Project objectives
FLAMR combines advanced AI, metagenomics and bioinformatics with social science and participatory governance.
Develop, deploy and validate a privacy-by-design federated reinforcement learning architecture for antimicrobial resistance data integration across at least 12 laboratories in Estonia, Romania, Colombia and Sri Lanka.
The architecture will support secure, collaborative analysis without requiring participating laboratories to transfer their raw sensitive data.
Strengthen diagnostic capacities for bacteriological and metagenomic surveillance through the examination and sequencing of more than 400 field samples and the characterisation of phage-based alternatives.
Field, laboratory, metagenomic and bioinformatics work will generate robust evidence for near real-time AMR surveillance in diverse settings.
Co-develop antimicrobial resistance stewardship, governance and education toolkits to empower local communities and public authorities.
Participatory research will connect scientific evidence with locally relevant education, community engagement and policy action.
Expected direction