A common challenge with Cell & Gene Therapy products and other products having accelerated approval status is the limitation of available data to develop acceptance criteria. This can lead to inaccurate ranges that can be either too wide or too narrow, depending on the method used to compute the specifications. An adaptive approach using Bayesian statistical methods could incorporate all existing information, not just the sample data to develop initial specifications. As process data accumulates, specifications would be mathematically updated to develop more accurate ranges than possible with classical statistical approaches. These methods are used with great success in adaptive clinical trials to establish the endpoint with fewer patients. There is substantial opportunity to leverage these methods for CMC applications to develop more accurate models especially in situations of small sample size and complex relationships.
Upon completion, participant will be able to describe (at a high level) a statistical method that can address the challenge of specification development when the sample size is small
Upon completion, participant will be able to list other pharma regulated situations that currently that leverage the Bayesian approach
Upon completion, participant will be able to list the ultimate benefit to patient when more accurate modelling methods are utilized