Abstract: The shelf-life of a drug product is the time that the average drug characteristic (e.g., potency) remains within an approved specification after manufacture. The United States Food and Drug Administration (FDA) requires indication for every drug product of a shelf-life on the immediate container label. Since the true shelf-life of a drug product is typically unknown, it has to be estimated based on assay results of the drug characteristic from a stability study usually conducted during the process of drug development. Furthermore, the FDA requires that the estimated shelf-life be so constructed that it is statistically evident that the estimated shelf-life is less than the true shelf-life, i.e., the estimated shelf-life should be a conservative (negatively biased) estimator. In this paper, we study and compare several shelf-life estimators, one of which is adopted by the FDA's 1987 guidelines, in terms of their asymptotic biases and mean squared errors. Finite sample performance of some shelf-life estimators is examined in a simulation study.
Key words and phrases: Asymptotic bias, asymptotic mean squared error, batch-to-batch variation, inverse regression, lower confidence bound, lower prediction bound.