Definitely, I would challenge the analytical development team as well as the process team to gather all prior information available from development studies (characterisation, optimization, qualification, validation, ..., or even from similar processes/assays) to give all available data and build from this database informative prior distributions that could then be used into the specification definition setting with a Bayesian approach. Indeed, there is a huge knowledge available that could be used to “help” all situations where “low” amount of data is available. If this possible for clinical trials (pediatric, rare disease,...) why not in CMC/Non-clinical applications?

Learn more from Dr. Eric Rozet by viewing his presentation “Patient-Centric Commercial Specifications for Biotherapeutic Products, Strategies and Case studies” during the Expert Forum:  Setting Biopharmaceutical Specifications: Navigating Regulatory Requirements in Accordance with ICH Q6B 

When only a small number of batches are available, a purely statistical approach cannot be relied upon. Prior knowledge, including data from early development studies, will be used to support the specification. Clinical data—particularly safety and efficacy results from those batches—will also be considered to justify the acceptance range. If necessary, a wider range will be applied initially and refined later as more data become available. In such cases, a risk-based approach is considered essential.

Join Dr. Patanachai “Kong” Limpikirati from Chulalongkorn University to learn more about the basic regulatory science underlying drug substance and drug product specifications of monoclonal antibodies.

Watch the On-Demand presentation now: https://bio-qc.com/the-basic-regulatory-science-behind-drug-substance-and-drug-product-specifications-of-monoclonal-antibodies-and-other-protein-therapeutics/

Plus, don’t miss his expert insights during the panel discussion on Setting Biopharmaceutical Specifications: Navigating Regulatory Requirements in accordance with ICH Q6B.