Fundamentals in Population Pharmacokinetics: Mathematics in Linear Mixed Effects Model and Nonlinear Mixed Effects Model

Funatogawa Ikuko, Funatogawa Takashi

doi:10.5691/jjb.36.s33

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母集団薬物動態解析の基礎：線形混合効果モデル・非線形混合効果モデルの数理
ボシュウダンヤクブツドウタイカイセキノキソ : センケイコンゴウコウカモデル・ヒセンケイコンゴウコウカモデルノスウリ

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Abstract

Longitudinal data are data collected repeatedly from each subject for a particular response variable over a certain time period. Specifically, in longitudinal data analysis, the researchers are interested in changes in the response levels over time and the differences in these changes among factor levels or covariates. Because of within-subject correlations, analysis methods considering the correlations or variance-covariance structures have been developed. One of the approaches is the use of mixed effects models that take into account between-subject heterogeneity by random effects. In population pharmacokinetics, the response variable corresponds to drug concentration and is analysed typically using nonlinear mixed effects models. In this article, longitudinal data analysis with a continuous response variable is introduced focusing on population pharmacokinetics. Longitudinal data analysis, linear mixed effects models, nonlinear mixed effects models, and population pharmacokinetics are discussed from a biostatistical point of view. This article is expected to be of interest to biostatisticians, pharmacologists, pharmacokineticists, and those in related fields.

Journal

Japanese Journal of Biometrics

Japanese Journal of Biometrics 36 (Special_Issue), S33-S48, 2015

The Biometric Society of Japan

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