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OUTBreak AI-driven Detection: Enhancing MALDI-TOF outbreak detection with multimodal AI integrating epidemiological and genomic data

Objective

Hospital-acquired infections (HAIs) from resistant and hypervirulent bacteria—such as Methicillin-resistant Staphylococcus aureus, Vancomycin-resistant Enterococcus faecium, Carbapenemase-producing Pseudomonas aeruginosa, Carbapenemase-producing Acinetobacter baumannii, and Clostridioides difficile—pose a growing threat to patient safety worldwide. Outbreaks often go undetected until severe harm occurs. While whole genome sequencing (WGS) is the gold standard for outbreak tracing, it is costly, slow and not globally accessible. MALDI-TOF mass spectrometry, in contrast, is rapid and widely used, but its outbreak detection potential remains unexploited.

The OUTBReak AI-driven Detection (OUTBRAID) project will transform hospital outbreak surveillance by leveraging an unprecedented international dataset—over 1.2 million MALDI-TOF spectra already collected at the IMM Zurich, plus new contributions from 9 countries across Europe, Asia, and Australia, including Low and Median Income Countries (LMICs), each providing at least 100 samples per pathogen for rigorous, external validation.

OUTBRAID will develop two breakthrough approaches: (1) diffusion models to generate synthetic MALDI-TOF spectra, ensuring robust, cross-center performance; and (2) multimodal machine learning that combines MALDI-TOF, epidemiological metadata, and WGS to enable automated, high-resolution cluster detection. These models will be benchmarked not only at species level but also at sequence type (ST), cgMLST, and single-nucleotide polymorphism (SNP) resolution—pushing MALDI-TOF as close as possible to the granularity of WGS.

All data, models, and code will be open access. OUTBRAID’s participation in workshops and training will reach and train 150+ scientists and clinicians (e.g. ESCMID), ensuring broad impact. By braiding together international data streams and AI, OUTBRAID aims to deliver scalable tools for early outbreak detection, supporting hospitals and public health globally.

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Topic(s)

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSITAT ZURICH
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 307 958,88
Address
RAMISTRASSE 71
8006 Zurich
Switzerland

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Region
Schweiz/Suisse/Svizzera Zürich Zürich
Activity type
Higher or Secondary Education Establishments
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Total cost

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Partners (1)

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