Imagine having a giant, global map that tracks how different versions of a virus change and how people react to them. This project uses AI to spot patterns in thousands of patients and students to see which vaccines work best and how to keep schools open safely. It is like a high-tech early warning system for future outbreaks.
Healthcare providers and policymakers struggle to predict how new viral variants will affect patient outcomes and school safety, leading to inefficient treatment and unnecessary closures.
A centralized data collection platform, a Virtual Biobank of 12,097 samples, a library of 72 viral variants, and AI models for analyzing complex viral interactions.
If you are a vaccine developer dealing with viral mutations and vaccine escape — this project developed a library of 72 live viral variants and data on 12,097 biological samples that helps refine cross-immunization patterns.
If you are an analytics firm dealing with complex patient data interactions — this project developed an AI-powered platform that processed data from 49,280 hospitalized patients to identify clinical outcomes.
If you are a school operator dealing with infection spread and closure risks — this project developed containment and prevention strategies tested across 437 school classes to optimize safety measures.
Based on available project data, no specific pricing or cost structure is mentioned; the project is funded by HORIZON-RIA.
The project has already demonstrated scale by enrolling 49,280 patients and 7,886 individuals in schools across 10 countries and 4 continents.
Based on available project data, specific licensing terms are not provided, though data is available under approval procedures and regulatory constraints.
The project uses a centralized data collection platform with standardized data to ensure compatibility with research and clinical guidelines.
The project period runs from 2021-10-14 to 2026-10-13, with significant data already collected as of October 2025.
The consortium is research-heavy with 11 universities and 3 research institutes, but it maintains a 15% industry ratio with 3 industrial partners and 1 SME. This balance suggests a strong focus on scientific validation and data generation, coordinated by EURESIST NETWORK GEIE, with enough industry presence to ensure the results are applicable to real-world health sectors.
Contact EURESIST NETWORK GEIE in Italy
Contact us to explore licensing opportunities for the AI-driven viral variant analysis tools.
