JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 435
Type: Contributed
Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #315717 View Presentation
Title: Shelf Life Estimation: Bayesian Augmented Mixed Model Approach
Author(s): Maryna Ptukhina* and Walter Stroup
Companies: University of Nebraska - Lincoln and University of Nebraska - Lincoln
Keywords: shelf life ; BLUP
Abstract:

Shelf life estimation procedures, following ICH guidelines, use multiple batch regression with fixed batch effects. This guidance specifically mandates estimates based on at least 3 batches. Technically, the fixed-batch model limits inference to the batches observed, whereas ICH also requires resulting estimates to apply to all future batches. This creates a conflict between the model used and the inference space the model is intended to address. Quinlan, et al. (2013) and Schwenke (2010) studied the small sample behavior of this procedure. Both studies revealed large sampling variation associated with the ICH procedure, producing a high proportion of extreme estimates. Quinlan, et. al (2013) also considered alternative approaches including mixed models with random batch effects. While this eliminated the conflict between model and intended inference space, there were still problems with the approaches Quinlan considered. We present a Bayesian augmented mixed model approach to shelf life estimation that takes advantage of the theoretical benefits of the mixed model and uses prior information about variance components to improve accuracy of shelf life estimation procedure.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home