(384a) Use of Real-Time Analytics and Apoptosis Assays for Enhanced Understanding of Cell Growth and Viability in a CHO-Based Process for Monoclonal Antibody Production
AIChE Annual Meeting
2016 AIChE Annual Meeting
Pharmaceutical Discovery, Development and Manufacturing Forum
Tools for Accelerating Pharma Development and Innovations in Biopharmaceutical Discovery, Development, and Manufacturing
Tuesday, November 15, 2016 - 12:30pm to 12:52pm
In this study, we have applied markers of early, middle and late apoptosis to evaluate changes in cell growth, health and viability during a fed-batch process in 5L bioreactors. The markers that were monitored included 7-AAD, Caspases, and TUNEL assay for DNA nicking. Multiple early and mid-stage apoptotic markers were compared for their effectiveness in evaluating cell health and predicting cell growth trends in a bioreactor. Additionally, to provide more frequent cell growth measurements and metabolite readings to align with apoptotic assays, in-line probes were incorporated for real-time data analysis. Through calibration and method development, a capacitance-based Incyte probe was used for real-time monitoring of viable cell density (VCD), and an in-line Raman spectroscopy probe was used for real-time monitoring of glucose and lactate.
The results demonstrated that apoptotic markers can provide additional insight into cell health beyond what is learned from daily cell counts, thereby greatly deepening our understanding of cell culture conditions and process parameters during development. Markers of early apoptosis were observed several days prior to a drop in viability as measured by a commercial cell counter, while late-stage apoptotic markers were observed hours in advance or concurrently with the VCD and viability drop. Further insight into the health and productivity of the culture may be obtained by correlation of in-line metabolite and cell growth profiles with cell apoptotic progress.
In summary, optimization and application of real-time analytics and apoptosis assays in a CHO cell process can provide a rich and complete data set for better visualization of cell growth and health throughout the culture process, thereby enabling process improvement to maximize product titer and quality.