A Coupled Single Cell-Population Balance Model for Mammalian Cell Cultures

Abstract Accurate quantitative prediction of mammalian cell culture behaviour is crucial in optimising the productivity of the important therapeutic and diagnostic high value products they synthesize. The two major facets all good predictive models must address are (1) the heterogeneity of cellular properties that differentiate one cell from another in the culture, and (2) the complex intracellular structure that constitutes a cell entity. Population balance models capture the heterogeneity but little structure with which to differentiate the cells due to the computationally intense nature of their solution while the structured kinetic single cell models are good at describing structure but cannot describe heterogeneity. We present a new model that captures certain strengths of both modelling frameworks. The model consists of a modified version of a highly structured single cell model (Sanderson 1997) that is coupled to a structured population balance model via single cell growth rates. The culture is structured into sub-populations associated with cell cycle phases and cells are distinguished on the basis of their mass and nuclear DNA content