Pulmonary arterial hypertension, a cardiovascular disease, affects around 6,500 people in the UK.
Researchers from Imperial College London (ICL), the Alan Turing Institute, the University of Sheffield and the University of Nottingham develop the first-ever ‘digital twin’ heart model for chronically ill NHS pulmonary arterial hypertension (PAH) patients. and test to provide better monitoring and better care.
The CVD-Net project is supported by £8 million in funding from the Engineering and Physical Sciences Research Council and further funding from the National Institute for Health and Care Excellence Imperial Biomedical Research Center.
PAH affects around 6,500 people in the UK and is a life-threatening cardiovascular disease that causes severe shortness of breath, heart failure and recurrent hospitalization.
The team will design and build an accurate virtual copy of a patient’s heart using health data such as medical records, hospital scans, and information from wearable and implantable monitors that are continuously updated with real-time data. We are aiming for
Engineers, clinicians, computational statisticians, and research engineers work together to access data and build digital infrastructure, while working closely with patients, physicians, and stakeholders to improve its usability and accuracy.
Researchers hope that the digital twin heart will help accurately track and assess changes in each patient’s disease progression and response to treatment, allowing for personalized predictions.
Additionally, this project will determine whether the use of digital twin heart models in NHS patient care pathways is feasible, scalable and affordable.
Professor Stephen Niederer, Co-Director of Digital Twins at the Alan Turing Institute and Director of Biomedical Engineering at the National Heart and Lung Institute, commented: You are more likely to have a health problem, or when your medication is working and when it is not. ”
In 2023, the Alan Turing Institute launched its own digital twin initiative, the Turing Research and Innovation Cluster (TRIC-DT), to improve access to emerging digital twin technologies for development and deployment as a national service. .
