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Many diabetes patients have been calling for ‘smart’, internet-connected pens to monitor their condition, but the technology has been slow to arrive.

Now, Novo Nordisk has announced that it will globally launch two ‘connected’ insulin pens, which will be able to communicate with continuous glucose monitoring (CGM) systems and blood glucose meters (BGM).

This looks to be the start of the long-awaited digital integration, which has been held back by safety concerns, competitive interests and incompatible digital platforms.

Novo Nordisk’s biggest competitors in diabetes injectables are Eli Lilly and Sanofi, but looks to be ahead of its rivals in rolling out a joined-up digital solution, announcing plans to make two durable, connected insulin pens NovoPen 6 and NovoPen Echo Plus commercially available across key markets from early 2019.

In addition to demand from patients, healthcare payers, especially in the US, are calling for comprehensive disease management platforms.

Medtech companies have enlisted novel approaches to detecting diabetes and measuring blood glucose levels from tears to sweat, if only to show that it can be done. But a new study by digital health startup Cardiogram with the University of California San Francisco suggests yet another potential avenue to detection: heartbeat assessment through a wearable fitness tracker.

“By continuously monitoring using non-invasive wearables, we can identify when you’re at high risk of undiagnosed pre-diabetes or diabetes, offer you a free A1c test, and then guide you to clinically appropriate treatments,” Ballinger said.

The study recruited 14,011 participants who access the Cardiogram app. Although the app is available through Apple Watch or Android smartwear, the study only involved Apple Watch users.  The web-based, IRB-approved study was run in partnership with the cardiology department at UCSF. Participants completed a medical history, including previous diagnoses, blood test results, and medications. A mobile app integrated with HealthKit continuously stored, processed, and displayed participant heart rate, step count, and other activity data, according to a description of the study.
The study was part of the larger online Health eHeart Study by UCSF, which has enrolled more than 100,000 participants worldwide.
Using its deep neural network called DeepHeart, Cardiogram assessed 200 million heart rate and step count measurements to predict who had diabetes and who did not. The accuracy rate was 85 percent.