It is often difficult to include sufficient biological detail when modelling cell population growth to make models with real predictive power. Continuum models often fail to capture physical and chemical processes happening at the level of individual cells and discrete cell-based models are often very computationally expensive to solve. In the first part of this talk, I will describe a phenomenological continuum model of cell aggregate growth in a specific perfusion bioreactor cell culture system, and the results of numerical simulations of the model to determine the effects of the bioreactor operating conditions and cell seeding on the growth. In the second part of the talk, I will introduce a modelling approach used to derive continuum models for cell population growth from discrete cell-based models, and consider possible extensions to this framework.
