使用非线性混合效应方法的双变混合隐藏马尔科夫模型对抗药物抗体动态的表征
Ari Brekkan1, Rocío Lledo-Garcia2, Brigitte Lacroix3
1Department of Pharmacy, Uppsala University, Box 580, Uppsala, SE-75123, Sweden.
Journal of pharmacokinetics and pharmacodynamics
|November 9, 2023
概括
生物疗法可以触发抗药抗体 (ADA). 一个新的混合隐藏马尔科夫模型 (MHMM) 识别了ADA生产,提供了一种更独立于测试的方法来了解药物处置并最大限度地降低影响.
科学领域:
- 药理动力学和药理动力学
- 免疫学 免疫学 免疫学
- 生物统计学 生物统计学
背景情况:
- 生物疗法可以引起免疫反应,导致抗药抗体 (ADA).
- 由于ADA生物试验灵敏度的局限性,人口药理动力学 (PK) 模型经常难以完全描述ADA-药物处置关系.
- 了解ADA形成对于优化治疗疗效和安全至关重要.
研究的目的:
- 开发和探索一种新的方法来阐明底层的ADA生产动态.
- 用混合隐藏马尔科夫模型 (MHMM) 描述ADA形成对药物处置的影响.
- 与传统的PK分析相比,评估MHMM作为一种测试独立方法的实用性.
主要方法:
- 开发一个双变的混合隐藏马尔科夫模型 (MHMM).
- 使用的血药物度和ADA测量来自六项临床研究 (n=845) 涉及certollizumab pegol (CZP).
- 采用双变的高斯函数来关联观察到的数据并推断ADA生产的隐藏状态.
主要成果:
- MHMM成功地推断出与影响PK的ADA生产相关的隐藏状态.
- 维特比算法可以确定个体患者的ADA生产的开始时间.
- 虽然观察到的模型参数估计得很好,但隐藏状态参数的精度较低;个人间变异性估计没有得到支持.
结论:
- 开发的MHMM提供了一个更独立于测试的方法来理解ADA生产动态.
- 这种模型可以作为确定影响ADA形成的共变量的基础.
- 该方法有可能指导策略,以尽量减少ADA对药物PK和疗效的影响.
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