Michael Barbella, Managing Editor08.14.23
Non-invasive cardiac diagnostic company Sensydia has been awarded a $3 million Fast-Track Small Business grant from the National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH).
The grant provides Sensydia with non-dilutive funding to develop and clinically test 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.
“We are honored to be a recipient of this competitive award from the NIH/NHLBI and look forward to unlocking the capabilities of AI-based cardiac assessment to provide personalized care to patients suffering from heart disease,” Sensydia Chief Medical Officer Aman Mahajan, M.D., said.
Phase I of the grant proposal is budgeted for approximately $600,000 and Phase II for $2.4 million, following successful completion of Phase I milestones.
The NIH grant follows Sensydia's recent $8 million venture funding round.
The Small Business Technology Transfer (STTR) program of the NIH supports U.S.-owned small businesses with early-stage capital for creating innovative technologies to improve human health. The STTR Fast-Track streamlines funding for Phases I and II, with feasibility established in Phase I and technology development in Phase II.
Sensydia intends to revolutionize heart failure therapy by expanding access to cardiac performance assessment outside the hospital with its non-invasive Cardiac Performance System (CPS). The U.S. currently spends more than $30 billion annually to diagnose and manage heart failure, which requires costly and risky in-hospital catheterization procedures to obtain an accurate assessment of cardiac performance. Sensydia’s CPS platform delivers accurate, non-invasive assessment of cardiac performance (cardiac output, ejection fraction, and pulmonary pressures) almost anywhere in less than five minutes. CPS utilizes proprietary waveform machine learning methods that have been trained against gold-standard measurements from in-hospital catheterization lab data.
In 2018, Sensydia received U.S. Food and Drug Administration 510(k) clearance for non-invasive measurement of ejection fraction using first-generation hardware. In 2022, Sensydia’s CPS received FDA Breakthrough Device Designation to measure three additional key cardiac measures (cardiac output, pulmonary artery pressure, and pulmonary capillary wedge pressure).
The grant provides Sensydia with non-dilutive funding to develop and clinically test 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.
“We are honored to be a recipient of this competitive award from the NIH/NHLBI and look forward to unlocking the capabilities of AI-based cardiac assessment to provide personalized care to patients suffering from heart disease,” Sensydia Chief Medical Officer Aman Mahajan, M.D., said.
Phase I of the grant proposal is budgeted for approximately $600,000 and Phase II for $2.4 million, following successful completion of Phase I milestones.
The NIH grant follows Sensydia's recent $8 million venture funding round.
The Small Business Technology Transfer (STTR) program of the NIH supports U.S.-owned small businesses with early-stage capital for creating innovative technologies to improve human health. The STTR Fast-Track streamlines funding for Phases I and II, with feasibility established in Phase I and technology development in Phase II.
Sensydia intends to revolutionize heart failure therapy by expanding access to cardiac performance assessment outside the hospital with its non-invasive Cardiac Performance System (CPS). The U.S. currently spends more than $30 billion annually to diagnose and manage heart failure, which requires costly and risky in-hospital catheterization procedures to obtain an accurate assessment of cardiac performance. Sensydia’s CPS platform delivers accurate, non-invasive assessment of cardiac performance (cardiac output, ejection fraction, and pulmonary pressures) almost anywhere in less than five minutes. CPS utilizes proprietary waveform machine learning methods that have been trained against gold-standard measurements from in-hospital catheterization lab data.
In 2018, Sensydia received U.S. Food and Drug Administration 510(k) clearance for non-invasive measurement of ejection fraction using first-generation hardware. In 2022, Sensydia’s CPS received FDA Breakthrough Device Designation to measure three additional key cardiac measures (cardiac output, pulmonary artery pressure, and pulmonary capillary wedge pressure).