Digital Twin: supporting the optimization of bioreactor operation and automation

Description

We want to develop a digital twin supporting the optimization of bioreactor operation and automation. Our approach involves creating a hybrid model while defining and standardizing interfaces between bioprocess automation and the digital twin. Digitalization is progressing continuously, and we aim to become the market leader in the digital transformation of bioreactors. When we engage with potential customers, they cannot predict how their cells will behave in our systems.

Our revolutionary and innovative idea is to develop a digital Twin of our bioreactors, which we can offer to our customers. By doing so they can connect their twins of the biomass growth to our twin, and they can evaluate how their cells will behave in our systems. Therefore, depending on the outcome of the innovation cheque, an Innosuisse project is likely to follow.

For implementing a digital twin, there are different modeling approaches, namely mechanistic, data-driven, and hybrid modeling (Lin et al. 2025). Additionally, hybrid models are scale-independent, allowing knowledge to be transferred vertically and can be applied to scale up processes (Sokolov et al. 2021). Another key challenge in the digitalization of bioprocesses is the integration of soft sensors, digital models, and other advanced technologies. This highlights the need for standardized communication protocols and interfaces to effectively connect a digital twin with bioreactor automation (Mu’azzam et al. 2024).