Mammalian cell cultures are widely used to produce biopharmaceuticals, e.g. antibodies, interferons etc. Optimisation of cell culture productivity via experimentation alone is costly and time consuming; and model-based approach which can potentially speedup the procedure is still a challenge due to the complex nature of cell systems (Sanderson et al. 1997; Sanderson et al. 1995; Schneider 1989). Cell cultures tend to reach a higher viable cell density and product concentration when they are grown in fed-batch cultures instead of batch cultures (Frahm et al. 2003; Gorfien et al. 2003; Xie et al. 1997). Current models of mammalian cell cultures mainly capture major cellular activities such as metabolisms, growth and death kinetics and product formation (Batt and Kompala 1989; Bree and Dhurjati 1988; Frame and Hu 1991; Jang and Barford 2000; Portner and Schafer 1996; Sidoli et al. 2004; Tziampazis and Sambanis 1994; Zeng 1996; Zeng and Deckwer 1995); but cellular regulations at various culture conditions are yet to be modelled in a tractable way for practical bioprocess optimisation.

We propose a deterministic unsegregated and unstructured model linking nutrients uptake, growth, death, and product synthesis to cellular responses upon a decrease in concentration of glucose and glutamine that are encountered in fed-batch culture conditions, and apply the model on a CHO-IFNγ cell-line. The cellular responses to low nutrient concentration are modelled using a semi-black box approach based on biologically known cellular regulations under low nutrient concentrations from the literature together with justified assumptions and simplifications where the biological knowledge is incomplete. The model consists of roughly 60 differential algebraic equations and includes key culture variables such as glucose, amino acids, lactate, ammonia, IFNγ, viable and total cell concentration. Such a model integrates cellular regulation mechanisms with traditional macroscopic cell culture modelling in order to bridge the gap between detailed models that are not readily applicable for new cell lines and simple models that do not capture certain different cell culture behaviours encountered in fed-batch conditions. The model parameters are analysed using global sensitivity analysis and the sensitive parameters are estimated from batch and fed-batch CHO-IFNγ culture data. The model developed would be used to optimise the feed profiles of two dominating nutrients, glucose and glutamine, for CHO-IFNγ fed-batch cultures.

The proposed model could serve as an initial step to incorporate cellular regulations into mammalian cell culture process optimisation. As current developments of genomics, proteomics, and metabolomics continue to reveal hidden aspects of cell metabolism and signalling, novel discoveries of cell culture dynamics would enrich the model structure to further enhance its predictive ability. The model structure can potentially be adapted to various mammalian cell lines to meet the need of multi-cell-line nutrient profile optimisation in the bioindustry.

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