Multidisciplinary Approach to Optimize and Redefine Bioreactor Operations: Leveraging Coupled Bioreactor Analytics, Automated Sampling, and Applied Mathematics to Improve Productivity & Product Quality
The focus of the presentation will be on introducing an emerging process-development methodology that is based on applying novel and existing bioreactor monitoring technologies to existing bioreactor processes, coupled with applied mathematics and data-integration techniques across disciplines. This methodology offers an improved way to turn large raw data sets into useful guidance for process development and guidance. This methodology enables better use of existing data, as well as strategies to generate more frequent and higher-quality data sets to meet the dynamic nutrient requirements of cell cultures. This approach employs the use of dielectric spectroscopy (DS), other enhanced process-analytical technologies (PATs), and cell-based bioreactor models with a simple, compact device that automatically obtains samples aseptically at specified intervals for off-line analysis.
Examples will be shown, including a case study of a user interface linking on-line data with applied-mathematics techniques to increase process understanding at the cellular level under different growth conditions as well as a case study of statistical modeling techniques being used to predict and forecast cell culture productivity in a bioreactor.
See the webinar here: