Modelling and Digital Twins of Bioprocesses

chemical conversion due to (a) moderate process conditions, (b) the possibility to target many different products with a similar setup, and (c) the potential of microbes to digest and metabolize waste streams (such as CO2 from industrial offgas sources).

These promising properties notwithstanding, biochemical processes currently hardly match industrial chemical conversions in terms of yield or scalability. Also, microbial growth and production are hard to control, in particular in the face high feedstock variability conferred by waste streams. The intensification of bioprocesses requires advanced monitoring and control strategies.

Our team in Vienna develops real-time capable computational models of bioprocesses, to predict key objectives such as biomass or product formation, and deploys them as Monitoring Devices, Softsensors or MPC (Model Predictive Control) that are capable of managing prolonged growth or feedstock variability.

Real-time implementations are supported by inline and targeted off (at) line measurements that we develop according to the requirements of the process.

Our Expertise at a glance:

• Development of real-time capable process models • Development of targeted off-line measurement strategies for real-time modelling of complex kinetics • Hybrid process modelling using mechanistic and data-driven approaches (PINN) • Deployment of real-time applications (softsensing, MPC) • Fields of application: Upstream, downstream; biomass, product formation, protein re-folding) • Heading towards: comprehensive models along the process chain, inclusion of circular streams, model tranferability