Twins have long been a source of fascination to people, not only because of their identical DNA, but also their powerful connection and ability to be attuned to each other’s well-being.

But what if each of us had a “digital twin” that could offer some of those same advantages? A synthetic twin that could predict or even prevent illness and help keep us safe and well?

Mohamed Rehman, M.D., chair of the Department of Anesthesia, along with his team of data scientists led by Luis Ahumada, Ph.D., at Johns Hopkins All Children’s Hospital in St. Petersburg, Florida, is convinced this is the future of health care.

“We’re moving from ‘herd medicine,’ or one-size-fits-all, to individualized, precision medicine,” Rehman says.

Rehman, also a professor of anesthesiology, critical care medicine and pediatrics with Johns Hopkins University School of Medicine, is leading the Human Digital Twin Project at Johns Hopkins All Children’s. In multiple studies, researchers have collected real-time physiological data of consenting patients, along with their electronic medical records, lab results and other information. They’ve aggregated the data to create a digital twin of each patient.

The first study, in 2022, focused on children scheduled for spinal fusion surgery. Patients were assigned a personalized, wearable device one month prior to surgery to enable researchers to monitor and collect data such as heart rate, sleep patterns, oxygen saturation and number of steps taken each day. Researchers also gathered information on stress levels.

The combined information helped to form the digital twin — in this study, a baseline for each patient. Data collected in the weeks and months following surgery was compared to the patient’s baseline to help predict recovery patterns.

“A physician may tell a patient they can expect to recover from surgery in four to six weeks,” Rehman says. “But the data we gathered actually showed three different recovery patterns in patients.”

The ability to understand and predict what is “normal” in a particular patient and what is not is powerful medicine. Knowing that a patient will be likely to recover sooner or later than average can help doctors spot problems and prevent medical issues from escalating.

Nineteen-year-old Cooper, now a college student, was one of the patients in the first study. He underwent successful spinal fusion surgery to correct kyphosis (curvature) in his spine. As a Type 1 diabetic, Cooper already had an appreciation for how data and technology improved his ability to manage chronic disease, so he didn’t hesitate when given the opportunity to be in the digital twin study.

Cooper wore the device and responded to emails and phone calls from researchers who were closely following his experience.

“Sometimes when you’re recovering from something, it’s hard to detect day by day that things are getting better,” Cooper says. “But this data gave me lots of insight. I could really see the evolution of things.”

His mother, Susan, could watch the benefit play out for her son in real time.

“There was information on where he was before surgery, where he was right after, and the progress he made over the following few months,” Susan says. “It was motivating for him. Not only did it provide him objective feedback, but also the ability to set goals.”

Digital twin technology not only affords the clinical care team the opportunity to detect and respond to potential problems in patients, but it offers parents more information to work with.

Rehman recalls a patient in a study who did well after surgery, but later, the mother noticed that the child’s heart rate began increasing well above baseline. The child was taken to the Emergency Center and diagnosed with a COVID-related heart condition.

Patients with chronic illnesses such as sickle cell anemia may stand to benefit greatly from emerging digital twin technology. Most sickle cell patients are vulnerable to pain crises due to the nature of the disease. But the illness plays out differently in each patient.

“We know that some may get sick within 12 hours, some within 24 hours and some, 72,” Rehman says. “If we have adequate data as to how each patient gets sick, we can intervene before it becomes a full-blown crisis by developing individualized models.”

Researchers are also analyzing data from a completed study on concussion recovery time and additional studies are either planned or underway.

Because mental health is predicted to be the greatest public health issue by the end of the decade, the well-being of employees is also of increasing concern. One study at Johns Hopkins All Children’s focused on creating a digital twin of 60 consenting employees who worked in the perioperative area of the hospital, monitoring for heart rate, activity, stress levels and sleep patterns. That data is currently being analyzed.

While digital twin technology has been employed for years by NASA, the airline industry, tech companies and various other sectors, its application in health care is relatively new. Despite being in its infancy within this field, digital twin technology exhibits significant promise and tangible outcomes. As its footprint expands, it is poised to become an integral part of our lives.

This fundamental change in the approach to clinical care, coupled with the right algorithms, could ultimately lead to a healthier population.

“Digital twin technology is how we shift the paradigm from treatment to prevention,” Rehman says.