Data Integration Methodology that Leverages Coupled Bioreactor Monitoring Tools, Automated Sampling, and Applied Mathematics to Redefine Bioreactor Operation

Optimization of bioreactor operation, media composition, and feed strategies typically involves a significant set of experiments based on limited, empirical, primarily off-line/at line, and few on-line data sets. Since cell physiology dynamically affects the nutrient requirements of the culture, it is critical to obtain the appropriate data over appropriate time intervals to assess the impact of process conditions on the cell population.

To accomplich continuous process improvements, achieve quality by design (QbD), and shorten development timelines, a new development paradaign is required. Here, we present an emerging process-development methodology that is based on applying novel and existing bioreactor monitoring technologies to existing bioreactor processes, coupled with applied mathematics.

This approach employs tools like dielectric spectroscopy, and cell-based bioreactor models, in conjuntion with a simple, compact device that automatically obtains samples aseptically at specified intervals for off-line analysis. This poster presents how the information gained from all of these individual tools can be coupled by using the right data integration and applied mathematics techniques.


This poster was presented at IFPAC 2013.


Biotherapeutics / Bioprocessing