InSpark believes there is significant untapped diabetes management potential that can be extracted from the 25 billion episodic home blood glucose (BG) readings performed annually worldwide. Most BG software today, whether on a meter, phone or computer, incorporate simple logs, charts and graphs that do not answer important questions like; 1) at what time of day do I have strong daily patterns of highs and lows, and 2) what is my risk of severe hypoglycemia?
InSpark has licensed a suite of blood glucose pattern recognition technology from the University of Virginia (PI Boris Kovatchev) that can be applied to BG data to answer these questions when patients need it most - when they are testing. The performance of these algorithms is supported by numerous peer reviewed publications and issued and pending patents. InSpark believes feedback powered by these algorithms can significantly improve the clinical impact of BG monitoring in the 10's of millions of diabetes patients on insulin.
InSpark is currently developing a number of solutions incorporating these algorithms, including Vigilant, an mHealth software system that informs about glycemic variability, daily patterns of highs and lows, and risk of severe hypoglycemia in the next 24 hours. InSpark's goal is to deliver this transformational technology into the hands of patients, clinicians and health care systems to improve health outcomes for millions of people with diabetes worldwide.