Optimization of Monoclonal Antibody Production in Fed-Batch Fermentation Processes of Hybridoma Cells by Using Genetic Algorithm

In this study, the optimization of a semi-continuous culture of hybridoma cells have been investigated to maximize the production of monoclonal antibodies by using a genetic algorithm.  The culture time was ten days. The objective function was the monoclonal antibody production and the independent variables were daily feeding profiles of the substrate (glucose and glutamine). To achieve the optimal feeding strategy, a seventh-order kinetic model was used to model the hybridoma semi-continuous cultivation process. The governing differential equations have been solved using MATLAB software. The modeling results show that the optimal amount for monoclonal antibody production based on the uniform feeding profile of the substrate is 233 mg and based on the variable feeding profile of the substrate is 314 mg, which shows 34% improvement in monoclonal antibody production. In addition, the results of the model have a consistent agreement with the previous research by Trembli et al. and Miguel et al.