Published Study Supports MyoKardia’s Wrist-Worn Biosensor

MyoKardia’s said data on its wrist-worn digital health device was published in an article titled, “Machine Learning Detection of Obstructive Hypertrophic Cardiomyopathy (oHCM) Using a Wearable Biosensor,” in the Nature Partner Journal, Digital Medicine.

The South San Francisco-based company said results from an exploratory study provided encouraging evidence of the potential for a wrist-worn biosensor to screen for obstructive hypertrophic cardiomyopathy.

The study demonstrated that continuous monitoring using a wrist-worn photoplethysmography (PPG) digital health device, similar to the optical sensors that monitor heart rate on commercially available fitness trackers, revealed differences in arterial pulse wave patterns between oHCM patients and those of individuals without oHCM.

MyoKardia’s proprietary machine learning algorithm identified individuals with oHCM with a sensitivity of 0.95 and a specificity of 0.98. The digital health substudy was conducted by MyoKardia as part of the company’s Phase 2 PIONEER-HCM trial of mavacamten.

“Hypertrophic cardiomyopathy, or HCM, is associated with an increased risk for heart failure, stroke, and sudden death, even in asymptomatic patients. However, HCM is vastly underdiagnosed, as only approximately 15% of the estimated 1 in 500 people with HCM receive the correct diagnosis. The symptoms of HCM, such as shortness of breath, exercise intolerance, or fatigue, are nonspecific, and our research indicates that it can take patients up to three or more years after symptom onset to receive a diagnosis. The results of this study suggest that broadly available wrist-worn biosensor technologies may be able to identify undiagnosed oHCM patients who could be at risk of developing serious cardiac complications,” said Marc Semigran, MD, Senior Vice President of Medical Sciences at MyoKardia, and senior author of the article. “As part of our commitment to improving the lives of patients, we have integrated digital health technologies into our interventional clinical studies, with the aim of advancing the diagnosis, treatment and monitoring of cardiomyopathies.”