The IngredientIA Project combines artificial intelligence, computational modelling and experimental micro-scale digestion systems to understand how food ingredients interact with the gut microbiota and to support the development of more effective and personalised foods.
Combining artificial intelligence, computational modelling and micro-scale digestive simulation, the IngredientIA Project, coordinated by OmniumAI – a spin-off from the University of Minho created from the Centre for Biological Engineering (CEB) – is using data science to drive the creation of more effective and personalised foods. The ultimate aim is to contribute to the prevention of metabolic diseases and to improve gastrointestinal wellbeing, whilst also promoting a more competitive and environmentally responsible food industry.
In addition to the CEB, the initiative also brings together the company NIUM and the International Iberian Nanotechnology Laboratory (INL), combining expertise in food science, microbiology and experimental technologies to analyse the interaction between ingredients, gut microbiota and digestive processes.
In this research, artificial intelligence is used to integrate large volumes of data on ingredients and the microbiota, enabling the identification of relationships between ingredients and the microbiota that would not be detectable by conventional methods. In this way, it is possible, for example, to predict synergistic or antagonistic effects between food components, as well as the metabolisation of specific compounds by the gut. Understanding these processes is essential, as the effect of a food depends not only on its chemical composition, but also on how it is transformed during digestion and metabolised by the gut microbiota.
OmniumAI’s CibusAI platform will be expanded to incorporate data on interactions between ingredients and the gut microbiota, in order to generate predictive analyses. These algorithms, in turn, support the personalised reformulation of foods, anticipating results that could often only be obtained through a large number of laboratory tests.
Meanwhile, the experimental MicroDiGut system, developed by NIUM, simulates the entire human digestive process on a micro-scale, from the mouth to the colon. This approach makes it possible to validate the predictions of computational modelling using minimal samples, reduce costs and experimentation time, and maintain strict control over parameters such as pH, temperature and microbiological composition.
By exploring new technologies for the encapsulation and stabilisation of bioactive compounds, the project aims to increase the ingredients’ resistance to the digestive process and optimise their efficacy. Interoperability with scientific databases and the development of specific APIs reinforce the platform’s technological capabilities, enabling the results to be integrated and applied in industrial contexts.
The CEB plays a central role in experimental validation, using macro-scale dynamic digestion models to compare and calibrate the performance of MicroDiGut. Furthermore, it leads the development of genome-scale metabolic models of gut microbiota organisms, which are essential for understanding how microorganisms metabolise different ingredients.
Focused on developing technological solutions with concrete industrial applications and the potential for commercialisation in the European and international markets, IngredientIA paves the way for the creation of more effective functional foods, whilst also contributing to the growth and development of the sector.
