A use of Monte Carlo integration for population pharmacokinetics with multivariate population distribution.
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.
Department of Clinical Pharmacology, Kitasato Institute, Tokyo, Japan.
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A
Yafune
M
M
Takebe
H
H
Ogata
D000465:Algorithms; D015233:Models, Statistical; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D010599:Pharmacokinetics; D011153:Population