Des Linden’s heart will be studied like never before with Dassault Systèmes’ Living Heart.
Desiree “Des” Linden is one of the most accomplished female marathoners in American history. She’s a two-time Olympian, finishing 7th in the 2016 Rio Games; winner of the 2018 Boston Marathon; the first woman to run under 3 hours for 50 kilometers; and recently set the U.S. Master’s (over 40) record in the marathon with a time of 2:27:35 at the 2023 Chicago Marathon. Linden has had one of the most illustrious and enduring distance-running careers in American history. The diminutive runner from Michigan has one of the biggest motors in the sport running inside her 5-ft 1-in frame.
Thanks to the power of digital twins, we may be able to quantify how well Linden’s heart works and how differently her cardiovascular system functions compared to the average human. Through a partnership with TCS and Dassault Systèmes, Linden’s heart will be replicated and studied digitally to allow for a more complete understanding of how the body functions at the limits of human performance. Powered by machine learning and data analytics, Linden’s digital twin will open up new avenues for training in the world of long-distance running and could potentially modernize medical treatments.
Digitizing the Heart and Taking Fitness to the Next Level
An MRI of Linden’s heart served as the backbone for what would become a digital twin—a fully electronic replica of her heart and circulatory system. The digital twin, however, is so much more than a basic scan and image on a screen. It is a fully living, computerized simulation of her marathoner’s heart. The twin can receive data and external inputs and, with enough refining through the use of artificial intelligence and machine learning, it can deliver predictions pointing to how the heart might function in certain scenarios. To build this type of model, Linden’s own heart’s patterns, rhythms and daily activity have been collected.
Ultimately, the goal of the digital twin is to be able to run hundreds of simulations and be able to deliver an exact prediction of how the athlete’s heart will function under a very specific set of conditions. For example, how would the heart function be affected if an athlete slept poorly due to travel several days before a marathon? It may be possible to quantitatively evaluate the effectiveness of a set of workouts and daily training with a firmer grasp on the heart’s function and eventually that of other body systems.
Coaching distance runners and the act of running itself remains a very inexact science. Writing a training plan is in some ways an art form that is based on the coach and athlete’s experiences in the sport as a runner. There is no formula to raise a runner’s VO2 max by two points over the course of a 16-week training plan. Experience lends enough understanding for the coach, while repetition and comparison to past performances and workouts often give an athlete a feel for their current fitness levels.
How well an athlete responds to intense mile repeats on the track versus an extended tempo run at a slightly slower pace is entirely driven by their own internal body chemistry and muscle composition. It is very rare for two athletes who have similar peak potential to arrive at that maximal fitness level by following the exact same training plan. Individualized training is required to maximize human performance. With enough refinement, a digital twin will give an athlete a better understanding of exactly why they respond strongly to certain types of workouts while struggling to finish others.
In the same Chicago Marathon where Des Linden became the fastest over-40 runner in American history, Kelvin Kiptum of Kenya was on his way to becoming the fastest man in history on a sanctioned course. The 23-year-old broke the tape in 2:00:35, bettering Eliud Kipchoge’s previous world record by 34 seconds. Kipchoge, of course, is the first and only man to run 26.2 miles in under 2 hours, but he did so with an army of pacers while running on a contained course with perfect conditions. The stage is now set for Kiptum to attempt to run the first true sub-2-hour marathon in an actual race. As he pushes the boundaries of what is humanly possible, a digital twin could become a necessary tool to determine the right time to attempt breaking the boundary.
The Tech Behind the Twin
The digital twin of Des Linden’s heart is part of a larger effort by TCS and Dassault Systèmes to understand how the human heart functions, the Living Heart Project. The Living Heart Project is focused on utilizing simulation to create better models of the heart and develop new treatment strategies and devices. Simulation software is one of Dassault Systèmes’ cornerstone offerings and the SIMULIA portfolio is the environment in which the digital heart lives.
An MRI provided the visual representation and model of Linden’s heart. TCS provided data refinement and expertise in computational models to bring the heart to life. Turning the digital twin into more than a picture on a screen requires a deep understanding of artificial intelligence, simulation, cognitive computing and predictive analytics. This is true of any type of digital twin but is especially true when attempting to develop a model and digital approach to healthcare that could one day include virtual clinical trials of medical devices and treatments. Through its Digital BioTwin initiative, TCS hopes to produce similar models of all human organs.
“TCS is excited to be a part of the Living Heart initiative and to collaborate in creating a pathbreaking digital simulation of the human heart that can enrich our understanding of the cardiac function and provide insights for novel cardiac treatments and new product development for the med-tech and pharma sectors. We believe that our extensive expertise in building digital bio-twins for other organs and body parts positions us well to contribute significantly to this collaborative initiative,” said Vikram Karakoti, Global Head of Life Sciences Business at TCS.
Beyond Roads and Track
Although seeing a 2-hour marathon excites running fans, the long-term value for all of creating digital twins and simulations of the heart is improved medical care and health. For her part, Linden understands this is about more than athletic achievements and appreciates the importance of the study.
“It’s all encompassing. First, I just want to see how it works and be able to show that this is a great concept and more people should have it done. For me, if we can show how training works and avoid things like overtraining, see what workouts and what type of work is giving us the best bang for a buck, in terms of improvement—if those things are able to show through, I think that would be groundbreaking and would really personalize training to a whole different level,” the runner said.
“But beyond that, I turned 40 this year and I just want to be healthy. If there’s tweaks I can make in my lifestyle and we see those as well, I think health and wellness is probably the thing that’s going to extend to everybody else. It’s a small number of people who are looking for tweaks in training; everyone can benefit from health and wellness. So that’s the big thing for me.”
The development of digital twins for healthcare is still in its early stages, but as computing power increases and artificial intelligence improves, this technology could fuel more personalized medical solutions. Medical care now remains a reactionary field—you feel sick, you go to the doctor. The doctor treats you based on their own personal experience and intuition with an approach that is not necessarily based on the patient’s internal body structure and genetics. Heart attacks can occur suddenly and with little warning.
A world where a digital twin of each at-risk person’s heart is created and then monitored continuously using artificial intelligence does not seem like a stretch as technology improves. Expanding beyond heart health is also on the horizon. Digital twins have untapped potential across virtually every industry, but their greatest impact on humanity may yet come in the healthcare field.
