MEDITWIN: using digital twins to develop tomorrow’s personalized medicine
How can the use of virtual twins improve the quality of care, making healthcare safer and more accessible for all? This is the mission of MEDITWIN, a consortium of 7 Instituts Hospitalo-Universitaires (IHUs) including IHU ICAN, from Nantes University Hospital, Inria, associated startups and Dassault Systèmes, announced on Monday, December 11, 2023 in the presence of French President Emmanuel Macron..
Thanks to personalized virtual twins of organs, metabolism and cancerous tumors, this innovative project will make it possible to diagnose the risk of cardiovascular disease for high-risk patients, and to help specialized physicians choose treatments for effective patient follow-up.
The MEDITWIN initiative will be developed over 5 years, from 2024 to 2029. The partners’ investment in this project will be financially supported by the French government as part of France 2030.
What medical need does MEDITWIN meet?
“Digital twins open up the prospect of a new form of precision and preventive medicine for cardiometabolic diseases, by establishing for each individual his or her future risk of developing cardiovascular disease, based on risk factors such as his or her genomic signature. Such a project requires a change of scale in research, which has now been achieved thanks to the project led by Dassault Systèmes, with all the MEDITWIN partners on board.”
Prof. Stéphane Hatem, General Director of the ICAN IHU and Director of UMR 1166 Cardiovascular and Metabolic Diseases
Cardiometabolic diseases, also known as cardiovascular-metabolic diseases, refer to a group of interconnected disorders affecting the heart and metabolic system. They mainly include: cardiovascular diseases affecting the heart and blood vessels (coronary heart disease, hypertension…) and metabolic disorders (type 2 diabetes, obesity, hypercholesterolemia, steatotic liver disease – MASH-(NASH)).
Cardiovascular disease is the world’s leading cause of death, accounting for almost 18 million deaths every year. In France, they represent the 2nd cause of death in the general population, with almost 150,000 deaths each year, and the 1st cause in women. More than 15 million people are treated in France for disease, cardiovascular risk or diabetes, at an annual cost of over 17 billion euros.
To date, all symptomatic and asymptomatic patients at risk are assessed for cardiovascular risk by their physicians.
The association between certain classic biological markers (classic lipid profile, LDL-cholesterol) and the risk of cardiovascular disease is indisputable. However, to date, the use of these markers in medical practice does not allow for fine stratification of this population.
Without predictive tools, it is difficult to individualize patient follow-up and choose the most appropriate treatments and optimal doses, while reducing the side effects associated with treatment (statins).
Technical advances not yet systematized
Scientific and biomedical research has made significant advances in this field, with plans to integrate other markers based on imaging and Omics data (metagenomics, metabolomics, lipidomics, proteomics).
Advances in imaging techniques, such as thoracic CT scans (large and small arteries), now enable non-invasive, detailed analysis of vascular damage in patients with no known cardiovascular disease.
By revealing the progression, stabilization or regression of the disease and predicting the quality of response to treatment, these new indicators become a concrete means of applying prevention and targeted therapies according to the patient’s profile and biology.
Familial hypercholesterolemia (FH) is a major cause of premature cardiovascular disease, and represents a model of accelerated pathological progression. Following the trajectory of these patients is therefore an opportunity to access risk prediction indicators within a limited timeframe.
Recent data have shown that, even in the case of familial hypercholesterolemia, the use of non-invasive coronary imaging can predict the incidence of cardiovascular events in asymptomatic subjects, with high predictive power over a follow-up of less than 3 years.
However, these techniques are not fully integrated into decision-making algorithms, and their use in clinical practice is not systematized.
Using virtual twins for a better treatment strategy
With this use case for virtual twins, the MEDITWIN consortium’s ambition is to develop a personalized predisposition diagnostic service for cardiovascular disease, and to select the best treatment strategies, while integrating the patient’s environment, such as gut microbiota and nutrition.
The predictions of such twins in terms of trajectories and their improvement could support the practitioner in the management of the patient, and also make more tangible the patient’s future in the absence of intervention in order to improve adherence to treatment. This will make it possible to measure the impact of proposed solutions in terms of reducing the number of patients with cardiovascular events (coronary, cerebrovascular, arterial…).
The benefits will be felt by patients, who will benefit from care tailored to their individual risk and directly linked to the progress of their disease, and by practitioners, who will be able to take advantage of tools for the early identification and management of chronic diseases.
MEDITWIN will therefore enable a digital twin model to be established to monitor the individualized cardiovascular risk of patients with familial hypercholesterolemia, thanks to a selection of relevant biomarkers.
Digital twins will help to clarify the cause-and-effect relationship between micro and macro-circulation in a healthy cardiovascular system, so that we can better understand the pathophysiological mechanisms of aging, hypertension, diabetes and other conditions.
