Model-Based Optimization of the Medium Refreshment Regime During Neotissue Growth in a Perfusion Bioreactor

Computational models are interesting tools to facilitate the translation from the laboratory to the patient. In regenerative medicine, computer models describing bioprocesses taking place in bioreactor environment can assist in designing process conditions leading to robust and economically viable products. In this study we present a low-cost computational model describing the neotissue (cells + extracellular matrix) growth in a perfusion bioreactor set-up. The neotissue growth is influenced by the geometry of the scaffold, the flow-induced shear stress and a number of metabolic factors. After initial model validation, a Genetic Algorithm optimization technique is used to find the best medium refreshment regime (frequency and percentage of medium replaced) resulting in a maximal amount of neotissue being produced in the scaffold in a 28 days of culture period.