在骨和关节感染中使用利沃素: 开发一种基于模型的精确剂量应用
Léo Mimram1, Sophie Magreault1,2, Florian Lemaitre3
1Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME, Paris, France.
贝叶斯估计准确地预测了使用有限的样本对骨感染的勒沃素暴露 (AUC0-24). 一个免费的网络应用程序有助于精确的剂量,尽管Cmax估计仍然具有挑战性.
科学领域:
- 药理学
- 传染性疾病
- 计算生物学
背景情况:
- 对于骨和关节感染来说,利沃素非常重要.
- 治疗失败和耐药性需要精确的剂量策略.
- 需要使用药物动力学/药物动力学 (PK/PD) 监测工具.
研究的目的:
- 评估贝叶斯估计用于预测levofloxacin AUC0 - 24和Cmax.
- 开发一个基于模型的精确剂量 Web 应用程序.
- 在骨感染中比较人群PK模型.
主要方法:
- 对已公布的 PK 模型进行系统审查.
- 在各种采样场景下使用模拟数据进行贝叶斯估计.
- 使用现实数据队列进行验证.
- 开发和验证一个免费的基于网络的应用程序.
主要成果:
- 一个选定的勒沃素PK模型显示出良好的预测性能.
- 一个限量采样策略 (T0h-T3h) 准确估计了AUC0-24.
- 在所有测试场景中,Cmax的估计结果并不令人满意.
- 开发了一个验证的网络应用程序 (https://levoshiny.iame-research.center/).
结论:
- 用有限的样本进行贝叶斯估计,可有效预测levofloxacin治疗中的AUC0- 24.
- 开发的网络应用程序可为骨和关节感染提供精确的剂量.
- 可能需要进一步优化Cmax估计.
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