A coupled single cell-population-balance model for mammalian cell cultures

Mainstream modeling of cell culture systems to date has followed two distinct approaches: cell population-balance modeling and single-cell modeling. The former aims to capture increasing heterogeneity between cells, while the latter attempts to faithfully capture intracellular processes. However, the oversimplistic expressions used in the single-cell kernels, the functions that characterize single-cell behavior, are the main predictive bottleneck of population-balance models (PBMs). Single-cell models (SCMs) do not describe differences between cells, such as the mass variation. We present a new model that captures certain strengths of both approaches. It uses a highly structured SCM to characterize the single-cell growth and death rates that are applied to terms in each stage of a multistaged PBM. The high degree of intracellular detail, however, also leads to more than 700 parameters. The parameter set is significantly reduced by employing an estimability method on the model. The model is subsequently compared using literature data for batch and fed-batch conditions.