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Examination of Physiologically‐Based Pharmacokinetic Models of Rosuvastatin

机译:罗苏伐他汀的生理基于生理学药代理学模型

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摘要

Physiologically‐based pharmacokinetic (PBPK) modeling is increasingly used to predict drug disposition and drug–drug interactions (DDIs). However, accurately predicting the pharmacokinetics of transporter substrates and transporter‐mediated DDIs (tDDIs) is still challenging. Rosuvastatin is a commonly used substrate probe in DDI risk assessment for new molecular entities (NMEs) that are potential organic anion transporting polypeptide 1B or breast cancer resistance protein transporter inhibitors, and as such, several rosuvastatin PBPK models have been developed to try to predict the clinical DDI and support NME drug labeling. In this review, we examine five representative PBPK rosuvastatin models, discuss common challenges that the models have come across, and note remaining gaps. These shared learnings will help with the continuing efforts of rosuvastatin model validation, provide more information to understand transporter‐mediated drug disposition, and increase confidence in tDDI prediction.
机译:基于生理学的药代动力学(PBPK)建模越来越多地用于预测药物处理和药物 - 药物相互作用(DDIS)。然而,准确地预测转运物底物和转运蛋白介导的DDIS(TDDIS)的药代动力学仍然具有挑战性。 Rosuvastatin是一种常用的底物探针,用于新分子实体(NME)的DDI风险评估中,其是潜在的有机阴离子传输多肽1B或乳腺癌抗性蛋白转运蛋白转运蛋白,因此,已经开发出几种Rosuvastatin PBPK模型来试图预测临床DDI并支持NME药物标签。在这篇综述中,我们研究了五个代表性的PBPK Rosuvastatin模型,讨论了模型遇到的共同挑战,并注意剩下的差距。这些共同的学习将有助于罗斯伐他汀模型验证的持续努力,提供更多信息以了解转运介导的药物处理,并增加对TDDI预测的信心。

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