title: A two one-sided parametric tolerance interval test for control of delivered dose uniformity--part 3--investigation of robustness to deviations from normality.
abstract: 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.
authors: Discovery Analytics, GlaxoSmithKline, Research Triangle Park, North Carolina, USA.
authors: Steven
authors: S
authors: Novick
authors: David
authors: D
authors: Christopher
authors: Monisha
authors: M
authors: Dey
authors: Svetlana
authors: S
authors: Lyapustina
authors: Michael
authors: M
authors: Golden
authors: Stefan
authors: S
authors: Leiner
authors: Bruce
authors: B
authors: Wyka
authors: Hans-Joachim
authors: HJ
authors: Delzeit
authors: Chris
authors: C
authors: Novak
authors: Gregory
authors: G
authors: Larner
mesh_terms: D000281:Administration, Intranasal; D000336:Aerosols; D000465:Algorithms; D016503:Drug Delivery Systems / Q000592:standards* / Q000706:statistics & numerical data; D015233:Models, Statistical; D015203:Reproducibility of Results; D018401:Sample Size; D014481:United States; D014486:United States Food and Drug Administration
chemical_list: D000336:Aerosols