A population pharmacokinetic model with time-dependent covariates measured with errors.
We propose a population pharmacokinetic (PK) model with time-dependent covariates measured with errors. This model is used to model S-oxybutynin's kinetics following an oral administration of Ditropan, and allows the distribution rate to depend on time-dependent covariates blood pressure and heart rate, which are measured with errors. We propose two two-step estimation methods: the second-order two-step method with numerical solutions of differential equations (2orderND), and the second-order two-step method with closed form approximate solutions of differential equations (2orderAD). The proposed methods are computationally easy and require fitting a linear mixed model at the first step and a nonlinear mixed model at the second step. We apply the proposed methods to the analysis of the Ditropan data, and evaluate their performance using a simulation study. Our results show that the 2orderND method performs well, while the 2orderAD method can yield PK parameter estimators that are subject to considerable biases.
Li
Lang
L
Division of Biostatistics, Indiana University, Indianapolis, Indiana 46254, USA. lali@iupui.edu
Lin
Xihong
X
Brown
Morton B
MB
Gupta
Suneel
S
Lee
Kyung-Hoon
KH
D001699:Biometry; D006801:Humans; D016013:Likelihood Functions; D008333:Mandelic Acids / Q000493:pharmacokinetics; D008954:Models, Biological; D015233:Models, Statistical; D010599:Pharmacokinetics; D013997:Time Factors
D008333:Mandelic Acids; C005419:oxybutynin