Permutation Test (PT) and Tolerated Difference Test (TDT): two new, robust and powerful nonparametric tests for statistical comparison of dissolution profiles.

Abstract

The most popular way of comparing oral solid forms of drug formulations from different batches or manufacturers is through dissolution profile comparison. Usually, a similarity factor known as (f2) is employed; However, the level of confidence associated with this method is uncertain and its statistical power is low. In addition, f2 lacks the flexibility needed to perform in special scenarios. In this study two new statistical tests based on nonparametrical Permutation Test theory are described, the Permutation Test (PT), which is very restrictive to confer similarity, and the Tolerated Difference Test (TDT), which has flexible restrictedness to confer similarity, are described and compared to f2. The statistical power and robustness of the tests were analyzed by simulation using the Higuchi, Korsmayer, Peppas and Weibull dissolution models. Several batches of oral solid forms were simulated while varying the velocity of dissolution (from 30 min to 300 min to dissolve 85% of the total content) and the variability within each batch (CV 2-30%). For levels of variability below 10% the new tests exhibited better statistical power than f2 and equal or better robustness than f2. TDT can also be modified to distinguish different levels of similarity and can be employed to obtain customized comparisons for specific drugs. In conclusion, two new methods, more versatile and with a stronger statistical basis than f2, are described and proposed as viable alternatives to that method. Additionally, an optimized time sampling strategy and an experimental design-driven strategy for performing dissolution profile comparisons are described.