Mechanistic models provide a quantitative framework for understanding and optimizing bioprocesses, yet their application to microbial cultures in industrial settings remains limited by the complexity of the underlying biophysical phenomena. In this work, we present a comprehensive mechanistic model of Escherichia coli cultures that integrates membrane transport phenomena, intracellular metabolic reactions, and cell division dynamics. The model predicts the influence of key process parameters, including feed composition, feeding strategy, pH, and temperature, on biomass growth, product formation kinetics, and time-resolved metabolite concentrations such as glucose, glutamate, acetate, formate and ammonia. Model development and validation were supported by an extensive experimental dataset generated by Sanofi as part of the CALIPSO project, enabling robust parameter estimation and scenario analysis. This case study demonstrates the capability of mechanistic modeling to capture complex bioprocess behavior and highlights its potential for guiding numerical process optimization in future biopharmaceutical manufacturing workflows.
