使用时间平均曝光指标在曝光-响应分析中对二进制终点的影响
Yu-Wei Lin1,2,3,4,5, Anna Largajolli6,7, A Yin Edwards6,7
1Certara Inc., Melbourne, VIC, Australia.
Frontiers in pharmacology
|January 31, 2025
概括
在被审查的受试者中,仔细推导时间平均度到事件 (CavTE) 对于准确的暴露-反应 (ER) 分析至关重要. 错误的CavTE衍生可能会影响药物开发决策和风险-益处评估.
科学领域:
- 药量计学和定量药理学
- 药物开发和监管科学 药物开发和监管科学
背景情况:
- 暴露-反应 (ER) 分析是基于模型的药物开发中不可或缺的组成部分,用于剂量选择和风险-益处评估.
- 时间平均度到事件 (CavTE) 是一个暴露指标,它解释了剂量修改,但可以在后勤回归模型中引入偏差.
研究的目的:
- 评估不同的方法来推导CavTE在没有治疗结束 (EoT) 事件的受试者.
- 评估CavTE导出对ER关系和药物开发决策中的潜在偏差的影响.
主要方法:
- 模拟暴露和事件数据,使用基于真实数据的修改模型.
- 多样化的虚拟人口大小 (n=50-200) 和药物效应大小 (0.5-1).
- 对于被审查的受试者,在EoT后的多个时间点 (EoT,EoT+7,+14,+21,+28天) 获得CavTE.
主要成果:
- 对于CavTE导出所选择的时间点显著影响了后勤ER关系.
- 偏差的ER趋势可能导致错误的事件预测,剂量选择和Go/No-Go决策.
- 在被审查的受试者中仔细推导CavTE对于避免错误的积极或负面结论至关重要.
结论:
- 当与药理动力学,药理动力学和生物可信度相结合时,CavTE是一个有价值的暴露指标.
- 考虑生物可信性,事件时间和剂量修改水平对于度量选择至关重要.
- 对于ER分析的时间不变逻辑回归可能会忽视暴露和反应的重要时间方面.
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