Estimating Shelf Life Through Tolerance Intervals
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Updated: Dec 5, 2025

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Published on: May 6, 2009
James Schwenke1, Michelle Quinlan2, Walter Stroup3
1Applied Research Consultants, LLC, 119 Town Farm Road, New Milford, Connecticut, 06776, USA. JRSchwenke@aol.com.
Abstract:
This paper is a continuation of the research published by the Stability Shelf Life Working Group as chartered under the Product Quality Research Institute. The Working Group was formed in 2006 and disbanded in late 2019. Following the philosophy presented by the Working Group on how to characterize the stability shelf life paradigm (Capen et al., 2012), shelf life is estimated here in terms of defining risk as a specified proportion of the pharmaceutical stability distribution of interest being out of specification. Shelf life can be defined for the batch mean distribution for regulatory issues, as well as for the product distributions for patient interests. Estimates of shelf life are proposed corresponding to each stability distribution through the use of statistical tolerance intervals. Appropriate estimates of the between-batch and within-batch variance components are obtained through a random coefficient mixed regression model analysis based on the best fit to batch stability response data. Tolerance interval estimates are computed as part of the mixed model analysis and computed directly using the statistical definition of the stability distributions. A proposed rationale is offered on how to select an appropriate proportion allowed out of specification to define a meaningful shelf life. Examples of the proposed shelf life estimates are presented using industry stability batch data. For each example, the traditional ICH shelf life estimate is given for comparison.
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