Tech & Innovation in Healthcare

Researchers could identify a new pandemic early in the spread.

Scientists are using digital twins to test different treatment methods for a variety of medical conditions. Since every patient is different, digital twins allow scientists to make models based on the patient’s data, so they can find a precise treatment method for each individual patient.

Read on to discover how healthcare providers can use digital twin technology to treat long-haul COVID-19 symptoms.

Simulate Impossible Scenarios With Digital Twins

What exactly is a digital twin? “Digital twins today are detailed three-dimensional, functioning computer models built to represent the physical size, shape, and behavior of the original,” says Steven Levine, PhD, senior director of Virtual Human Twin at Dassault Systèmes in Boston, Massachusetts.

For years, scientists have used digital twins to guide rockets in space from Earth for NASA, develop commercial airlines, and build innovative products. Now, the technology has advanced into healthcare. “Digital twins are ideal for solving problems that would be impossible, unethical, or simply too expensive to explore in the real world,” Levine adds.

Healthcare professionals and scientists have been tasked with solving quite a large problem in the past two years in the COVID-19 pandemic. With digital twin technology, researchers have an opportunity to find treatment plans that suit a vast population with a multitude of health issues. Luckily, healthcare providers and organizations have an abundance of data gathered through in-hospital visits via lab work and vitals, outpatient clinics, and wearable devices they can use to craft treatment plans and follow-up care.

“As a surgeon-inventor, I see the myriad of patient data points continuously being amassed before, during, and after patients leave the hospital and respond by imagining engineered solutions that harness the data to maximize its diagnostic and therapeutic potential,” says Grace M. Thiong’o, MD, clinical and research fellow in the division of neurosurgery at the Hospital for Sick Children in Toronto, Ontario.

After the data is collected, models have been tested, and the digital twin is built, researchers can run nearly limitless tests to evaluate the possible treatment effects on the patient. Digital twin virtual worlds mirror their physical counterparts, and synchronized models will show any changes almost instantaneously on the virtual counterpart, Dr. Thiong’o adds.

Combat COVID-19 Effects After Recovery

As the COVID-19 pandemic persists, healthcare providers continue to see the effects of the disease in patients even after they’ve recovered from the initial infection. These post-COVID, or long-haul COVID-19, symptoms are found to persist for several weeks or months, even causing damage to body organs, such as lungs, heart, kidneys, and brain.

The world is two years into this pandemic, and yet, researchers are continuing to find new variants, test new treatments, and more. But what if healthcare professionals could develop personalized treatment and care plans depending on the patient’s medical history? By creating a digital (or virtual) twin of the patient, providers can explore new avenues to treatment without affecting the patient.

Turn Data Into Therapy

Scenario: A patient presents to an emergency department (ED) with shortness of breath, fatigue, fever, chills, and a persistent cough. The physician tests them for COVID-19, which returns positive. The patient is stabilized, treated, and released a few days later. Five weeks later, the patient returns to the hospital still experiencing shortness of breath, fatigue, and a persistent cough. The physician diagnoses them with post-COVID symptoms and admits the patient to the hospital. During the patient’s stay, the physician creates a digital twin using the data from the patient’s previous visit, their personal medical history, and their current symptoms. The physician tests different therapies on the digital twin, determining which one will work best for the patient.

During the COVID-19 pandemic, an immense amount of information has been collected. However, the data was collected in a traditional way, so the information is fragmented and doesn’t paint a full picture of the population’s health. Healthcare professionals and scientists have the chance to harness that data for the benefit of post-COVID patients. “With a focused effort, that information is now available to construct effective virtual twins, which can be used to identify the best treatment for those suffering from long COVID,” Levine says.

Initial digital twin models may not be very accurate, but over time the models would become effective and could be used around the world. Through the use of machine learning (ML) algorithms, digital twin models can effectively mine data and have the possibility to provide risk stratification and prognostication as researchers determine the ideal care for a patient. If physicians can use a digital twin model of a patient, they could craft treatment plans for complicated conditions, such as long-haul COVID-19, “sometimes better and faster than a single care physician’s mind could accomplish within a similar timeframe,” Thiong’o says.

Prepare for the Next Pandemic

The COVID-19 pandemic seemingly caught the world off-guard. Could researchers use digital twins to flatten the curve before another virus has a similar effect?

“For a given virus, we can create virtual twins of the virus, the cell, the lungs, the heart, the brain, etc., as well as complete populations and their mobility, allowing us to identify more clearly what is happening early in the spread,” Levine says. Additionally, digital twins can be shared between researchers in countries around the world, so scientists can collaborate and share their expertise.