Statistical comparison of dissolution curves.
The purpose of this investigation was to develop statistical procedures to determine if two sets of dissolution curves could have come from the same population of curves. The f(2)statistic developed by the Food and Drug Administration, FDA, has been shown to have many limitations and is too liberal in concluding similarity between dissolution profiles. The procedure currently used by the FDA involves computing the mean amount dissolved at each time and then comparing the two mean curves. This approach ignores all of the variability within sets of profiles, which, from a statistical viewpoint, is a serious limitation. This investigation presents three different statistics for comparison of dissolution curves with associated decision rules and power functions. These three statistics are extensions of existing procedures: (1) an extension of the Mann--Whitney test which compares the variability within each set of profiles and between the two sets; (2) an extension of the Kolmogorov--Smirnov D statistic which compares three empirical cumulative distribution functions; and (3) an adaptation of the well known chi-squared test. A computer program, which includes the algorithm for each of the three statistics and varying sample sizes, is also available.