4.4.1 Suspension growth (w/o microcarriers) in a stirred tank
bioreactor
In the case of stirred tank set-ups w/o microcarriers, Bayrak et al.
[29] uses a hybrid methodology combining flux balance and
agent-based modeling which can predict quantitative changes in nutrient
and metabolite concentrations in a fed-batch set up. The model uses the
measured dissolved oxygen and sodium data as input together with initial
cell culture conditions and predicts viable cell density, viability and
concentrations of glucose and lactate. The model shows good agreement
with experimental trials. However, the application is low density
(< 107 cells/mL) and, as the authors
explain, assumes ideal mixing, with no allowance for spatial gradients.
In cultivated meat, the output required demands high density and/or
large-scale bioreactors, in which gradients are inevitable. To capture
spatial gradients and heterogeneities will require three-dimensional
modeling with cells or aggregates of cells represented by distinct
agents.
The review paper by Hutmacher and Singh [30] on the application of
computational fluid dynamics to three-dimensional modeling of tissue
engineering-related bioreactors concludes that fluid flow processes have
direct implications on cellular responses such as attachment, migration
and proliferation. For cultivated meat, we propose to extend these
principles to modeling of suspension growth in a stirred tank
bioreactor, introducing a high-density of cell-clusters, each
represented by an agent, to correspond to a higher density of cells.