Imagine your gut is like a filter; when it gets leaky, toxins leak into your blood and trigger inflammation in your joints. This research finds the specific biological markers of that leak to predict who will develop arthritis. It's like finding a warning light on a dashboard before the engine actually breaks down.
Current arthritis treatments only address symptoms and have severe side effects because the exact causes are unknown. This leads to a massive economic burden of 240 billion euros per year in Europe.
An AI-informed rheumatic disease prediction tool and a set of validated biomarkers for gut-joint axis inflammation.
If you are a drug discovery firm dealing with high failure rates in arthritis treatments — this project developed in vitro mechanistic studies and organ-on-chip models that identify new targets for drugs or nutraceuticals to stop endotoxemia.
If you are a software provider dealing with a lack of precision in disease onset prediction — this project developed a machine learning and AI-informed prediction tool that helps clinicians identify patients at risk of transitioning from health to rheumatic disease.
If you are a nutrition company dealing with a lack of clinical evidence for gut-joint products — this project developed proof-of-concept dietary intervention studies (TASTY study) to validate how nutrition reduces disease activity in RA.
Based on available project data, the specific cost or pricing for the AI prediction tool is not provided.
The project uses 12 geographically diverse large cohorts and high-throughput OMICS, suggesting the underlying data is scalable for broad population use.
Based on available project data, there is no specific information regarding the licensing terms or patent status of the identified biomarkers.
The project period runs from 2023-01-01 to 2026-12-31, indicating the tool and targets are currently in development and testing phases.
The tool is designed for use by clinicians to predict the health-to-disease transition and severity of rheumatic diseases to assist in personalized intervention choices.
The consortium is well-balanced for translation, consisting of 14 partners across 8 countries. With a 21% industry ratio (3 industrial partners) and a strong academic base (5 universities, 5 research institutes), the project bridges the gap between high-throughput OMICS research and commercial AI application.
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Contact us to explore licensing opportunities for the AI prediction tool or biomarker data.
