Speaker
Description
Background: The stability of a drug product over time is a critical property in pharmaceutical development. A key objective in drug stability studies is to estimate the shelf-life of a drug, involving a suitable definition of the true shelf-life and the construction of an appropriate estimate of the true shelf-life. Simultaneous confidence bands (SCBs) for percentiles in linear regression are valuable tools for determining drug shelf-life in drug stability studies.
Methods: In this paper, we propose a novel criterion, the Minimum Area Confidence Set (MACS), for identifying the optimal SCB for percentile regression lines. This criterion focuses on the area of the constrained regions for the newly proposed pivotal quantities, which are generated from the confidence set for the unknown parameters of a SCB. We employ the new pivotal quantities to construct exact SCBs over any finite covariate intervals and use the MACS criterion to compare several SCBs of different forms. Additionally, we introduce a computationally efficient method for calculating the critical constants of exact SCBs for percentile regression lines.
Results: The optimal SCB under the MACS criterion is demonstrated to effectively construct interval estimates of the true shelf-life. The proposed method for calculating critical constants significantly improves computational efficiency. A real-world drug stability dataset is used to illustrate the application and advantages of the proposed approach.
75002911487