A two one-sided parametric tolerance interval test for control of delivered dose uniformity—part 3—investigation of robustness to deviations from normality

Steven Novick, David Christopher, Monisha Dey, Svetlana Lyapustina, Michael Golden, Stefan Leiner, Bruce Wyka, Hans-Joachim Delzeit, Chris Novak, Gregory Larner
AAPS PharmSciTech 2009, 10 (3): 829-40
The robustness of the parametric tolerance interval test, which was proposed by the Food and Drug Administration for control of delivered dose uniformity in orally inhaled and nasal drug products, is investigated in this article using different scenarios for deviations from a univariate normal distribution. The studied scenarios span a wide range of conditions, the purpose of which is to provide an understanding of how the test performs depending on the nature and degree of the deviation from normality. Operating characteristic curves were generated to compare the performance of the test for different types of distributions (normal and non-normal) having the same proportion of doses in the tails (on one or both sides) outside the target interval. The results show that, in most cases, non-normality does not increase the probability of accepting a batch of unacceptable quality (i.e., the test is robust) except in extreme situations, which do not necessarily represent commercially viable products. The results also demonstrate that, in the case of bimodal distributions where the life-stage means differ from each other by up to 24% label claim, the test's criterion on life-stage means does not affect pass rates because the tolerance interval portion of the test reacts to shifting means as well.

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