Establishing Bioequivalence in Complete and Incomplete Data Designs Using AUCs

Abstract

Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration versus time curve (AUC). The classical complete data design where each animal is sampled for analysis at every time point is applicable for large animals only. In the case of small animals, where blood sampling is restricted, the batch design or the serial sampling design need to be considered. In batch designs, samples are taken more than once from each animal, but not at all time points. In serial sampling designs, only one sample is taken from each animal. In this article we derive the asymptotic distribution for the ratio of two AUCs and construct different confidence intervals, which are frequently used to assess bioequivalence. The performance of these intervals is then evaluated between the different designs in a simulation study. Additionally, the sample sizes required for the different designs are compared.

Key Words:

• AUC
• Batch design
• Bioequivalence
• Complete data design
• Serial sampling design
• Sparse sampling

Notes

Note. n _k … sample size per time point in group k.

Note. n _k … sample size per time point in group k.

Note. n _k … sample size per time point in group k.

Note. n _k … sample size per time point in group k.

Note. n _k … sample size per time point in group k.

Note. n _k … sample size per time point in group k.

Note. Number in parenthesis is the empirical power/type I error.