基于生理学的综合性药理动力学模型来评估芬伊托因的药物相互作用
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Leyanis Rodriguez-Vera1, Xuefen Yin1, Mohammed Almoslem1
1Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA.
Pharmaceutics
|October 28, 2023
概括
为了预测药物药物相互作用 (DDI),开发了一种基于生理学上的phenytoin的药理动力学 (PBPK) 模型. 这种PBPK方法有效地评估DDI,通过减少临床测试需求来支持药物开发.
科学领域:
- 药理动力学 药理动力学
- 药物开发 药物开发
- 计算机建模 计算建模
背景情况:
- 临床药物相互作用 (DDI) 研究对于药物安全性和疗效评估至关重要.
- 进行所有可能的临床DDI研究是耗时且昂贵的.
- 氨酸是一种强大的CYP3A4诱导剂和中度的CYP2C9基质,需要进行DDI评估.
研究的目的:
- 开发一个基于生理学的药理动力学 (PBPK) 平台模型用于phenytoin.
- 评估氨酸在DDI中作为受害者 (CYP2C9,CYP2C19) 和事者 (CYP3A4) 的作用.
- 评估PBPK建模在预测phenytoin DDI中的实用性.
主要方法:
- 通过使用GastroPlus®和来自15项研究的数据,开发了氨酸的PBPK模型.
- 该模型阐明了CYP2C9和CYP2C19对芬伊托因代谢的贡献.
- 对PBPK模型的准确性进行了验证,并与各种类型的氨酸剂量,配方和食物影响进行了对比.
主要成果:
- 该PBPK模型准确地预测了不同剂量和不同给药途径的类胺的药理动力学.
- 该模型成功解释了氨酸的代谢途径和剂量依赖的非线性.
- 模拟和观察到的DDI与可纳,奥梅普拉和伊特拉可纳显示出良好的一致性 (AUC比率0.891.25).
结论:
- 开发的PBPK模型可靠地描述了伊的药理动力学及其相互作用.
- PBPK建模为广泛的临床DDI测试提供了一种有效的替代方案.
- 这种方法支持在类药物和类似药物的药物开发中做出知情决策.
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