title: Shelf life determination based on equivalence assessment.
abstract: In a regular analysis of covariance (ANCOVA) approach to stability analysis, the decision for pooling data from different batches plays a key role in the determination of the shelf life of the drug product. Conventionally, the decision to pool data for the estimate of slope and intercept of common or individual regression lines is made by "no evidence to reject the null hypothesis of no difference." With typically limited observations, a significance level of much higher than 0.05 was recommended for the pooling tests in order to avoid inflation of type-I error rate of the shelf life testing. This logic of the pooling test decision making discouraged the use of replicates to improve power of testing and precision of estimation. The concept of pooling by equivalence test was originally proposed by Ruberg and Hsu in their 1990 article "Multiple comparison procedures for pooling batches in stability studies" Such a concept has evolved to pooling batches based on the shelf life equivalence test by Yoshioka et al. in their 1996 article "Power of analysis of variance for assessing batch-variation of stability data of pharmaceuticals." In this article, an approximation test of shelf life equivalence and a test of chemical value equivalence for the data pooling decision are proposed as an alternative to the conventional ANCOVA approach.
authors.affiliation: Office of Biostatistics, Center for Drug Evaluation and Research, FDA, Rockville, Maryland 20875, USA. tsong@cder.fda.gov
authors.forename: Yi
authors.initials: Y
authors.lastname: Tsong
authors.forename: Wen-Jen
authors.initials: WJ
authors.lastname: Chen
authors.forename: Tsae-Yun Daphne
authors.initials: TY
authors.lastname: Lin
authors.forename: Chi Wan
authors.initials: CW
authors.lastname: Chen
mesh_terms: D016001:Confidence Intervals; D004355:Drug Stability; D004356:Drug Storage / Q000592:standards / Q000706:statistics & numerical data; D015233:Models, Statistical; D013997:Time Factors