Sensydia, a Los Angeles, CA-based non-invasive cardiac diagnostic company, raised $3M NIH Grant.
The Fast-Track Small Business grant came from the National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH).
The company intends to use the funds for the development and clinical testing of the machine learning algorithms for the Cardiac Performance System (CPS), designed to enable earlier detection and therapy guidance for patients with heart failure and pulmonary hypertension.
Phase I of the grant proposal is budgeted for approximately $600,000 and Phase II for $2.4M, following successful completion of Phase I milestones.
Sensydia provides AI-based solutions for the diagnosis and management of cardiopulmonary diseases, expanding access to cardiac performance assessment outside the hospital setting. Cardiac Performance System (CPS) utilizes proprietary waveform machine learning methods that have been trained against gold-standard measurements from in-hospital catheterization lab data. Its platform delivers accurate, non-invasive assessment of cardiac performance (cardiac output, ejection fraction, and pulmonary pressures) almost anywhere in under 5 minutes.
In 2018, Sensydia received FDA 510(k) clearance for non-invasive measurement of ejection fraction using first-generation hardware. In 2022, its CPS was granted Breakthrough Device Designation by the FDA, to measure three additional key cardiac measures (cardiac output, pulmonary artery pressure, and pulmonary capillary wedge pressure).
