The announcement came just months after Mayo Clinic selected the program’s initial cohort of four companies in March.
Each company participating in the 20-week program, called Mayo Clinic Platform_Accelerate, receives a $200,000-benefit package. As a condition of this investment, Mayo Clinic Platform receives an equity position in each startup.
The package allows startups to refine their AI models using Mayo Clinic’s deidentified data sets and get feedback from Mayo Clinic’s subject matter experts, including clinicians, researchers and product development professionals. It also gives startups the opportunity to attend workshops and presentations about topics ranging from FDA clearance requirements to AI ethics. Some of these workshops are led by experts from Google and Epic, according to Eric Harnisch, Mayo Clinic Platform’s vice president of partner programs.
The companies chosen for the program’s second cohort went through a selection process in which Mayo Clinic experts assessed their potential to address unmet medical needs with the use of AI. Harnisch said the team selected companies that had robust data science foundation and prior experience with Google Cloud Platform, as that is Mayo Clinic’s cloud provider.
Here are the seven startups selected:
Berkeley, California-based AESOP, which stands for AI-Enhanced Safety of Prescription, develops automation software to improve the clinical decision support process and make physician data entry faster and less error-prone. It recently launched its latest clinical documentation improvement tool, which helps medical coders flag diagnoses or procedures that were flagged incorrectly. The startup has offices in California, Colorado and Taiwan.
New York City-based Biotia is a spinout of Cornell Tech that is focused on battling infectious diseases with AI and genomics. The company claims it is working toward developing the world’s leading microbial sequence database. It is currently creating DNA sequencing technology to allow for the personalized discovery of disease-causing microorganisms. This rapid precision infectious disease discovery would guide better patient treatment and improve health outcomes, according to the startup.
San Francisco-based Delfina is a maternal telehealth company that remotely monitors pregnant women to assess health risks and collaborates with providers to produce a personalized care plan. The startup partners with OBGYN providers to offer its services to their patients in an effort to lower the country’s maternal mortality rate, which is the highest among all developed nations. The company also has offices in New York City and Rochester, Minnesota.
Cambridge, Massachusetts-based Dynocardia uses wearable technology to track real-world continuous blood pressure and other advanced heart function measures. It created ViTrack, a cuff-less wearable that enables non-invasive blood pressure measurement and leverages AI for the early detection of heart issues to prevent serious health events.
Palo Alto-based ImpriMed is aiming to validate a personalized medicine platform for human and animal cancer patients. Using AI, the startup’s platform gives patients and clinicians predictive information for personalized cancer treatment pathways, allowing oncologists to quickly identify which available drugs provide the best clinical outcomes for a particular patient. The company also has offices in Seoul.
Tel Aviv-based Predicta Med offers an AI-powered decision support platform for the early detection of autoimmune diseases. Using EMRs and claims data, the company built algorithms that detect various autoimmune diseases. The startup’s platform shows clinicians which patients are at risk and provides treatment recommendations. It believes that early detection and intervention decreases health plans’ costs and strengthens treatment efficacy.
Boca Raton-based SOAP Health stands for Subjective, Objective, Assessment, Plan. Its software is designed to improve early disease detection and diagnosis at the point of care. The startup offers an EHR-integrated platform with a patient and physician-facing interface that is powered by conversational AI. This platform identifies at-risk patients who meet national medical associations’ guidelines for increased surveillance for cancer, heart disease and type 2 diabetes.
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