Project description
Preventing type 2 diabetes: wearable technology with physics-informed machine learning
Impaired glucose tolerance, with or without impaired fasting glucose tolerance, is a manifestation of so-called prediabetes that can be reversed without the use of prescription drugs to prevent progression to type 2 diabetes (T2D). Building on patient-specific mathematical models developed within the EU-funded MISSION-T2D project, the Italian SME Spindox Labs will develop a prototype tool for the real-time prediction of prediabetic risk through the EU-funded PRAESIIDIUM project. The models simulate metabolism, pancreas hormone production, microbiome metabolites, the inflammatory process and immune system response. The novel prediction algorithm, based on physics-informed machine learning combining the model with real-life data, will be piloted harnessing wearable sensors. Success could prevent the development of T2D in hundreds of millions worldwide.
Objective
The incidence of undiagnosed diabetes accounts for 36% European adults, while 541M adults worldwide have Impaired Glucose Tolerance (IGT), an important risk factor for further T2D development. Both IGT and/or Impaired Fasting Glucose (IFG) are intermediate glucose mishandling (i.e. intermediate conditions in the healthy-T2D transition) and are manifestations of the so-called prediabetes condition. Prediabetes itself is not an extensively studied condition compared to the overt T2D, but it is also a condition that can be reversed without the prescription usage to not proceed into T2D. The aim of our project is to develop a prototype tool for the real-time prediction of the prediabetic risk based on a series of patient-specific mathematical models (firstly developed during the FP7 MISSION-T2D project) that simulate metabolism, pancreas hormone production, microbiome metabolites, inflammatory process and immune system response. The prediction algorithm will be based on a physics-informed machine learning approach. A rich dataset of real-life data will be combined with a mathematical model to overcome the limits of a black-box ML approach, while reducing the computational time for simulating the solutions of a heavy mathematical models and improving its prediction performances.We will collect the necessary training data (e.g. diet questionnaire, physical activity, blood metabolites and microbiome) from already existing clinical studies (used as retrospective trials) which are representative of the real-life scenarios of a prediabetes/diabetes risk insurgence in adulthood (20-80y): family history, Metabolic Syndrome, Liver disease and obesity. A newly dedicated multicentric pilot prospective observational study will be also performed, during which we will also equip the participants with wearable sensors (e.g. glucose monitoring, bioimpedance, heart rate, accelerometer).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- humanities history and archaeology history
- medical and health sciences clinical medicine endocrinology diabetes
- medical and health sciences health sciences nutrition obesity
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.2.1 - Health
MAIN PROGRAMME
See all projects funded under this programme -
HORIZON.2.1.1 - Health throughout the Life Course
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-RIA - HORIZON Research and Innovation Actions
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-HLTH-2022-STAYHLTH-02
See all projects funded under this callCoordinator
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.
38123 Trento
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.