Analyzing the dynamics of cell growth and protein production in mammalian cell fed-batch systems using logistic equations

Abstract

The logistic modeling approach was used to describe experimental viable cell density (X) and product concentration (P) data from two industrial fed-batch mammalian cell culture processes with maximum product concentrations in the 3.0–9.4 g/l range. In both cases, experimental data were well described by the logistic equations and the resulting specific growth rate and protein productivity profiles provided useful insights into the process kinetics. Subsequently, sensitivity equations for both the X and P models were analyzed which helped characterize the influence of model parameters on X and P time courses. This was augmented by conventional sensitivity analyses where five values of each model parameter, 25% apart, were used to generate X and P time courses. Finally, results from sensitivity analysis were used to simulate X and P time courses that were reflective of typical early- and late-stage fed-batch cell culture processes. Different combinations of the logistic model parameters were used to arrive at the same final product concentration demonstrating the ability of the logistic approach to describe the multitude of process paths that result in the same final product concentration. Overall, the capability of the logistic equations to well describe X and P data from fed-batch cultures, coupled with their ability to simulate the multitude of paths leading up to the desired cell density and product concentration profiles, make them a useful tool during mammalian cell fed-batch process development.