Exits Stealth with $2M in Funding

Funds to Be Used to Build the Highway of Clinical-Grade AI for Safe and Effective Medical Applications, the company ensuring that medical artificial intelligence (AI)  is safe and effective, today exits stealth and announces $2M in seed funding led by 500 Global.

The company is also releasing a community edition of its platform free to academics and unveiling its advisory board that includes; The Honorable Dr. David Shulkin, M.D., the 9th US Secretary of Veterans Affairs, former president and CEO of Beth Israel Medical Center in New York; Bryan Sivak, former CTO of US Department Health and Human Services and former Managing Director of Kaiser Permanente Ventures; Dr. Paul Chang, M.D., a radiology professor at UChicago Medical Center.

Gesund combines an off-the-shelf machine learning operations (MLOps) toolbox and graphical user interface (GUI) with an explainability layer based on a low-code platform to allow non-programmers, e.g., physician-scientists or ML scientists, to run algorithms against new data sets and explore algorithm efficacy. Critically, this platform untangles the bottleneck of limited data by connecting curated and diverse data sets to innovative companies in a HIPAA-compliant fashion so they can more quickly and efficiently bring AI algorithms to market. Gesund’s clinical partners include UChicago Medical Center and Massachusetts General Hospital in the U.S., Berlin’s Charité, the largest university hospital in Europe. The immediate focus of the platform is solving the lack of contract research organizations (CROs) in the medical AI space, which is currently dominated by imaging/radiology applications.

Traditional CROs conduct clinical trials for drug and medical device companies to validate safety and efficacy on the way to regulatory clearance from the FDA. Gesund is providing CRO-like services for medical AI algorithms given traditional CROs, as well as regulatory bodies, lack the appropriate tools and data access for evaluation purposes.

“AI systems are only as good as the data used to train them but healthcare data is extremely fragmented across different providers, insurance companies, pharmacy records, and even consumer-generated data like fitness trackers,” explains Enes Hosgor, Ph.D., CEO and founder of Gesund. “We’re ensuring that AI is truly clinical grade and equitable by providing scalable and compliant access to standardized yet diverse data through a low-code MLOps platform.”

Artificial intelligence holds great potential for improving healthcare in ways that include improving preventative medicine and new drug discovery, which is why AI in healthcare is expected to grow at 48% annualized between 2017 and 2023, But the still-nascent nature of AI in healthcare carries risks of injuries and errors with the lack of data availability, cited in a recent report as a critical limiting factor to developing effective healthcare AI.

Overcoming those limitations is complicated by the fact that hospital IT systems are high-compliance environments that don’t fit with traditional MLOps stacks, which rely on third-party managed services used by traditional MLOps that complicate privacy compliance. Gesund’s proprietary and lightweight MLOps stack works both on-premise and via the cloud without strictly relying on containerization, like Docker, or orchestration, like Kubernetes, which is often a roadblock in high-compliance environments.

“AI can do so much to improve health outcomes but we first have to solve the lack of access to data that’s keeping its potential mired in gridlock,” says Enis Hulli, General Partner at 500 Global. “Gesund’s superhighway of clinical-grade AI is exciting because it clears the way to safer, more effective tools to help improve medical outcomes for patients.”

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