DT4PH – Digital Twins for Personalized Healthcare aims at using individual-specific computational models for various medical applications, from prevention, diagnosis, and treatment of diseases, to optimisation, selection, and personalisation of interventions.
The digital twins also play a role in medical product development: they can help reduce development costs and time-to-market, while also limiting animal testing. The levels of safety and effectiveness of therapeutic strategies remain high, and could be improved for rare and pediatric diseases.
A digital twin is built on knowledge derived from biomedical research and can be further supplemented with clinical data.
It allows to offer patient-specific tools to answer therapeutic questions, ranging from discovering new therapies to predicting the effects of proposed therapeutic interventions and optimising care delivery.
Digital twins rely on in silico technologies, ranging from purely data-driven technologies such as artificial intelligence (AI) at one end, to computational models that provide a mathematical translation of the mechanisms of biological processes, at the other end.
In healthcare, we often have an insufficient quantity or quality of data to rely on a purely data-driven approach. However, there is often also a lack of comprehensive biological knowledge to create predictive individualised models. Therefore, we rely on a combination of different in silico technologies (including AI) to enhance the reliability of the models and to provide the patient or healthcare provider with the best possible answers.
DT4PH has a duration of 36 months from 2023 to 2026, during which the consortium will work on:
- five technical proof-of-concept sub-projects
- the implementation of an educational curriculum
- the ecosystem expansion
- a translational pathway
This project positions Belgium internationally as one of the leading EU27 states in digital healthcare and enables the sustainable anchoring of digital twins for personalised healthcare as a core part of national and regional innovative health policy.