A Two One-Sided Parametric Tolerance Interval Test for Control of Delivered Dose Uniformity. Part 1—Characterization of FDA Proposed Test

The FDA proposed a parametric tolerance interval (PTI) test at the October 2005 Advisory Committee meeting as a replacement of the attribute (counting) test for delivered dose uniformity (DDU), published in the 1998 draft guidance for metered dose inhalers (MDIs) and dry powder inhalers (DPIs) and t...

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Bibliographic Details
Published inAAPS PharmSciTech Vol. 10; no. 3; pp. 820 - 828
Main Authors Novick, Steven, Christopher, David, Dey, Monisha, Lyapustina, Svetlana, Golden, Michael, Leiner, Stefan, Wyka, Bruce, Delzeit, Hans-Joachim, Novak, Chris, Larner, Gregory
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.09.2009
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Summary:The FDA proposed a parametric tolerance interval (PTI) test at the October 2005 Advisory Committee meeting as a replacement of the attribute (counting) test for delivered dose uniformity (DDU), published in the 1998 draft guidance for metered dose inhalers (MDIs) and dry powder inhalers (DPIs) and the 2002 final guidance for inhalation sprays and intranasal products. This article (first in a series of three) focuses on the test named by the FDA “87.5% coverage.” Unlike a typical two-sided PTI test, which controls the proportion of the DDU distribution within a target interval (coverage), this test is comprised of two one-sided tests (TOST) designed to control the maximum amount of DDU values in either tail of the distribution above and below the target interval. Through simulations, this article characterizes the properties and performance of the proposed PTI-TOST under different scenarios. The results show that coverages of 99% or greater are needed for a batch to have acceptance probability 98% or greater with the test named by the FDA “87.5% coverage” (95% confidence level), while batches with 87.5% coverage have less than 1% probability of being accepted. The results also illustrate that with this PTI-TOST, the coverage requirement for a given acceptance probability increases as the batch mean deviates from target. The accompanying articles study the effects of changing test parameters and the test robustness to deviations from normality.
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ISSN:1530-9932
1530-9932
DOI:10.1208/s12249-009-9270-x