The approach is newer in medical research but is quickly gaining traction, especially as more health systems adopt AI systems and tools.
The Digital Twin For Personalized Medicine Project at Temple would create virtual representations for ALS patients. They would account for a person’s health history, genetics, social determinants of health and other factors.
The twin also relies on a person’s current medical status, including vital signs and blood work as well as levels of mobility, muscle strength, respiratory function, swallowing capabilities, speech and more.
“So, this virtual representation is unique to their symptoms, including some of their working history, environmental [exposures] and also their medications,” said Huanmei Wu, chair of the Department of Health Services Administration and Policy at Temple University’s Barnett College of Public Health.
Doctors can then simulate different therapies and treatment options through the digital twin’s AI program, which will generate outcome predictions and suggestions. The AI program will be trained on data from a global network of ALS health outcomes databases comprising thousands of people living with or who have lived with the disease.
Consistently updating the digital twin with a patient’s most up-to-date medical information is key to getting real-time, accurate predictions, Wu said. Data can be gathered at regular doctor’s appointments or through wearable technology like smartwatches and biosensors.
“Then the doctor can say, ‘We need to change our plan,’ or ‘We can simulate if this medication still works,’ or ‘How much longer do we need to prepare for the wheelchair or how much longer we need to prepare for the [feeding] tube?’” Wu said. “We can simulate, if we give this medication, then maybe six months later. And if we give something else, potentially we can slow that down.”
Working toward ALS precision medicine and enhanced research
The desire to provide doctors and patients with more accurate tools in predicting and managing ALS has always been there, said Heiman-Patterson. But researchers had to wait until technology caught up in order to launch something like the digital twin project.
In addition to giving people more reliable information about living with ALS, Heiman-Patterson said she hopes that digital twins could also help in clinical trials.
“If I’m somebody with ALS, I know I’m only getting one chance at a clinical trial, because I’m going to be too far progressed, likely, when I’m done with this trial to be enrolled in another,” she said.
But some people – usually 50% – are put in a placebo group that doesn’t get the therapy or experimental medication.
“That’s frustrating to say the least,” Heiman-Patterson said. “So, if we could provide [digital twin] prediction data that is suitable to supplement placebo groups, we would be able to have fewer people in a placebo group.”
The future applications for using this kind of technology and precision-medicine approach could go beyond ALS, said Temple researchers, and apply to other types of neurodegenerative and chronic diseases.
Researchers say it could take another two to six years before the digital twin program is ready for clinical testing, depending on funding. A significant amount of money will be needed to support software development, AI engineers, data analysis, data storage and testing. Project leaders said they are pursuing state and federal funding opportunities, as well as partnerships with philanthropic organizations.
Heiman-Patterson, who has dedicated most of her 40-year career in medicine to studying and caring for people with ALS, remains determined to see this latest project through.
“We have a team here and we have assembled people who are interested and can do the work,” she said. “That’s the first step. And we’re moving forward.”
Kids attend an annual summer camp in New Jersey through Hope Loves Company, a nonprofit that supports children and families impacted by ALS. (Courtesy of Jodi O’Donnell-Ames)