一个多隔间人群PK模型,用于预测Tenofovir和Emtricitabine粘膜组织度,用于HIV预防
Erick Leung1, Mackenzie L Cottrell1, Craig Sykes1
1Division of Pharmacotherapy and Experimental Therapeutics, University of North Carolina UNC Eshelman School of Pharmacy, Chapel Hill, North Carolina, USA.
CPT: pharmacometrics & systems pharmacology
|October 10, 2023
概括
数学建模可以从坚持问题预测艾滋病毒暴露前预防 (PrEP) 结果. 这种药理动力学模型优化了剂量策略,以减少临床试验失败.
科学领域:
- 药理动力学和药理动力学
- 在药物开发中的数学建模.
- 艾滋病毒预防研究 预防研究
背景情况:
- 临床试验失败在艾滋病毒暴露前预防 (PrEP) 开发中很常见.
- 不完全遵守和降低剂量频率是关键风险.
- 预测建模可以减轻这些风险.
研究的目的:
- 为抗逆转录病毒药物开发一个半生理学群体药动力学模型.
- 为了评估粘膜组织中的药物度.
- 为了优化HIV PrEP的剂量策略.
主要方法:
- 利用了一项I期剂量范围研究的药理动力学数据.
- 开发了一个16个隔间的半生理学群体药理动力学模型.
- 执行了同时对诺福维尔二氧化 fumarate和emtricitabine数据的共建模型.
主要成果:
- 一个线性运动模型准确地描述了血和组织中的药物度.
- 该模型结合了23名健康女性志愿者的数据.
- 模型成功模拟了不同剂量的药物处置.
结论:
- 开发的药理动力学模型可以预测改变剂量策略的结果.
- 这种方法可以优化HIV PrEP治疗方案,减少试验失败.
- 数学建模对于有效的药物开发至关重要.
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