Developing biotech faster and cheaper using computational power

In our CLIB webinar “Machine Minds, Bio Solutions: Redefining Bioprocess & Enzyme Engineering” we and more than 140 participants dived into the topic of developing enzymes, processes and products faster using artificial intelligence and machine learning.

Our speakers Victor Guallar from the Barcelona Supercomputing Center, Lukas Pluska from Exazyme, Matthew Thompson form Biomatter and Max Siska from the Forschungszentrum Jülich presented their work and research on the topic: They talked about using virtual data to fill in gaps of experimental data or training an AI-powered large language model like ChatGPT to speak “protein”. They showed how to reduce the need for experiments by the factor one thousand, how to build new-to-nature proteins, even from scratch, by combining generative AI and physics and how to find the right experiment within a multi-dimensional cloud of opportunities to accelerate the development.

In a final discussion with all speakers, we discussed about standardisation of data, computational power needed and how communication between biotechnologists, engineers and data scientist can work.


Most of the participants probably learned as much about AI as the CLIB team did, especially about all the possibilities to use these powerful tools to design biotech processes of the future.

Thank you to all speakers and participants for joining us and to our projects FuturEnzyme and BiodeCCodiNNg for supporting the webinar.