Bayesian population pharmacokinetic and pharmacodynamic analyses using mixture models.
Bayesian population pharmacokinetic and pharmacodynamic analyses using mixture models.
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使用混合模型进行贝叶斯群体药代动力学和药效学分析。
DOI：
10.1023/a:1025784113869
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发表时间：
1997
期刊：
影响因子：
--
通讯作者：
Müller,P
中科院分区：
文献类型：
--
作者：
Rosner,GL;Müller,P
对药物动力学或药效学或药物的总体研究有助于我们了解药物处置和效果的可变性，这些信息可用于以安全有效的剂量治疗未来的患者。我们提出了一种新的基于具有随机权重和均值的正态分布加权混合的总体建模方法。该方法允许在不预先指定这些概率分布的参数形式或形状的情况下估计潜在的连续总体分布。此外，这种方法可以对患者协变量进行药代动力学或动力学参数的非参数回归，同时估计潜在的分布。两个实例说明了该方法及其灵活性。
Population studies of the pharmacokinetics or pharmacodynamics or drugs help us learn about the variability in drug disposition and effects, information that can be used to treat future patients at safe and effective doses. We present a new approach to population modeling based on a weighted mixture of normal distributions having random weights and means. This method allows estimation of underlying continuous population distributions without prespecifying the parametric form or shape of these probability distributions. Additionally, this method can carry out nonparametric regression of pharmacokinetic or dynamic parameters on patient covariates while estimating the underlying distributions. Two examples illustrate the method and its flexibility.