Improving Glucose Monitoring for Patients With Diabetes

Years ago, while I was a resident physician, I had the opportunity to attend a camp for children with diabetes. For one week I, along with a team of nurses, dietitians and other experienced adults as well as a pediatric endocrinologist, taught these children about their disease and monitored their health virtually every minute of the day—hiking and swimming along side them and even staying in the cabins. Despite this, I saw numerous hypoglycemic events, one actually leading to a prolonged seizure. Obviously, much has changed in the past 40 years regarding management of type 1 diabetes; but, strikingly, there remain few effective solutions for preventing hypoglycemia.

Hundreds of millions of times each year, Americans will inject a dose of insulin, any one of which may cause hypoglycemia, causing more than a quarter of a million ER visits each year. This is one of the greatest fears of those using this lifesaving drug.

There are ~25 billion self-administered blood glucose monitoring tests performed annually worldwide. These readings identify when blood glucose levels are in or out of range for people with diabetes. Otherwise, this enormous source of information remains significantly underutilized. The majority of diabetes management software applications act as data stores or logs that offer only basic charts and statistics.

People with diabetes and their clinicians do not have time to navigate through all this data, and few have the clinical acumen to be able to analyze this data to answer important diabetes management questions.

InSpark, a small company formed under the guidance of Dr. Boris Kovatchev, a mathematician, statistician, author of over 120 peer-reviewed publications and holder of over 98 patents (both granted and pending) plans to change all of this.

InSpark uses advanced pattern recognition technology to identify important patterns and periods of risk, and can do so when people are making diabetes management decisions, like when they are testing. The foundational elements of InSpark’s pattern recognition technologies have been licensed from the University of Virginia (UVA) Licensing and Ventures Group. UVA scientists are worldwide leaders in blood glucose analysis and algorithm development, and the technologies under license have been in development for more than 10 years.

InSpark has spent 3 years adopting the system, improving and validating the algorithms, then translating the algorithms into an easy-to-use mobile software ecosystem, and testing this software in the hands of users. Now InSpark is launching it’s lead product based on this technology, called Vigilant^TM.

Vigilant is a smartphone-based application (iOS and Android) intended for people who take multiple daily injections of insulin or who use insulin pumps. This includes people with type 1 or type 2 diabetes. It acts like an intelligent notification system, alerting people to risk when they test or when they are on the go. More specifically, Vigilant can inform users:

• when they may be at risk of a severe hypoglycemic episode in the next 24 hours
• of upcoming patterns in their day where they may be at increased risk for highs or lows
• of upcoming time periods where they have gaps in testing; and
• at a glance about their general risk of short-term or long-term complications.

For compatible phones, Vigilant is also connected to a wireless blood glucose meter from a major meter manufacturer (the Accu-Chek® Aviva Connect) so that results can be automatically collected each time a user tests. Otherwise there is no new device required, no requirement to look at hundreds of data points, and nothing invasive.

There is also a web-based Caregiver portal (“Vigilant Caregiver”) that allows people to share patterns and risks with clinicians or loved ones. Vigilant believes this will facilitate a more efficient and informed patient-caregiver interaction and also give caregivers a means to easily monitor patterns and risks without having to wade through all the data.

Vigilant could benefit people by helping them not only reduce hypoglycemia but also reduce overall glucose variability. Insurers, health plans, and insurers could also benefit as acute complications such as hypoglycemia and diabetic ketoacidosis are reduced.

In summary, Vigilant’s system offers a novel diabetes management software paradigm enabled by advanced pattern recognition technology. Rather than acting as a just data repository, it empowers users with knowledge from their entire glucose profile, alerting them to upcoming periods of risk when they test or when they are on the go.