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A use of Monte Carlo integration for population pharmacokinetics with multivariate population distribution.

机译:将蒙特卡洛积分用于具有多元人口分布的人口药代动力学。

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This paper describes a use of Monte Carlo integration for population pharmacokinetics with multivariate population distribution. In the proposed approach, a multivariate lognormal distribution is assumed for a population distribution of pharmacokinetic (PK) parameters. The maximum likelihood method is employed to estimate the population means, variances, and correlation coefficients of the multivariate lognormal distribution. Instead of a first-order Taylor series approximation to a nonlinear PK model, the proposed approach employs a Monte Carlo integration for the multiple integral in maximizing the log likelihood function. Observations below the lower limit of detection, which are usually included in Phase 1 PK data, are also incorporated into the analysis. Applications are given to a simulated data set and an actual Phase 1 trial to show how the proposed approach works in practice.
机译:本文介绍了蒙特卡洛积分在具有多元人口分布的人口药代动力学中的用途。在提出的方法中,假设药代动力学(PK)参数的总体分布为多元对数正态分布。采用最大似然法估计多元对数正态分布的总体均值,方差和相关系数。代替非线性PK模型的一阶泰勒级数逼近,所提出的方法在最大对数似然函数中对多积分采用了蒙特卡罗积分。低于检测下限的观察结果(通常包含在第1阶段PK数据中)也被纳入分析中。给出了一个模拟数据集和一个实际的1期试验的应用程序,以显示所提出的方法在实践中如何工作。

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