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 p opulation of curves. The f(2) statistic developed by the Food and Drug Admi nistration, FDA, has been shown to have many limitations and is too liberal in concluding similarity between dissolution profiles. The procedure curre ntly used by the FDA involves computing the mean amount dissolved at each t ime and then comparing the two mean curves. This approach ignores all of th e variability within sets of profiles, which, from a statistical viewpoint, is a serious limitation. This investigation presents three different stati stics for comparison of dissolution curves with associated decision rules a nd power functions. These three statistics are extensions of existing proce dures: (1) an extension of the Mann-Whitney test which compares the variabi lity within each set of profiles and between the two sets; (2) an extension of the Kolmogorov-Smirnov D statistic which compares three empirical cumul ative distribution functions; and (3) an adaptation of the well known chi-s quared test. A computer program, which includes: the algorithm for each of the three statistics and varying sample sizes, is also available. (C) 2001 Academic Press.