Development of a mathematical model for animal cell culture without pH control and its application for evaluation of clone screening outcomes in shake flask culture

Abstract

BACKGROUND: Currently used mathematical models for animal cell growth and metabolism cannot simulate changing culture pH and its effect on metabolism, and hence cannot accurately model cultures lacking pH control. Animal cell cultures are however widely cultured at a small scale without pH control, e.g. for clone screening during cell line development. A mathematical model for animal cell growth without pH control is developed and applied to design optimal conditions for clone screening without pH control.RESULTS: The mathematical model successfully simulates published data for suspension CHO culture in shake flasks. It is further used to simulate clonal heterogeneity and predict relative clone performance in different culture conditions. Predictions of correlation coefficients between clone titers in batch and fed batch screening conditions and pH controlled fed batch agree with published values. Fed batch mode is predicted to give better screening outcomes than batch, but only for clones able to consume lactate. Simulations reveal that culture duration of the screening assay has a large effect on the screening outcome and optimal durations differ based on the ability or inability of clones to consume lactate. CONCLUSION: This study presents a tool for optimal design of screening assay for clone selection without pH control.

Screening and assessment of performance and molecule quality attributes of industrial cell lines across different fed-batch systems

“…Considering lactate metabolism during cell line selection might be an additional tool for identifying high producer cell lines during the screening process in uncontrolled vessels. Indeed, Gadgil developed a mathematical model simulating cell culture in absence of pH control, which showed a better screening outcome for fed‐batch mode compared to batch mode for clones able to consume lactate, and a high impact of the culture duration on the selection outcome with an optimal duration differing according to the capacity of clones to consume or not lactate. Regarding ammonium, moderate levels were accumulated during the cultures, except for cell line 1 in shake tubes, where 11 mM were measured on day 14.…”

Population balance modelling captures host cell protein dynamics in CHO cell cultures

“…In Eq ( 19 ), glucose is consumed by cell growth and maintenance-nongrowth-dependent terms [ 87 – 89 ]. The maintenance term, m glc ( mmol cell −1 h −1 ), is the consumption rate for glucose that does not depends on cell growth rate.…”

“…by describing maximum cell growth rate as a continuous function of temperature using the Arrhenius and Eyring equations [ 96 ]. The third method is based on statistical modelling to derive a correlation from experimental data or other common equation for the pH such as Henderson-Hasselbalch [ 89 , 97 , 98 ].…”

Cell Culture Processes for Biopharmaceutical Manufacturing

“…They showed that clone ranking during screening in fed batch mode in shake flasks is not identical to their ranking in pH controlled fed batch bioreactors. To help understand the effect of lack of pH control on the outcome of screening process, we developed a mathematical model to simulate changing culture pH due to lactate formation in animal cell cultures, along with incorporation of the effect of pH on cell metabolism and growth as reported in the literature 59 . Such models can help guide the design of screening assays; for e.g., this model suggested that culture duration for screening assay has greater effect on the outcome of the assay.…”