A platform approach for mAb and mAb-like therapeutic protein cell culture process development has been established to speed bioprocess development times and reduce complexity associated with technology transfer to manufacturing. To enable this strategy, process understanding must be achieved across multiple projects within the platform. For upstream processes, this entails understanding the first principles such as mass transfer and mixing that dictate the bioreactor performance at lab and manufacturing settings. Furthermore, empirical modeling can be performed to identify the important scale-up factors that affect the upstream bioprocess outcome.

Empirical modeling was completed using several platform-based projects that had been scaled up to the cGMP CT pilot plant. Factors such as dissolved gases, seed train performance, and process controllability were examined while all process setpoints were assumed constant between the scales (i.e. temperature, pH). The resulting models indicated that matching seed train performance and dissolved carbon dioxide levels between the bench and pilot scales would result in equivalent productivities.

These models have been implemented and are being used to focus attention on the most important scale up parameters during technology transfer to increase the probability of success at scale. As a result, the productivities demonstrated by the CT pilot plant have matched that of the bench scale to date.