Design of enzymatic cascade reactors through multi-objective dynamic optimization

Multi-enzymatic cascade reactions have gathered a lot of interest lately because of their potential for sustainable production of chemicals. In this paper, model-based, multi-objective, dynamic optimization is applied to the design of an enzymatic cascade reactor that produces α-ketoglutarate. Pareto-optimal process schedules, which are best compromises between space-time yield, enzyme consumption and cofactor consumption, are determined and visualized. Depending on the importance of the individual objectives, the optimal process schedules vary. It is demonstrated, that multi-objective optimization is a valuable tool for the development of enzymatic cascades. It provides decision support for making further experiments, finding bottlenecks in the cascade, and choosing an optimal process schedule for the production.