Abstract
We review major modeling strategies and methods to understand and simulate the macroscopic behavior of mammalian cells. These strategies comprise two important steps: the first step is to identify stoichiometric relationships for the cultured cells connecting the extracellular inputs and outputs. In a second step, macroscopic kinetic models are introduced. These relationships together with bioreactor and metabolite balances provide a complete description of a system in the form of a set of differential equations. These can be used for the simulation of cell culture performance and further for optimization of production.
Highlights
Mammalian cell cultures are the major source of a number of biopharmaceutical products, including monoclonal antibodies (Niklas and Heinzle 2012; Sidoli et al 2004), viral vaccines (Vester et al 2010), and hormones (Nottorf et al 2007)
Lactate and ammonia were considered as toxic products of catabolic reactions, which inhibit cell growth and can cause cell death in their model; even though they assumed that hybridoma cells can produce monoclonal antibodies until any of amino acid is depleted, they only considered glutamine as a limiting amino acid
As in most other cases of modeling, macroscopic modeling of mammalian cell cultures is an iterative process of setting up a model, calibrating, validating, and testing it; designing and performing new experiments; and revising the model
Summary
Mammalian cell cultures are the major source of a number of biopharmaceutical products, including monoclonal antibodies (Niklas and Heinzle 2012; Sidoli et al 2004), viral vaccines (Vester et al 2010), and hormones (Nottorf et al 2007). Reactions and interactions are represented as continuous processes (production, consumption, growth...) by corresponding mathematical functions It is appropriate for systems composed of a relatively large number of cells, e.g., more than 10,000. This general reaction scheme represents a macroscopic stoichiometric relationship To set up such a macroscopic model, the important parameters, i.e., the relevant cellular inputs, ξi; and outputs, ξ j; as well as the stoichiometric coefficients, νi;k; ν j;k; relating the inputs to the outputs, have to be determined. This can start from the increasingly comprehensive knowledge of cellular reactions and transport or, as traditionally done, from purely empirical data. This step is often the main bottleneck in the design of a macroscopic model for complex biotechnological processes
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