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The biopharmaceutical industry is known for its long time-to-market and for requiring large resources and time investment for product development. The type of activities required at the start of a biopharmaceutical product development focus mainly on designing a suitable process for manufacturing as rapidly as possible material to be tested in pre-clinical and clinical trials. The number of development and GMP batches is at this stage typically limited. This is followed, upon success in early clinical trials, by a process optimization phase, which aims at increasing yields while reducing costs-of-good. Moving on towards late stage development, the manufacturing process needs to be characterized, meaning that its robustness to produce the desired product quality when operated within certain process ranges needs to be demonstrated. This phase is a major component of process development as it translates into generating large numbers of development batches using elaborate analytical methods and advanced statistics, in order to fully study the relations between the manufacturing process and product quality.
Janssen Vaccines has transitioned over the last 3 years from being focused on early stage process development, to being able to accommodate and run full late stage development programs. Janssen Vaccines also embraces the principles of Quality by Design (QbD) in its development programs, where science and risk-based approaches are used as a systematic way to build product and process understanding.
In this presentation, we present the implications of this transition from early to late stage development, with the case-study of the QbD-based characterization of a perfusion-based PER.C6® cell culture process for Adenovirus vaccine production.
Computational Fluid Dynamics modeling and in-depth scaling calculations have been utilized in partnership to generate data to support equipment design and facility fit during commercialization of a fermentation and primary recovery process for a vaccine candidate across multiple technical transfers. This analysis utilizing representative computer models for tank configurations, supplemented with traditional computational scaling approaches (ungassed P/V, gassed P/V, kLa, etc.), ensures full knowledge of a tank’s mixing and oxygen transfer capabilities allowing process understanding and robust manufacturing across technology transfer to multiple sites. Implementation of this approach across process steps as well as manufacturing sites allows increased knowledge prior to use in a process and/or prior to construction of a new vessel, therefore contributing to successful process transfer with reduced risks upon scale-up/scale-down and new facility introductions.