In recent decades, the use of enzymes in the biotechnological industry has increased significantly. They are biodegradable, possess a high substrate specificity, and function effectively under mild operation conditions (e.g. temperature, pH value, pressure). They are used as alternative catalysts for chemical reactions in various industries, including beverages, food, pharmaceuticals, and cosmetics. Compared to conventional chemical catalysts, the use of enzymes reduces energy consumption, operating costs, and by-product formation.

Enzymes are usually produced through continuous upstream processes (USP). They are then found in complex biosuspensions (i.e. fermentation broths) that additionally contain various impurities, such as salts, medium proteins, cell debris. Isolating the target enzyme from the fermentation broth requires a complex downstream process (DSP) involving numerous separation steps. The large number of unit operations in DSP leads to high costs and energy consumption. Each process step causes product loss which leads to smaller yields. This work proposes an integrated two-step process chain as an alternative to conventional DSP. First, the target enzyme is separated from the biosuspension during a continuous aqueous two-phase flotation (ATPF) step (see Fig. 1 left). In the subsequent ultrafiltration (UF) step (see Fig. 1 right), the enzyme-loaded top phase is further concentrated. The integrated ATPF-UF process enables continuous enzyme separation while significantly reducing process complexity.

Integrated online measurement technology, including electrical conductivity probes and UV/Vis spectroscopy, enables continuous monitoring of critical parameters, such as phase mixing, enzyme concentration, and activity. We thoroughly investigate the influence of key process parameters, such as gas flow rate, volume flows of the top and bottom phases, and transmembrane pressure, to identify optimal operating conditions. These experiments are also necessary to develop stochastic and mechanistic process models capable of reliably predicting the behavior of individual processes. The project's overarching goal is to achieve autonomous, closed-loop control of the entire process chain. Fully autonomous control of the entire process chain requires successful automation of ATPF and UF independently from each other and consideration of their interaction during operation. Robust and autonomous control of the process chain under realistic and challenging conditions is only possible when this interaction is reliably described by suitable process models.

This presentation uses experimental data to show that the proposed process chain results in high yields and enzyme concentrations. Therefore, it is a promising alternative to the complex DSP currently used in industry. Additionally, it introduces initial approaches to modeling the two individual unit operations, as well as the entire process chain. This lays the foundation for developing a model-predictive control scheme that can ultimately enable autonomous operation of the entire process chain.