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在药物不依附的情况下,对两部分的药理动力学模型进行统计分析
Dingding Yan1, Xiaotian Wu2, Jun Li3,4
1School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Bulletin of mathematical biology
|June 9, 2023
概括
药物坚持不良显著影响药物的有效性. 这项研究在药理动力学模型中模拟了剂量遗漏,揭示了非坚持是影响药物度和治疗结果的关键因素.
科学领域:
- 药理动力学和药理动力学
- 数学生物学 数学生物学
- 药物坚持研究研究 药物坚持研究
背景情况:
- 药物坚持不良是有效药物治疗的主要障碍.
- 了解剂量遗漏影响对于优化治疗结果至关重要.
- 药理动力学模型对于预测体内的药物行为至关重要.
研究的目的:
- 为了研究剂量遗漏对血中药物度的影响,在双隔间的药理动力学模型中.
- 分析静脉注射玻尿酸和外血管第一阶段吸收路径的影响.
- 开发剂量摄入及其药理动力学后果的随机模型.
主要方法:
- 复制经典的两部分药理动力学模型,使用随机剂量摄入 (双项随机模型).
- 预期和低谷和极限度的变异的明确表达式的正式化.
- 作为马尔科夫链的低谷度的静态性和度的数学证明.
- 对药物度可变性和规律性的非坚持效应的数值模拟.
主要成果:
- 已确定的存在和独特性,用于临界度的稳定状态分布.
- 证明了极低度的严格静止性和厄尔戈迪性.
- 数字模拟显示,药物不坚持显著影响度变化.
- 灵敏度分析确定了不遵守作为极限度预期的关键参数.
结论:
- 开发的随机药理动力学模型量化了剂量遗漏的影响.
- 药物不依附严重影响血药物度和潜在的治疗疗效.
- 这种方法可以增强慢性疾病模型,以预测依附变异性下的治疗结果.
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