A carbon dioxide stripping model for mammalian cell culture in manufacturing scale bioreactors (Biotechnology and Bioengineering)

Control of carbon dioxide within the optimum range is important in mammalian bioprocesses at the manufacturing scale in order to ensure robust cell growth, high protein yields, and consistent quality attributes. The majority of bioprocess development work is done in laboratory bioreactors, in which carbon dioxide levels are more easily controlled. Some challenges in carbon dioxide control can present themselves when cell culture processes are scaled up, because carbon dioxide accumulation is a common feature due to longer gas-residence time of mammalian cell culture in large scale bioreactors. A carbon dioxide stripping model can be used to better understand and optimize parameters that are critical to cell culture processes at the manufacturing scale. The prevailing carbon dioxide stripping models in literature depend on mass transfer coefficients and were applicable to cell culture processes with low cell density or at stationary/cell death phase. However, it was reported that gas bubbles are saturated with carbon dioxide before leaving the culture, which makes carbon dioxide stripping no longer depend on a mass transfer coefficient in the new generation cell culture processes characterized by longer exponential growth phase, higher peak viable cell densities, and higher specific production rate. Here we present a new carbon dioxide stripping model for manufacturing scale bioreactors, which is independent of carbon dioxide mass transfer coefficient, but takes into account the gas-residence time and gas CO2 saturation time. The model was verified by CHO cell culture processes with different peak viable cell densities (7 to 12 × 106 cells/mL) for two products in 5,000-L and 25,000-L bioreactors. The model was also applied to a next generation cell culture process to optimize cell culture conditions and reduce carbon dioxide levels at manufacturing scale. The model provides a useful tool to understand and better control cell culture carbon dioxide profiles for process development, scale up, and characterization. This article is protected by copyright. All rights reserved