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首页> 外文期刊>Drug Metabolism and Disposition: The Biological Fate of Chemicals >Physiologically Based Pharmacokinetic Model of the CYP2D6 Probe Atomoxetine: Extrapolation to Special Populations and Drug-Drug Interactions
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Physiologically Based Pharmacokinetic Model of the CYP2D6 Probe Atomoxetine: Extrapolation to Special Populations and Drug-Drug Interactions

机译：CYP2D6探针的生理基础药代动力学模型氧毒素：外推到特殊群体和药物 - 药物相互作用

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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.
机译：药物分配和药物 - 药物相互作用（DDIS）的生理基础药代动力学（PBPK）建模已成为药物发育的关键组成部分。 PBPK建模也被认为是预测特殊人群药物处理的一种方法。但是，是否可以在健康人群中开发和验证的模型可以推断给特殊人群并不是很好的成熟。本研究的目标是确定使用健康群体验证的药物特异性PBPK模型是否可用于预测特定群体和器官障碍患者的药物处理。使用来自CYP2D6基因分类个体的训练组的药代动力学（PK）数据进行了全部PBPK模型。使用药物特异性验收标准和14个健康主题PK研究进行验证该模型。通过模拟种族，DDIS，儿科，肾和肝损伤对杂草素PK的影响，人口PBPK模型被挑战。奥昔乙胺处理均成功预测了100％的健康主题研究，88％的亚洲研究，79％的DDI研究和100％的儿科研究。然而，血浆浓度与时间曲线（AUC）下的氧氧杂志面积呈3-至4倍的末期肾病和肝损伤。结果表明，经过验证的PBPK模型可以推断为不同的种族，DDIS和儿科，但不是肾病和肝脏损伤患者，可能由于对这些条件的生理变化不完全了解。这些结果表明，系统建模努力可用于进一步改进人口模型，以提高该领域的预测价值。

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