Abstract Details
Activity Number:
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133
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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Abstract - #308970 |
Title:
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Estimating Shelf Life via Mixed-Model Quantile Regression
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Author(s):
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Michelle Quinlan*+ and Walt W. Stroup and Dave Christopher
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Companies:
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Novartis Oncology and University of Nebraska-Lincoln and Merck
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Keywords:
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shelf life ;
quantile regression ;
random effects
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Abstract:
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Two key aspects in shelf life estimation made clear from the evaluation of the ICH methodology are: (1) batches are random effects, and (2) the focus should be on a quantile of the distribution. A batch's shelf life is the time the batch specific regression line intersects the acceptance limit. Given the relationship between the distribution of batch mean responses over time and the distribution of batch shelf lives, the desired quality statement to be made about any pharmaceutical product is that all batches meet or exceed the established shelf life with an acceptably high probability. The developed mixed model quantile regression procedure for estimating shelf life allows not only for a quality statement such as this to be made about the product, but also addresses the two key aspects in shelf life estimation inferred from the ICH methodology. The methodology and implementation of the mixed model quantile regression procedure for shelf life estimation are discussed along with utilizing the relationship between quantiles of the batch mean responses over time and quantiles of the distribution of batch shelf lives.
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Authors who are presenting talks have a * after their name.
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