AI ‘digital twins’ are revolutionizing cardiac care but will they work for women?
Sumesh Sasidharan of the Faculty of Medicine at Aix-Marseille Université explores how medtech revolution may not affect all patients equally.
Digital twin technology powered by AI it can change the way doctors understand and treat Heart disease. But if the medical data used to build these virtual models ignores the biological differences between women and men, the promise of truly personalized medicine may remain incomplete.
Artificial intelligence is beginning to reshape the way doctors study and treat heart disease. One of the most ambitious ideas is a “digital twin”: a computer model built from a patient’s medical data that allows researchers to simulate how a disease might develop and how treatment might work.
In cardiology, these models combine medical images, clinical records and biological data to create a virtual version of the heart. In the future, doctors may test treatment strategies on this digital model before applying them to a patient.
But an important scientific question arises: What if the medical data used to create these types of ornaments are missing important biological differences between women and men?
As digital health technologies approach clinical practice, ensuring that these tools reflect the full diversity of human biology is increasingly important.
Ours research at the University of Aix Marseille on patient-specific computer models of inflammatory heart disease (MYOCAR3 funded by Civis Alliance)we are beginning to see how differences in immune responses between women and men can influence how these diseases develop and how they may appear in future digital models.
The promise of digital twins in cardiovascular medicine
Digital twins are attracting increasing attention across Europe as a way to advance precision medicine.
Instead of treating patients based on average responses seen in the general population, researchers hope to develop personalized models that capture the unique biological characteristics of each individual. Several European initiatives are exploring this approach.
I The European Virtual Human Twin Initiative (VHT)supported by the European Commission, aims to accelerate the development of dual digital technologies for healthcare. Other projects, such as SimCardioTestfocus on developing patient-specific cardiovascular models to improve diagnosis and treatment planning.
These efforts bring together engineers, doctors and data scientists to better understand complex heart diseases. But the success of these models depends very much on one important factor: the quality and representativeness of the data used to build them.
When medical data fails to represent everyone
Over the past decade, researchers have increasingly recognized that biomedical research has sometimes taken male biology for granted.
A highly cited analysis published in Nature reported that male animals historically they outnumbered women by about five to one in most preclinical studies.
In heart medicinethis inequality is important.
Heart disease is still the leading cause of death worldwidecausing nearly 18 million deaths each year, according to the World Health Organization.
However Heart disease does not affect women and men equally. Symptoms, disease mechanisms and responses to treatment may vary.
Inflammatory heart disease is a striking example. Myocarditisinflammation of the heart muscle, can occur after viral infection and, in rare cases, after vaccination.
Global estimates suggest that myocarditis affects approximately 1.8 million people each year and occurs two to four times more often in men than in women, especially among the elderly.
Research published in journals such as Circulation suggests that these differences may be related to differences in immune responses, hormonal influences and the biology of heart tissue.
For scientists creating digital heart models, this raises an important question: if the datasets do not fully capture these biological differences, can digital twins accurately reproduce how the disease behaves in different patients?
From sex differences to gender-sensitive medicine
These concerns are part of a broader shift in biomedical research toward what is known as sexuality and gender-sensitive medicine.
This emerging field recognizes that both biological and social gender factors influence health, disease progression and responses to treatment.
Researchers are increasingly working to integrate these dimensions into medical research, clinical practice and health care education.
For example, i University Hospital Zurich Heart Centerconducted consultations dedicated to gender-sensitive cardiology. Researchers analyze international data sets, identifying patterns across large patient cohorts and generating new clinical data to better understand how gender and sex influence heart disease.
At the same time, European scientific cooperation is working to strengthen how gender differences are considered in research.
I European Initiative COST Action EU-SABV the first European-wide effort focused on developing the method “sex as a biological variable” integrated into biomedical research, which helps to ensure that studies produce findings that are both robust and appropriate for a diverse population of patients.
Together, these efforts aim to produce better data sets, an important basis for reliability digital health technology.
Building better digital medicine
Digital twins represent one of the most exciting frontiers in cardiology. In the future, these models could allow doctors to simulate the progression of the disease, evaluate potential treatments and tailor treatments for each patient.
But the promise of digital medicine ultimately depends on the data that shapes these models.
If that data fails to show biological differences between women and men, even the most advanced algorithms may miss part of the picture.
Ensuring that digital twins reflect the full diversity of human biology will, therefore, be important. Only then can this technology fulfill its promise of truly personalized medicine, not for the “typical” patient, but for every patient.
Sumesh Sasidharan
Sumesh Sasidharan is a biomedical engineer and senior researcher at Aix-Marseille University and CIVIS3i Laureate, sponsored by the European Union. He is ranked among the top candidates worldwide and is the first Indian researcher to receive this prestigious fellowship. His research focuses on developing patient-specific computer models and digital twin structures for inflammatory heart diseases, with an emphasis on acute myocarditis and immune-mediated cardiotoxicity.
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