“MANOVA OVER ANOVA”- A BETTER OBJECTIVE IN BIOEQUIVALENCE STUDY

Bioequivalence studies should be conducted for two products marketed by different licensees, containing same active ingredient(s), must be shown to be therapeutically equivalent to one another order to be considered interchangeable. The bioequivalence of two formulations of the same drug can be determined based on the absence of significant differences in primary pharmacokinetic properties of bioavailability, such as pharmacokinetic parameters like C_max, T_max, AUC_0-t, and AUC_0-∞. The pharmacokinetic parameters derived from the plasma concentration-time curve are subjected to ANOVA. So we need to check ANOVAs for all pharmacokinetic parameters. Instead of that we can use multivariate analysis of variance (MANOVA) as it contains ANOVA results and further give more information regarding significance. From the results we can see that we get the same values like ANOVA and additionally we get 4 different tests for significance. Wilk’s Lambda shows that 6.9%, 14.1% and 20% of the variance of the dependent variable (C_max, T_max, AUC_0-t, and AUC_0-∞) is accounted for by the differences between drugs, phase and interaction respectively. Pillai’s Trace, Hotelling’s Trace and Roy’s largest root says that the data lead to statistical insignificance. So from these results we can suggest MANOVA instead of ANOVA in bioequivalence and control the increase risk of Type I error.