Influence of heterogeneities on bioprocess performance : an empirical study on scale - up predictions

Abstract

Bioprocesses are often thought to be similarly to chemical processes, but they contain living cells. Different types of cells, namely eukaryotic and prokaryotic microorganisms, react differently to certain changes in their environment, depending on their growth behaviour and metabolic complexity. Therefore, the reproduction and the technology transfer are often cumbersome and difficult. A varying environment often affects the final performance in cellular growth or product formation. It is of great interest to industry and academia to ease these problems boosted by the increase of deep cellular knowledge and technological advance. Especially, the scale-up process is often hampered by the formation of gradients in the mixing regime of larger scales. The evolving uneven distribution of substrate, pH, oxygen and many more can cause metabolic burden for cells, which then, can cause a decrease in performance. Over the years, researchers focussed their interest more and more towards the understanding of the source and effects of inhomogeneous environments in bioreactors. Computational fluid dynamic (CFD) simulations have shown their usability to predict the gradient formation in liquids. It is of great interest to predict the performance

ain large scale bioreactors efficiently in terms of time and costs. Moreover, a tool or method to direct the performance of a certain bioreactor towards its maximum would be of great use for industry and academia. In the herein presented work, an approach towards this step is presented. Previous research on a 60 L pilot-bioreactor stated a possible tool to predict the performance of Escherichia coli fermentations upon the use of CFD simulations. Following up this work, we tried to strengthen the use of this tool by extrapolating its use to other organisms. During our proceeding, information came to light that changed the initial goal and shifted it towards a correction of the previous work and a manifestation of the used 60 L pilot-bioreactor as a robust and trustworthy tool to conduct a variety of processes. Moreover, similar process performances were found between bioreactors varying by a scale ratio of 1 to 250 in their working volume by using closed loop soft-sensors. This will surely boost research at our institute by making it easily possible to generate controlled processes and conduct studies in varying scales, leading to new knowledge and high quantities of biomass and product, due to process optimization.