📋 Tender Overview
Federated Artificial Intelligence For Privacy-Preserving International Stratification Of Colorectal Cancer Patients
New Screening Approach To Address Colorectal Cancercolorectal Cancer (Crc) Poses A Significant Health And Economic Challenge In The Eu, Costing Eur 20 Billion Annually. Colonoscopies Are The Standard Method For Detection And A Faecal Immunological Test (Fit) Is Commonly Used To Assess The Need For This Procedure. The Eu-Funded Microb-Ai-Ome Project Aims To Improve Crc Screening By Using Ai And Metagenomic Microbiome Data. Researchers Seek To Increase The Precision For Predicting The Need For Colonoscopies By 20 % Compared To The Traditional Fit. With Data From Over 5,000 Individuals And A Projected 100,000 By 2026, Microb-Ai-Ome Aims To Advance Precision Medicine In Crc Detection And Treatment While Preserving Patient Privacy Using Cutting-Edge Privacy-Preserving Ai Technology That Keeps Patient Data Within Secure Healthcare Provider Networks.
Funded Under
Health
Total Cost
€ 5 996 818,75
Eu Contribution
€ 5 996 818,75
Coordinated By
Universitaet Hamburg
Germany
Start Date
1 April 2023
End Date
31 March 2028
Objective
In the EU, 1 in 35 women and 1 in 23 men will be diagnosed with colorectal cancer (CRC) in their life span (ca. 340,000 cases and 156,000 deaths in 2020) causing an annual economic burden of ca. 20 billion EUR. Identifying CRC early enables better treatment options. Screening usually entails a quantitative faecal immunological test (FIT) to predict the need of colonoscopy for the detection of colorectal lesions, an expensive and invasive procedure. We aim to predict this need with specificity increased by >20 percentage points by using metagenomic microbiomes. We hypothesise that computational microbiome profiles extracted using artificial intelligence (Al) technology will allow for optimised personal therapy stratification. However, clinicians do not have access to broad microbiome data. With Microb-AI-ome, we will develop a novel kind of computational stratification technology to enable microbiome-enhanced precision medicine of CRC. Metagenomic microbiome data to date is distributed over many national registries, and privacy regulations are hindering its effective integration. With Microb-AI-ome, we will overcome this barrier by establishing the first privacy-preserving federated big data network in CRC research. We will integrate isolated, national databases into one international federated database network - rather than a cloud - covering metagenomes for over 5,000 individuals screened for CRC, and an expected total of 100,000 by 2026. Microb-AI-ome ensures that no sensitive patient data will leave the safe harbours of the local databases while still allowing for the classification of clinical CRC phenotypes, which we will demonstrate in clinical practice allowing regulatory bodies to adopt evidence-based guidelines. Our consortium combines expertise in CRC and its treatment, microbiomics, artif
