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47187 - The Acceptance of Modelling Approaches

‐ Oct 18, 2022 5:15pm

Over recent years, an increasing number of medicines have been developed for orphan indications and for treatment of unmet clinical need. The abbreviated development times associated with such clinical programmes has required sponsors to expedite CMC activities. Furthermore, the development of precision medicines has driven pharmaceutical development into more complex manufacturing of sophisticated drug products and dosage forms. This paradigm shift in pharmaceutical development has encouraged companies to challenge traditional approaches to product and process development. One area, which has until now been under explored is the use of models in CMC submissions.
Various modelling approaches can have different objectives, including increasing predictability, improving processes understanding, or expediting CMC development. This is particularly relevant for data driven models governing stability, control strategy, process validation, and product and process design. Examples of such approaches include stability models to predict shelf life, chemometric models for quality control of finished product, and adaptive process models used to adjust a manufacturing process in real time.
Nonetheless, while it is recognised that such models may have wide applicability in many areas of CMC, there are perceived regulatory barriers to their adoption. The intent of this session is to share industry experiences on how new modelling approaches can be applied, to get regulators’ views on the development of new guidance on models, and to discuss potential regulatory barriers to the successful implantation of such models in CMC submissions.

Session Speakers:
Regulatory Considerations for Modelling as a Tool for Process Understanding and Control
Matthew Popkin, GSK plc., United Kingdom

Enhanced Process Characterization through Monte-Carlo Simulations: From a Local to a Global Understanding of the Process 
Hervé Broly, Merck Serono, Switzerland 

Using Stability Prior-knowledge from 'Like-molecules' to Determine Shelf-life
Andrew Lennard, Amgen Limited, United Kingdom

Some Reflections on the Use of Models in Module 3
Nick Lee, HPRA-Health Products Regulatory Authority, Ireland

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