FLAMR · Federated Learning for Antimicrobial Resistance Surveillance

Линиите свързват координатора с партньорите.

Накратко на български

Цел на проекта

FLAMR tackles the global health threat of antimicrobial resistance (AMR) by developing and validating a next-generation, federated reinforcement learning (FRL) system for near real-time surveillance calibrated for ESKAPEE+ pathogens. The project integrates human, veterinary, and environmental AMR datasets, being the first to combine FRL with multimodal diagnostics and community-based governance for AMR surveillance, particularly useful in resource-constrained settings. Its objectives are to (1) develop, deploy, and validate a privacy-by-design FRL architecture for AMR data integration across ≥12 labs in Estonia, Romania, Colombia, and Sri Lanka; (2) strengthen diagnostic capacities for bacteriological and metagenomic surveillance through the examination and sequencing of >400 field samples and the characterization of phage-based alternatives; and (3) co-develop AMR stewardship, governance, and education toolkits to empower local communities and authorities.FLAMR combines advanced AI, metagenomics, and bioinformatics with social science and participatory governance to test whether FRL can outperform conventional surveillance pipelines in accuracy, interpretability, and inclusiveness. Technical leaders design and deploy the FRL architecture and analytical tools, while field and laboratory partners generate and validate AMR datasets under real-world conditions. Governance and SSH partners ensure ethical alignment, cultural adaptation, and social uptake. A core innovation of FLAMR is its transparency-by-design, bidirectional community-driven framework, where centralized data informs stewardship and policy intervention through interactive dashboards and geolocated visualizations. Aligned with the Horizon Europe Health Cluster and the EU One Health Action Plan on AMR, FLAMR embodies open science and interdisciplinary capacity-building, creating scalable, equitable pathways to global AMR resilience and long-term EU leadership in responsible One Health AI innovation.

Оригинален текст от CORDIS (на английски).

Участници

• EESTI MAAULIKOOL · TartuКоординаторЕстония
• Chungnam National University Industry-Academic Collabroration Foundation · DAEJEONЮжна Корея
• JUDETUL ILFOV · BucurestiРумъния
• N-VISION SYSTEMS AND TECHNOLOGIES SL · IGUALADAИспания
• Servicios Especiales de Salud · ManizalesКолумбия
• UNIVERSIDAD DE CALDAS · ManizalezКолумбия
• UNIVERSITATEA DIN BUCURESTI · BucurestiРумъния
• UNIVERSITATEA SPIRU HARET · BucurestiРумъния
• UNIVERSITRY OF PERADENIYA · PeradeniyaШри Ланка
• UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN · DublinИрландия

Връзки

• Виж в CORDIS
• DOI: 10.3030/101299901