Author Information

Zhiming Wang
Vince A. Uthoff

Abstract

Two medication formulations are compared using noncompartmental pharmacokinetic (PK) variables. However, more than the ratio of mean effects is of interest. A difference in formulation coeficients of varication (CV), within- or between-subject, is sought. The experimental design chosen is a 2 sequence crossover design of the form ABBA and BAAB, where A and B are two medication formulations. A mixed linear model is defined that contains random effects for subjects and for subject by formulation interactions. The model has fixed effects for the average formulation effects and period effects. The 2 formulations are assumed to have different error terms. The average formulation effect ratios and within-subject CVs may be compared by usual methods. An approximate Z-statistic is computed to compare the between-subject CVs. This statistic assumes a correlation of the 2 between-subject CV estimates. In addition, a tractable variance ratio is defined to indicate the extent to which the average effects ratio is applicable to each subject.

Keywords

Bioavailability, bioequivalence, variance component, pharmacokinetics

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Apr 27th, 10:30 AM

BIOAVAILABILITY AND CV COMPONENT COMPARISON IN A CROSSOVER

Two medication formulations are compared using noncompartmental pharmacokinetic (PK) variables. However, more than the ratio of mean effects is of interest. A difference in formulation coeficients of varication (CV), within- or between-subject, is sought. The experimental design chosen is a 2 sequence crossover design of the form ABBA and BAAB, where A and B are two medication formulations. A mixed linear model is defined that contains random effects for subjects and for subject by formulation interactions. The model has fixed effects for the average formulation effects and period effects. The 2 formulations are assumed to have different error terms. The average formulation effect ratios and within-subject CVs may be compared by usual methods. An approximate Z-statistic is computed to compare the between-subject CVs. This statistic assumes a correlation of the 2 between-subject CV estimates. In addition, a tractable variance ratio is defined to indicate the extent to which the average effects ratio is applicable to each subject.