Imagine a smart health assistant that looks at your lifestyle and genetics to tell you exactly how to avoid colon cancer. It's like a GPS for your health that helps doctors give you a personalized plan instead of a one-size-fits-all approach. The goal is to catch risks early and change habits before the disease even starts.
Colorectal cancer rates are rising due to poor health behaviors, especially in low-income groups. Current prevention programs often fail because they aren't personalized and don't address the specific social or economic barriers people face.
A technological ecosystem featuring trustworthy AI for personalized cancer prevention recommendations and cost-benefit financial models for health strategies.
If you are a software developer dealing with low user engagement in screening tools — this project developed a trustworthy AI ecosystem that provides personalized recommendations to shift user behavior. This increases the effectiveness of primary prevention services.
If you are a clinic owner dealing with inefficient patient stratification — this project developed a decision support system using multi-omics and data analytics. This allows for more precise risk-based screening and better resource allocation.
If you are an insurer dealing with high long-term costs of cancer treatment — this project developed cost-benefit models for prevention programmes. This helps in designing affordable financial schemes that reduce cancer incidence.
Based on available project data, the project investigates cost-effectiveness, affordability, and cost-benefit parameters to create financial models that balance costs and generate demand.
The project includes 3 Large-scale Intervention Pilots (LIPs) across 5 EU member states, indicating a clear path toward industrial scaling.
Based on available project data, specific licensing terms are not listed, but the project focuses on creating a technological ecosystem for integration into national health strategies.
Yes, the technological ecosystem is built on privacy-preserving principles and trustworthy AI to ensure secure delivery of interventions.
The project runs from 2023-06-01 to 2026-11-30, with validation occurring through Laboratory Integration Tests and Large-scale Intervention Pilots.
The consortium is highly diversified with 29 partners across 10 countries. It shows a strong commercial orientation with an industry ratio of 38% (11 industry partners, including 8 SMEs), balancing academic research from 3 universities and 6 research organizations with 9 other entities. This mix suggests a high capacity for translating research into market-ready health tools.
Contact the National Centre for Research and Technological Development (REC) in Greece.
Contact SciTransfer to connect with the ONCODIR consortium for pilot integration.
