选择最好的药理动力学模型,以先验模型为基础的精确剂量与模型组合
Bram C Agema1,2, Tolra Kocher3, Ayşenur B Öztürk3
1Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, The Netherlands.
Clinical pharmacokinetics
|September 27, 2024
概括
使用治疗药物监测 (TDM) 样本选择最佳的人口药理动力学 (popPK) 模型可以改善药物剂量. 这种方法确保更多的患者在治疗范围内获得最佳的万科米辛和伊马替尼布剂量.
科学领域:
- 药学指标 (Pharmacometrics) 是一个指标.
- 临床药理学 临床药理学
- 药物剂量优化 药物剂量优化
背景情况:
- 人口药理动力学 (popPK) 模型对于个性化药物至关重要,指导先验剂量个性化.
- 有效的模型选择对于确保准确和安全的药物剂量至关重要.
- 使用治疗药物监测 (TDM) 样本进行外部验证是评估模型性能的关键.
研究的目的:
- 开发和评估模型选择和组合技术,以确定最佳的popPK模型.
- 通过使用外部TDM数据来评估这些方法,以改善先验剂量个性化.
- 为了比较不同模型选择策略与标准剂量的性能.
主要方法:
- 利用了134名接受万科米辛治疗的住院患者和92名接受伊马替尼布治疗的门诊患者的PK数据.
- 我们比较了四种模型选择方法:最佳模型验证,未知组合,加权组合和决策树组合.
- 对标准剂量和治疗窗口的评估目标实现.
主要成果:
- 与标准剂量相比,所有评估的popPK模型选择方法都改善了治疗度的达到.
- 决策树组合方法显示了最显著的改善,特别是在万科米辛验证 (77.2%) 和伊马替尼布队列 (59.5%).
- 权重组合也显示了两种药物队伍的实质性改善.
结论:
- 一小组TDM样本足以用于外部评估,以确定个人患者的最佳popPK模型.
- 开发的方法成功地确定了表现良好的模型,并排除了不充分的模型.
- 基于选定的模型的剂量建议增加了范科米辛和伊马替尼的治疗范围内的患者比例,这证明了潜在的验证.
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