Advancing precision medicine
Revolutionizing Type 2 Diabetes Care
In pursuit of its objectives, dAIbetes aims to achieve personalized prediction of treatment outcomes for patients with type 2 diabetes. This prevalent condition affects 1 in 10 adults globally, with annual expenditures of around 893 billion EUR. The partners will harmonize data from approximately 800,000 type 2 diabetes patients across four cohorts distributed across the globe in a specialized federated database network and use it to train prognostic virtual twin models. After validation, these models will be applied in real-world clinical practice through dedicated software. Ultimately, the results will aid in alleviating the current lack of guidelines for expected treatment outcomes for specific patients. The project seeks to demonstrate that personalized predictions from federated virtual twin models have a prediction error at least 10% lower than population average-based models.
On the whole, dAIbetes is a multidisciplinary consortium of experts in AI, software, privacy, security, and diabetes. The project will create a blueprint to overcome the privacy-big data conflict in cross-national diabetes research and beyond.
Furthermore, the consortium is committed to advancing the frontiers of medical research, ultimately improving patient outcomes and contributing to the global development of precision medicine.
The role of Egnosis
As lead of WP4, Egnosis is responsible for designing, architecture, and developing the virtual twin software platform that orchestrates the data handling- and training-related operational workflows.
We will lead the overall development of the dAIbetes software platform following state-of-the-art industry standards: the software development lifecycle (SDLC) methodology combined with the agile iterative development process.
Using a patient-centric, simplistic front-end app and state-of-the-art APIs, the platform will ensure intuitive data handling based on the harmonized data standards developed and implemented by our project partners.
“What would one say if one is more than happy to have an outstanding and trustworthy partner like Egnosis? They’ve never disappointed us, but more than that, they’ve also been consistently ahead in the field. Maybe exactly this.”
Prof. Dr. Jan Baumbach
dAIbetes Project Coordinator, Director of the Institute for Computational Systems Biology University of Hamburg
Project data
Start date: January 2024
Duration: 5 years
Horizon Europe contribution: € 8,9 million
Egnosis budget: € 902 500
Project coordinator: University of Hamburg (Germany)
Participants: 12 partners from 7 countries
Check it out on Cordis!
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101136305.
