用小型现实数据集与大型虚拟数据集进行人口药动力学模型评估:样本大小是否会影响决策?
Mehdi El Hassani1,2, Daniel J G Thirion3,4, Amélie Marsot3,5
1Faculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada. mehdi.el.hassani@umontreal.ca.
European journal of drug metabolism and pharmacokinetics
|July 29, 2025
概括
小规模的临床数据集可以有效地评估人群药动力学 (PK) 模型,证实先前的模拟结果. 这种使用真实数据的验证支持药物研究中的高效模型开发.
科学领域:
- 药理动力学和药理动力学
- 临床药理学 临床药理学
- 药物开发 药物开发
背景情况:
- 之前的模拟研究表明,样本大小对外部人群药理动力学 (PK) 模型评估的影响很小.
- 这些发现适用于现实世界的临床数据需要验证.
研究的目的:
- 用实际的临床数据验证基于模拟的发现.
- 用小的临床数据集评估人口PK模型的外部评估.
主要方法:
- 从接受 piperacillin/tazobactam 的老年患者收集的临床数据.
- 模拟了一个由1000名患者组成的虚拟人口.
- 用临床和模拟数据集对人口PK模型进行外部评估.
- 通过偏差,不准确性,合适度图和预测纠正的视觉预测检查来评估模型性能.
主要成果:
- 对人口PK模型的外部评估是在一个小的临床数据集 (13名患者) 和一个模拟数据集上进行的.
- 在临床和模拟数据集之间的预测错误分布中没有发现显著差异.
- 合适度图和视觉预测检查表明,这两个数据集都存在类似的模型错误规范.
结论:
- 小规模的临床数据集足以对人口PK模型进行外部评估.
- 这些发现支持在PK模型评估中使用有限的临床数据.
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