Imagine your gut bacteria as a garden that helps manage your blood sugar. When the garden becomes overgrown with weeds, it can lead to diabetes. This project creates a special 'fertilizer' using insects fed with microalgae to fix the garden and uses AI to predict which food works best for each person.
Type 2 diabetes is rising globally, but current nutritional interventions often fail because people respond differently based on their unique gut bacteria. There is a lack of efficient tools to test and predict how specific novel foods will affect an individual's insulin resistance.
An AI-based prediction application and advanced ex-vivo platforms (organ-on-a-chip) that simulate insulin resistance. They also developed optimized insect-based flours and oils enriched with microalgae.
If you are a supplement manufacturer dealing with the rise of insulin resistance — this project developed insect-derived nutrients boosted by microalgae that promote a healthy microbiome. This allows for the creation of targeted dietary products to prevent the progression of Type 2 Diabetes.
If you are an insect protein producer dealing with inconsistent nutritional quality — this project developed a method using microalgae feeding rates of 12-15% to optimize the health profile of A. domesticus. This ensures the final flour and oils have higher antioxidant capacity and health-promoting properties.
If you are a digital health company dealing with the high variance in how people respond to diets — this project developed an AI-based application to predict individual responses to nutritional interventions. This enables a personalized approach to managing metabolic health.
Based on available project data, specific cost or pricing information for the nutrients or AI application is not provided.
The project involves industry partners and SMEs like NUTRINSECT and CCMAR focusing on biomass production and flour analysis, suggesting a path toward scaling, though specific industrial capacity is not detailed.
Based on available project data, there are no specific details regarding patents or licensing agreements provided in the summary.
The project period runs from 2024-10-01 to 2028-09-30, indicating that final results and AI validation will be available toward the end of 2028.
The AI acts as a predictive tool using project data to determine which specific nutritional interventions will work for a given individual's metabolic profile.
The consortium is well-balanced for a translation project, consisting of 6 partners across 3 countries (ES, IT, PT). With a 33% industry ratio including 2 SMEs, the project blends academic research from 1 university and 3 research centers with commercial application expertise, ensuring that the lab-grown organ-on-a-chip and AI models are aligned with food industry production needs.
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