Bioequivalence (BE) studies are widely carried out in the pharmaceutical industry. The assessment of BE adopted by the Food and Drugs Administration (FDA) is a moment-based criterion evaluating log-transformed pharmacokinetic responses such as Area Under the Curve (AUC), Maximum Concentration ( ), which are usually estimated from drug plasma time profiles. Average BE (ABE) is based solely on the comparison of population averages but not on the variances, while Population BE (PBE) and individual BE (IBE) approaches include comparisons of both averages and variances. The objective of this thesis is to review the standard approaches to statistical analyses of pharmacokinetic data. It also covers estimation of AUC, and other pharmacokinetic (PK) parameters as introduced in a Non-Compartmental Analysis (NCA) approach and Compartmental Models Analysis approach. Widely cited data sets from the published literature are used to illustrate these two approaches. They show the benefits of parameter estimation and subsequent statistical inference with an appropriate compartmental model, even though the model fitting could be a little complicated.
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