虚拟双胞胎方法使用基于生理学的药理动力学建模在接受apixaban或rivaroxaban治疗的住院患者中
Frédéric Gaspar1,2,3,4, Jean Terrier5,6,7, Celestin Jacot-Descombes2,7
1Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
British journal of clinical pharmacology
|March 4, 2025
概括
基于生理学上的药理动力学 (PBPK) 模型准确地预测了住院患者的阿皮克萨班和里瓦罗克萨班药物暴露. 这种方法有助于识别处于低剂量或过量剂量风险的个体,提高患者的安全.
科学领域:
- 药理学 药理学是指药理学的学科.
- 临床药房 临床药房
- 计算生物学 计算生物学
背景情况:
- 直接口服抗凝剂 (DOAC) 如阿皮克萨班和里瓦罗克萨班广泛使用,但暴露的个体间变化.
- 准确预测药物暴露对于优化治疗疗效和最大限度地减少住院患者的不良事件至关重要.
研究的目的:
- 评估基于生理学的药理动力学 (PBPK) 模型在预测住院患者个人阿皮克萨班和里瓦罗克萨班药理动力学方面的表现.
- 确定影响药物暴露和患者低剂量或过量服用风险的人口统计学,生理学和遗传因素.
主要方法:
- 研究了一组由100名用阿皮克萨班治疗的患者和100名用里瓦罗克萨班治疗的患者组成的队列 (OptimAT试验).
- 使用患者特定数据开发PBPK模型,包括人口统计,功能和P-糖蛋白 (Pgp) 和P450细胞染色体 (CYP450) 3A的表型.
- 模拟的药物动力学概况与测量药物度 (LC/MS-MS) 相比较.
主要成果:
- 结合人口统计和功能数据的PBPK模型预测了药物暴露在生物等价性标准 (apixaban的MFE:1.10,rivaroxaban:0.97).
- 包括Pgp和CYP3A表型略有增加了预测误差,但改善了患有出血风险的患者的识别 (MFE:0.90-1.15).
结论:
- 整合人口和功能数据的PBPK模型准确地预测了住院患者的阿皮克萨班和里瓦罗克萨班血暴露.
- 需要进一步的研究来澄清Pgp和CYP3A表型的附加值,但这种方法对识别高风险患者有希望,可能有助于床边应用.
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