AI-powered foodome characterization

What is this call about?

The topic funds an Innovation Action to develop AI tools that analyse complex foodomics data and identify, characterise and quantify chemicals in food. It targets consortia that combine industry, academia, start-ups, SMEs and international initiatives.

What does this call fund?

Scope

The topic supports the development and testing of validated AI algorithms that interpret and annotate high-throughput foodomics data, for example from untargeted mass spectrometry or nuclear magnetic resonance. The algorithms should predict or infer the presence and concentration of compounds in food from incomplete data, using innovative approaches such as phylogenetic relationships between species, and help identify analytical methods and potential food safety hazards by similarity to known compounds.

Research network

Proposals should also build a European research and innovation network between Member States and Associated Countries in food exposome research. The network should support the development, standardisation, valorisation and dissemination of the AI results and take account of existing initiatives, such as the Periodic Table of Food Initiative centre at Wageningen University.

Expected outcomes

• An AI tool that speeds up the identification, structural characterisation and quantification of chemicals in food.
• Greater capacity and synergies in foodomics research between academia, research infrastructures and industry.

Technology readiness

Activities are expected to start at TRL 5 and reach TRL 7 by the end of the project.

What are proposals expected to do?

• A multi-actor approach is encouraged.
• Collaboration with international partners and with private companies in the EU and Associated Countries is encouraged.

When is the deadline?

23 September 2027 (322 days)

23 September 2027 (single-stage call).