迈向以模型为基础的Voriconazole精确剂量:挑战已发表的Voriconazole非线性混合效应模型与现实世界的临床数据
Franziska Kluwe1,2, Robin Michelet1, Wilhelm Huisinga3
1Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Kelchstraße 31, 12169, Berlin, Germany.
使用非线性混合效应 (NLME) 模型的模型告知精度剂量 (MIPD) 显示了沃里可纳的适度预测性能. 纳入最近的患者数据显著提高了优化抗真菌治疗的模型准确性.
科学领域:
- 制药指标 (Pharmacometrics) 是一个指标.
- 临床药理学 临床药理学
- 抗真菌疗法是一种抗真菌治疗.
背景情况:
- 基于模型的精确剂量 (MIPD) 使用非线性混合效应 (NLME) 模型来优化药物治疗.
- 沃里康纳是一种抗真菌药物,具有狭窄的治疗范围和复杂的药理动力学 (PK),使其成为MIPD的候选药物.
研究的目的:
- 为了外部评估和比较不同NLME模型对沃里康纳MIPD的预测性能.
- 调查贝叶斯预测策略及其对沃里可纳剂量的临床影响.
主要方法:
- 实施了一种工作流程,用于对已公布的伏利康纳NLME模型进行外部评估.
- 利用一个全面的内部临床数据库进行模型评估,并应用贝叶斯预测策略.
主要成果:
- 一个综合的"混合"模型在评估的NLME模型中显示出最好的预测性能.
- 所有模型都表现出适度的预测性能,表明PK过程实施和变化捕获的潜在局限性.
- 包括最近的伏利康纳观察结果在内,大大提高了预测性能.
结论:
- MIPD有可能优化沃里康纳治疗.
- 强大的临床数据库和严格的外部模型评估对于复杂PK药物的成功MIPD至关重要.
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