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基于生理的药代动力学模型框架用于定量预测草药-药物相互作用。

Physiologically based pharmacokinetic modeling framework for quantitative prediction of an herb-drug interaction.

机构信息

Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

College of Pharmacy, Washington State University, Spokane, Washington, USA.

出版信息

CPT Pharmacometrics Syst Pharmacol. 2014 Mar 26;3(3):e107. doi: 10.1038/psp.2013.69.

Abstract

Herb-drug interaction predictions remain challenging. Physiologically based pharmacokinetic (PBPK) modeling was used to improve prediction accuracy of potential herb-drug interactions using the semipurified milk thistle preparation, silibinin, as an exemplar herbal product. Interactions between silibinin constituents and the probe substrates warfarin (CYP2C9) and midazolam (CYP3A) were simulated. A low silibinin dose (160 mg/day × 14 days) was predicted to increase midazolam area under the curve (AUC) by 1%, which was corroborated with external data; a higher dose (1,650 mg/day × 7 days) was predicted to increase midazolam and (S)-warfarin AUC by 5% and 4%, respectively. A proof-of-concept clinical study confirmed minimal interaction between high-dose silibinin and both midazolam and (S)-warfarin (9 and 13% increase in AUC, respectively). Unexpectedly, (R)-warfarin AUC decreased (by 15%), but this is unlikely to be clinically important. Application of this PBPK modeling framework to other herb-drug interactions could facilitate development of guidelines for quantitative prediction of clinically relevant interactions.CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e107; doi:10.1038/psp.2013.69; advance online publication 26 March 2014.

摘要

草药-药物相互作用的预测仍然具有挑战性。本研究采用基于生理的药代动力学(PBPK)模型,以半纯化奶蓟制剂水飞蓟宾作为代表性草药产品,提高潜在草药-药物相互作用的预测准确性。模拟了水飞蓟宾成分与探针底物华法林(CYP2C9)和咪达唑仑(CYP3A)之间的相互作用。预测低剂量水飞蓟宾(160mg/天×14 天)可使咪达唑仑 AUC 增加 1%,这与外部数据相符;高剂量水飞蓟宾(1650mg/天×7 天)可使咪达唑仑和(S)-华法林 AUC 分别增加 5%和 4%。一项概念验证临床研究证实了高剂量水飞蓟宾与咪达唑仑和(S)-华法林之间的相互作用最小(AUC 分别增加 9%和 13%)。出乎意料的是,(R)-华法林 AUC 减少(减少 15%),但这可能在临床上并不重要。将这种 PBPK 建模框架应用于其他草药-药物相互作用,可能有助于制定用于定量预测临床相关相互作用的指南。CPT 药代动力学系统药理学(2014)3,e107;doi:10.1038/psp.2013.69;2014 年 3 月 26 日在线提前发布。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e729/4042458/3b21ece921fe/psp201369f1.jpg

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