使用Stan与Torsten实施贝叶斯方法:对索马特龙的种群药动力学分析
Yuchen Wang1, Xinyi Pei2,3, Tao Niu3
1Pfizer Inc., South San Francisco, California, USA.
使用Stan和Torsten的完全贝叶斯人种群药动力学 (PK) 建模对索马特龙有效. 不同的先前集合表现良好,证明了对新个体的准确预测.
科学领域:
- 制药指标 (Pharmacometrics) 是一个指标.
- 计算统计学 计算统计学
- 药物开发 药物开发
背景情况:
- 人口药理动力学 (PK) 建模对于了解不同患者群体的药物行为至关重要.
- 完全贝叶斯的方法在人口PK建模中未得到充分利用,尽管它们具有潜在的好处.
研究的目的:
- 评估Stan与R和Torsten对群体PK模拟索马特龙的实用性.
- 评估不同先验集和参数化策略对模型性能和计算效率的影响.
主要方法:
- 使用Stan对马尔科夫链蒙特卡洛 (MCMC) 采样进行贝叶斯推理.
- 人口PK对长效生长激素索马特龙的建模.
- 评估三个先前的集合 (弱,中等和非常有信息) 和中心与非中心的参数化.
主要成果:
- 所有评估的先前套件都表现出良好的性能,使用混合良好的MCMC链.
- 后来的预测准确地覆盖了现有和新个体的观察数据.
- 非中心参数化改进了估计时间,尽管计算强度仍然是一个因素.
结论:
- 用Stan和Torsten的贝叶斯方法对于人口PK分析是可行的,特别是如果有足够的计算资源.
- 这些方法对于特殊群体,小型数据集和复杂的模型结构特别有用.
- 这项研究强调了贝叶斯推理在现代药理学中的实际应用.
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