By Dana Yamashita
Imagine having to prick your finger multiple times a day to test your blood sugar. For over 1 million people in the United States with Type I diabetes, that has been the case, until relatively recently when continuous glucose monitors (CGM) were created.
Type I diabetes, also known as insulin-dependent or juvenile diabetes, is usually diagnosed in children or young adults but can develop at any age. In Type I diabetes, the pancreas does not make insulin — or makes very little insulin — causing blood sugar to build up in the bloodstream. The high blood sugar damages the body and causes many of the symptoms and complications of diabetes.
Now, CGMs can track a person’s blood sugar automatically every five to 15 minutes to help detect trends and patterns to better manage the condition.
A new project funded by JDRF, the leading global organization funding Type 1 diabetes research, and led by Wayne Bequette, Rensselaer professor of chemical and biological engineering, will use artificial intelligence and big data techniques to analyze information gathered from thousands of CGMs and insulin pumps. Researchers will use that information to improve algorithms that control these critical devices.
The data analysis gathered in this research will assist engineers in improving models that predict the effect of insulin and meals on glucose levels, yielding better control of blood sugar levels.
“If we look at hundreds of people we can say, ‘Oh, certain problems occur more often in this age group, this type of population, or with this particular type of sensor,’” Bequette said. “If, for example, you find that it’s more likely that people 8 to 12 years old have these types of irregularities, then you can account for that in your algorithm, and provide more personalized control while reducing burden.”
Still in its early stages, a new project, also funded by JDRF, will support the creation of a smartphone app to help manage CGMs, and will specifically target senior citizens.
Several devices will likely be developed based on the user’s experience and comfort level with technology, visual set-up, types of alerts, and whether or not the information needs to be shared with a caregiver. The objectives in controlling blood glucose may change depending on the patient’s age — the younger the patient, the longer they need to ward off complications associated with diabetes. In older patients, the concern may be that blood sugar doesn’t dip too low, causing fainting and falling.
“Data-driven decisions, combined with technology, help improve quality of life and reduce co-morbidities associated with diabetes,” said Deepak Vashishth, director of the Center for Biotechnology and Interdisciplinary Studies (CBIS) at Rensselaer.
