By Dr. Kit Yee Au-Yeung, PhD, GM, Sensing, SandboxAQ
SandboxAQ technology combines artificial intelligence with high-performing sensors to help clinicians make faster and more accurate decisions. We are announcing today our AQMed division and our CardiAQ™ medical device, which has the potential to define a new state-of-the-art in cardiac care.
In just three years, our team went from sketching concepts on whiteboards at Google X to clinical studies at some of the world’s leading medical institutions. Our team, comprised of experts with strong track records in AI, medical devices, cardiology, physics and engineering, has come together for the primary mission of changing the healthcare landscape for the better.
Through AQMed, we are developing the next generation of medical diagnostic devices with two goals in mind: to save lives and to reduce the economic burden of medical care. To guide us in our mission, we have assembled a world-class clinical advisory board (CAB) which includes Dr. Toby Cosgrove, MD, cardiac surgeon and former president and CEO of the Cleveland Clinic for 13 years.
“Cardiovascular disease is the number one killer across most of the world. As a doctor, having the most accurate and timely information about a patient’s cardiac state is critical for making life-saving treatment decisions,” said Dr. Cosgrove. “SandboxAQ's CardiAQ device shows how AI and this next generation of sensing technologies have the potential to revolutionize cardiac diagnosis and address the unmet clinical need for more effective patient care. This is the future of medicine.”
The utility of AI in healthcare is experiencing a boon in both clinical application and patient trust. The AI-enhanced diagnostic market is set to grow from $16.3B in 2023 to $71.2B in 2027. We’re starting with cardiac diagnostics since cardiovascular conditions are still among the leading causes of death in much of the world. In the U.S., chest pain is currently one of the top reasons for someone to visit the ER.
While the standard diagnostic tool currently used to monitor heart activity and detect cardiac issues – the 150-year-old electrocardiogram (EKG) – has vastly improved cardiac care, it has limitations. Most notably, when measured by EKG, the electrical signals of the heart may be distorted as they pass through the body. This can complicate diagnosis, and can lead to inaccurate and potentially dangerous conclusions. CardiAQ detects the magnetic fields of the heart using room-temperature sensors and AI software in a process called magnetocardiography (MCG). The device does not need any room shielding, which significantly opens up the use cases from ER, to bedside, to ambulance and beyond.
To test MCG’s ability to improve cardiac diagnosis, we completed our successful feasibility study with the University of California at San Francisco (UCSF) Medical Center, and have ongoing studies at Mount Sinai Medical Center in New York City. Dr. Jeffrey Bander, MD, Chief of Cardiology at Mount Sinai West, said: “The current methods for heart attack diagnosis can miss many cardiac conditions. Blood tests are costly, take time to process, and may give false negatives and positives. SandboxAQ’s goal is to revolutionize cardiac diagnoses with contactless, high-performance sensors and sophisticated AI that has the potential to benefit patients, save lives, and impact cardiac care globally with on-demand, real-time analysis”.
Today, SandboxAQ also announced a research collaboration with The Mayo Clinic to examine the relationship between MCG and the findings seen in angiography. The study will take place throughout 2024 and 2025 at the Mayo Clinic in Rochester, MN.
As we continue testing CardiAQ with our clinical partners, our team will continue exploring additional MCG use cases for cardiology and AI-driven magnetic sensing for other tissue types to elevate patient care and bring advanced treatment capabilities to more patients at healthcare facilities around the world.
For more information about CardiAQ and potential cooperative research partnership opportunities, please visit https://www.sandboxaq.com/solutions/aqmed.
