同种族、DDI 和儿科人群,但不能外推到肾肝损伤患者,这可能是由于对这些情况下的生理变化了解不完整。这些结果表明,系统的建模工作可以用于进一步完善人群模型,提高该领域的预测价值。

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