DoE of fed-batch processes – model-based design and experimental evaluation

Background Experimental process-development and optimization is expensive and time-consuming. Real optimization by means of design of experiments involves data generation before optimization can be aimed for. This can make the way from process development to process establishment even harder, since academia or start-up research facilities might not have the possibility to generate these data. Furthermore, bioprocesses involving mammalian cells deal with many critical variables; processes are not only carried out batch wise, but increasingly in fedbatch mode with desired feeding profiles. The use of DoE tools in combination with an appropriate growth model might allow the experimenter to develop and to test fed-batch strategies in silico, before experiments are carried out in the laboratory. In our work, an unstructured model for mammalian cell culture was used for simulation. Kinetic parameters were derived from a small number of shake-flask experiments. The model was tested for data generation on common fed-batch strategies. By means of design of experiments strategies, relevant conditions were selected and experimentally tested. In this way, suitable fed-batch strategies for mammalian cell lines are evaluated in silico before bioreactor experiments are to be performed. This results in a significant reduction in the number of experiments during process development for mammalian cell culture.