AI-powered foodome characterization

investigación innovación I+D+i desarrollo tecnológico europeo. HORIZON Innovation Actions Expected Outcome: Project results are expected to contribute to all the following expected outcomes: an Artificial Intelligence (AI) tool able to accelerate the analysis of complex foodomics data to speed up the identification, structural characterisation, and quantification of chemicals present in food; improving capacity and synergies in foodomics research between academia, research infrastructures and industry. Scope: Through food and beverages, the population is exposed to an immense variety of chemicals (as contaminants and as ingredients). The “foodome” is the complete set of compounds present in a food sample at a given time; it includes both endogenous biomolecules (produced through a species' metabolic processes) and exogenous compounds (natural and synthetic substances from production, processing, handling, and packaging). The current knowledge is largely confined to a narrow set of approximately 150 food components catalogued by traditional databases. These components represent only a very small fraction of the total chemical complexity present in foods, while thousands (>100,000) of compounds and contaminants remain largely unquantified and underexplored. Understanding