Xsensio attracts Mayo Clinic as partner and investor

Xsensio will work closely with Mayo Clinic subject matter experts who will provide clinical and product development expertise to Xsensio around the use of its proprietary health monitoring technology for critical care. The intent is to further accelerate innovation in the development of next-generation wearable solutions that provide continuous, real-time, on-body monitoring of biochemical data, with the goal of enhancing personalized early detection of rapidly evolving acute events, improving rapid clinical workflow, and enabling remote patient monitoring.

"This collaboration will provide key insights for the use of our proprietary Lab-on-Skin sensing platform for critical care in the hospital and at home. We are very excited to establish a collaboration with Mayo Clinic," said Esmeralda Megally, CEO and Co-Founder of Xsensio. Mayo Clinic is the first and largest integrated, not-for-profit group practice in the world. Physicians and scientists from every medical specialty work in collaborative teams to advance discovery and translational research on behalf of patients. Mayo Clinic is a single institution located at three main campuses and over 70 smaller hospitals, laboratories and other facilities. It employs 63,000 people, including more than 4,500 physicians and scientists

Mayo Clinic has a financial interest in the technology. Mayo Clinic will use any revenue it receives to support its not-for-profit mission in patient care, education, and research.

Xsensio considerably expands the potential of wearable products with the development of a breakthrough wearable device that tracks – not physical data like today’s devices – but biochemical data in the interstitial fluid (ISF) on the skin. At the core of Xsensio’s wearable innovation lies a proprietary 5x5mm Lab-on-Skin sensing chip that leverages cutting-edge nanotechnology, biochemistry and microfluidics to continuously collect ISF at the surface of the skin, and continuously analyze its biochemical composition to detect changes in real time that reflect physiological state.

(Press release / SK)