Start date
2026
End date
2030
Coordinator
Esther Pueyo (IP coordinador: Pablo Lamata, King’s College London)
Funding agency
European Commission
Cardiovascular diseases have a huge impact on society in terms of mortality, morbidity and healthcare costs, being responsible for 1.9 million deaths in the EU annually with a total associated cost of €169 billion. Improving healthcare in a period of aging population and tightening financial constraints mandates a shift towards improving efficiency and efficacy through preventive and personalised management of disease.
Recent scientific progress is creating an unprecedented ability to support human reasoning and decision-making: we can now use in silico (i.e. in the computer) models to probe what cannot be measured and simulate response to therapy before it is given.
Additionally, artificial intelligence allows learning and extracting hidden patterns from large repositories of clinical data. Combining these two capabilities is the pathway towards precision cardiology, the vision of the Digital Twin in cardiovascular medicine wherein the computational avatar of each patient informs the identification and stratification of early risks, increases the accuracy of diagnosis, and steers the design of the optimal therapeutic strategy.
The complexity of our healthcare systems, the intricate mechanisms of cardiac pathophysiology, the societal, ethical, and regulatory barriers to the adoption of new technologies, and the intrinsic difficulties in developing trustworthy computational solutions, are some of the challenges that need to be tackled to fulfil this vision. CDTnet will address these challenges by training ten innovation leaders to develop practical and effective solutions, building bridges between disciplines (medicine, computer science, engineering and sociology) and sectors (academic, clinic, industrial and regulatory), to realise the potential of the Digital Twin in cardiovascular medicine.