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使用基于生理的药代动力学模型预测细胞色素P450介导的药物相互作用:沙丁胺醇与氟伏沙明的案例研究

Prediction of CYP-Mediated Drug Interaction Using Physiologically Based Pharmacokinetic Modeling: A Case Study of Salbutamol and Fluvoxamine.

作者信息

Marques Lara, Vale Nuno

机构信息

OncoPharma Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal.

Faculty of Medicine, University of Coimbra, Azinhaga de Santa Comba, Celas, 3000-548 Coimbra, Portugal.

出版信息

Pharmaceutics. 2023 May 24;15(6):1586. doi: 10.3390/pharmaceutics15061586.

Abstract

Drug-drug interactions (DDIs) represent a significant concern in healthcare, particularly for patients undergoing polytherapy. DDIs can lead to a range of outcomes, from decreased therapeutic effectiveness to adverse effects. Salbutamol, a bronchodilator recommended for the treatment of respiratory diseases, is metabolized by cytochrome P450 (CYP) enzymes, which can be inhibited or induced by co-administered drugs. Studying DDIs involving salbutamol is crucial for optimizing drug therapy and preventing adverse outcomes. Here, we aimed to investigate CYP-mediated DDIs between salbutamol and fluvoxamine through in silico approaches. The physiologically based pharmacokinetic (PBPK) model of salbutamol was developed and validated using available clinical PK data, whereas the PBPK model of fluvoxamine was previously verified by GastroPlus. Salbutamol-fluvoxamine interaction was simulated according to different regimens and patient's characteristics (age and physiological status). The results demonstrated that co-administering salbutamol with fluvoxamine enhanced salbutamol exposure in certain situations, especially when fluvoxamine dosage increased. To sum up, this study demonstrated the utility of PBPK modeling in predicting CYP-mediated DDIs, making it a pioneer in PK DDI research. Furthermore, this study provided insights into the relevance of regular monitoring of patients taking multiple medications, regardless of their characteristics, to prevent adverse outcomes and for the optimization of the therapeutic regimen, in cases where the therapeutic benefit is no longer experienced.

摘要

药物相互作用(DDIs)是医疗保健领域的一个重大问题,尤其是对于接受联合治疗的患者。DDIs可能导致一系列后果,从治疗效果降低到不良反应。沙丁胺醇是一种推荐用于治疗呼吸系统疾病的支气管扩张剂,由细胞色素P450(CYP)酶代谢,而同时服用的药物可能会抑制或诱导这些酶。研究涉及沙丁胺醇的DDIs对于优化药物治疗和预防不良后果至关重要。在此,我们旨在通过计算机模拟方法研究沙丁胺醇与氟伏沙明之间由CYP介导的药物相互作用。利用现有的临床药代动力学(PK)数据建立并验证了沙丁胺醇的基于生理的药代动力学(PBPK)模型,而氟伏沙明的PBPK模型先前已由GastroPlus验证。根据不同的给药方案和患者特征(年龄和生理状态)模拟了沙丁胺醇 - 氟伏沙明的相互作用。结果表明,在某些情况下,尤其是当氟伏沙明剂量增加时,同时服用沙丁胺醇和氟伏沙明会增加沙丁胺醇的暴露量。总之,本研究证明了PBPK建模在预测由CYP介导的DDIs方面的实用性,使其成为PK DDI研究的先驱。此外,本研究为在不再体验到治疗益处的情况下,对服用多种药物的患者进行定期监测以预防不良后果和优化治疗方案的相关性提供了见解,无论患者特征如何。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3313/10301358/e9200f183c0d/pharmaceutics-15-01586-g001.jpg

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