Stephanie Allassonnière, an influential AI and medical researcher, has been immersed in the world of AI for over 15 years. Her career in mathematics and statistics has led to multiple roles in the research world. From co-founding a startup to leading classes as a professor, holding positions in the AI Institute in Paris, PR[AI]RIE, all the way to leading her current research in generative AI at Parisanté, a campus uniting actors in digital health research and innovation.
One of the facets of her current research is on digital twins in healthcare. A tool that could revolutionize prevention, personalized treatments, and overall optimization of the clinical pathway for patients and practitioners.
What’s a Digital Twin?
With many applications across sectors, from design and engineering to modeling products for e-commerce in 3D, digital twins have been growing legs in the tech world since 2017. But how can digital twins be used in healthcare?
“The digital twin is, for me, the future of medicine,” Allassonnière told us. “We are trying to create a digital twin of organs, and eventually a digital twin of the patient, with clinical imaging and genetic data. So this digital twin will help test different drugs, for example, and see which is the better one.”
Her research is part of a private and public consortium between several health institutions called MediTwin. The project aims to create personalized virtual twins for better diagnosis and treatment. In particular, it will enable doctors to simulate future scenarios for a patient.
“It's focused mostly on urgent neurodegenerative diseases and cancers,” Allassonnière added. “So, let’s say your parent has some memory defect. [With the digital twin], we’d have the patient fill out a questionnaire and we’d plug that data in and see in real time a prediction of the outcome of this evolution in 6 months time.”
Dementia treatments are most effective when caught early on. Artificial intelligence in digital twins will be able to help patients act sooner and start personalized preventative treatments before having the first real symptoms.
The Evolution of AI in Medicine
Artificial Intelligence, and more specifically generative AI, has been in the spotlight since OpenAI released its AI tools over a year ago. But Allassonnière has been doing research in the field for over 15 years.
“When I started in the field, it wasn’t actually called AI yet,” she explained. “It was just called generative statistics. So, I did generative statistics in my Ph.D. and continued after working with standard classical statistical models at first and then going to include deep learning models.”
“Before, all the generative models that we were doing were very niche, they were only for medical doctors. And the AI boom came when you had to deal with many, many types of data and GPUs came into play. What changed was that it started to be useful for everybody.”
“What inspires me most about AI in medicine is the fact that we will be able to help people at any moment, from their non-disease stage up to the disease stage.”
The Next Generation
As a woman in a male-dominant research field, Allassonnière wants to urge young women to not listen to the stereotypes around them.
“I come from a discipline where women are very rare. I'm a mathematician,” she admitted. “So, I go to high schools and talk to students and teachers so that they stop [repeating the clichés] that I heard myself as a student.”
“I can only encourage women, and particularly young women, to learn math, learn physics, and learn about computer science, because we need a diversity of viewpoints. Do whatever you want, because all of our ideas together are really important to make things evolve.”
A New Future for Medicine
Stephanie Allassonnière's research and innovative projects in the realm of AI and medicine underline the tremendous potential of digital twins in transforming healthcare. A new era in medicine, where early detection, precise diagnosis, and tailored interventions hold the promise of better outcomes and improved quality of life for patients worldwide.
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