Abstract

Meaningful comparison of the dissolution profiles between the reference and test formulations of a drug is critical for assessing similarity between the two formulations, and for quality control purposes. Such a dissolution profile comparison is required by regulatory authorities, and the criteria used for this include the widely used difference factor f1 and a similarity factor f2 , recommended by the Food and Drug Administration . In spite of their extensive use in practice, the two factors have been heavily criticized on various grounds; the criticisms include ignoring sampling variability and ignoring the correlations across time points while using the criteria in practice. The goal of this article is to put f1 and f2 on a firm statistical footing by developing tolerance limits for the distributions of f1 and f2 , so that both the sampling variability and the correlations over time points are taken into account. Because f1 and f2 are defined in terms of sample mean dissolution profiles, they are not appropriate for comparing individual dissolution profiles. For the latter, we have considered similar criteria and have derived tolerance limits. Both parametric and nonparametric approaches are explored, and a bootstrap calibration is used to improve accuracy of the tolerance limits. Simulated coverage probabilities show that the method leads to accurate tolerance limits. Two examples are used to illustrate the methodology. Copyright © 2016 John Wiley & Sons, Ltd.

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