EU project Microb-AI-ome started
Coordinated by Prof. Jan Baumbach, Institute for Computational Systems Biology, Universität Hamburg (DE), project management by tp21.
Duration: 5 years - Start: 01 April 2023 - Total funding: approximately € 6 million.
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-AIome,
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, artificial intelligence, software development, and privacy
protection to close the gap between privacy and big data in international medical research.