iCARE4CVD is a public-private research collaboration aiming to personalise prevention and treatment of cardiovascular disease. The project is led by Maastricht University and Novo Nordisk and joins 34 leading international partners from civil society, academia and industry.

About us

iCARE4CVD ambition

The iCARE4CVD team is united in the pursuit of improving the healthcare of patients affected CVD. By creating one database gathering data from more than 1 million patients and using artificial intelligence, iCARE4CVD will look for new strategies to shift from a one-size-fits-all approach to personalised care.

iCARE4CVD aims to improve four key areas of current CVD healthcare:

The project will achieve this by:

Collecting large existing patient cohorts

covering patients of all CVD stages - from early risk to established heart failure

Establishing a federated database for sustainable data collection and storage

ensuring private and confidential remote access to data on an individual level

Identifying and determining the value of novel and known biomarkers 

to support early detection, monitoring, and treatment guidance for the entire spectrum of patients

Conducting in-depth qualitative research with patients and other stakeholders

to build a motivational framework for self-care by patients and ensure their needs are incorporated into the outputs of the project

Developing artificial intelligence (AI)-based models to support diagnosis and predict risk and treatment responses

to map the complete patient journey and response to interventions in CVD

Addressing legal and regulatory needs

to fast track the adoption of the new care pathways into the clinical setting

Validating AI-based models prospectively towards precision medicine

enabling the development of personalised care pathways

iCARE4CVD structure

iCARE4CVD approach



Existing evidence and cohorts

WP1 will gather and organise health information from of a wide range of CVD patients. This will include information on medical tests (diagnostic screenings), the presence of other medical conditions (comorbidities), data from fitness trackers and health apps (wearable data) and other measurable indicators of health in the body (biomarkers).

The goal is to organise this information into a large database (in WP2) so it can be used to better understand these health conditions and find the best ways to treat them. This information will be standardised and documented uniformly to ensure other researchers and health professionals can easily access, understand and use it.

In addition, WP1 will lay the foundations for a prospective clinical trial with type 1 diabetes patients, which will be carried later in the project (WP6) to address knowledge gaps about this patient population.

Lead Partners:

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