435 – Clinical Trial Design III
Shelf Life Estimation: Bayesian Augmented Mixed Model Approach
Maryna Ptukhina
University of Nebraska - Lincoln
Walter Stroup
University of Nebraska - Lincoln
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.