ABSTRACT
This chapter illustrates the use of R in the analysis of data collected in bioequivalence clinical trials. It describes two datasets from bioequivalence trials, the associated statistical analysis methods, and then step-by-step implementation of the methods in R. The primary endpoints in the statistical assessment of bioequivalence are area under the concentration-by-time curve (AUC), Maximum Concentration (CMAX) and T MAX, and are directly calculated from the blood/plasma concentration-by-time curve. In evaluating bioequivalence of two formulations, the commonly used statistical inference from usual hypothesis testing has long been criticized in pharmaceutical research to be inappropriate. It is well known that confidence intervals (CI) provide a more appropriate inferential framework for assessing bioequivalence. The chapter discusses the most commonly used CIs in assessing bioequivalence following the notations in Peace and Chen. The presence of differential carryover effect may impact the inference as to bioequivalence and attendant statistical methods. The chapter illustrates the implementation in R for these tests.
