%0 Journal Article %A Steven J. Novick %A Elizabeth Christian %A Erika Farmer %A Max Tejada %T A Bayesian Statistical Approach to Continuous Qualification of a Bioassay %D 2021 %R 10.5731/pdajpst.2019.011221 %J PDA Journal of Pharmaceutical Science and Technology %P 8-23 %V 75 %N 1 %X A validated bioassay is used to measure the potency of commercial lots, and as such, must be accurate, precise, and fit for its intended purpose. Regulatory expectations for a bioassay include a characterization of features, such as accuracy, precision, linearity, and range. The journey of a bioassay typically starts in a development lab, where it is initially qualified and used to support the release and stability testing of clinical lots. As a program moves through the different clinical phases, it may be optimized further, used to support process development, or transferred to new laboratories, with each activity generating additional bioassay data. Finally, the bioassay is fully validated as part of the transfer to the commercial quality control testing laboratories. In this work, rather than capturing the data from each study as a separate, independent report, it is proposed that, beginning with the qualification study, the accuracy and precision of the bioassay be continuously characterized, with each subsequent study result building upon the preceding ones. We call this approach continuous qualification. Such a proposition is naturally carried out using Bayesian statistical methods in which the historical study data is used to construct prior knowledge that is blended with the current study data. By doing so, the bioassay accuracy and precision may be assessed with high confidence well ahead of commercial manufacturing. Further, by following the total-variance approach, the method also allows for a robust construction of system suitability and control limits for potency. %U https://journal.pda.org/content/pdajpst/75/1/8.full.pdf