ROBUST METHODS IN BIOEQUIVALENCE ASSAY - PRELIMINARY-RESULTS

The aim of this study is to compare four statistical methods for outli er identification in Bioequivalence tests. The methods are based in fo ur confidence intervals, 'parametric','non- parametric','robust with t he asymptotic distribution of the M-estimator' and 'robust with the bo otstrap distribution'. The drug we used was Diltiazen, in a two sequen ce randomized crossover study design. The pharmacokinetic parameters m easured were the area under the plasma concentration curve (AUC), and the peak drug concentration (CMAX). Time to peak drug concentration (T MAX), was not used here in order to separate the efficiency of the met hods from the efficiency of the measurements. The methods were applied to simulated and experimental data. We made two simulations, one with normal data and another one with outliers data. When simulating norma l data all methods showed similar profiles and high power. On the cont rary, when simulating experiments with outliers data, the parametric m ethod showed low power, whereas robust methods showed just a slight de crement in power. When we analized experimental data of AUG, if we use d the parametric method (recommended by U.S.P), we were not able to co nclude Bioequivalence, but with the other methods, this was possi- ble . This disagreement between parametric and robust procedures was a sig n of outliers data. We conclude that the robust methods in bioequivale nce assays help us in the identification of outliers as observations w ith weight equal zero.