Mayo Clinic creates AI-powered clinical decision/diagnostics support platform, two digital health portfolio companies

“Changing the nature of healthcare from episodic to continuous”. Mayo Clinic announced the launch of the Remote Diagnostics and Management Platform (RDMP) that will connect data to artificial intelligence (AI) algorithms and create a ‘next generation’ of clinical support tools, diagnostics, and care protocols for faster diagnostics and more continuous care. According to Mayo Clinic Platform president John Halamka, MD, “clinicians will have access to best-in-class algorithms and care protocols and will be able to serve more patients effectively in remote care settings.” Patients will be able to access information to take better control of their health and make more informed decisions.

Mayo Clinic, with partners, is also organizing two portfolio companies to support RDMP:

  • Anumana, Inc. With nference, a synthesizer of biomedical data, Anumana will bring to market digital sensor diagnostics to decipher electrocardiograms (ECGs). The objective is to more effectively spot heart disease at the pre-symptomatic stage, enabling early treatment that saves patients and costs. Their first project will be to develop neural network algorithms based on billions of relevant pieces of heart health data contained in Mayo’s Clinical Data Analytics Platform, including millions of raw ECG signals. nference with Mayo in the past year has released COVID-19 molecular research based on Mayo data. Anumana completed a Series A of $25.7 million funded by the partner companies plus Matrix Capital Management, Matrix Partners, and NTTVC.  nference release.
  • Lucem Health Inc. With Commure, a General Catalyst portfolio technology company that accelerates healthcare software development, Lucem will develop the platform for connecting remote patient telemetry devices with AI-enabled algorithms. Lucem is kicking off with a jointly funded $6 million Series A. 

We noted back in 2019 Dr. Halamka’s move to Mayo to head up a machine learning/AI initiative which took a while (during a pandemic year) but is moving quickly. The Mayo release includes a YouTube video of Drs. Halamka and Friedman explaining Anumana’s objectives in early diagnosis reading ‘those invisible signals’ well ahead of an event, especially needed with heart disease as the first symptom may be devastating or deadly. Hat tip to HISTalk, which also amusingly notes Dr. Halamka’s sartorial changes.

 

Will there ever be a medical ‘tricorder’?

ZDNet teases us that ‘the race is on’, but is it? It’s a great clickbait headline, but the substance of the article illustrates the distance between today’s tech reality versus the picture of Star Trek’s Bones pointing a Tricorder at a patient and immediately pronouncing that your malady was Sakuro’s Disease or some strange Vulcan malady.

Was it that long ago that the Scanadu Scout was the odds-on bet to be the Tricorder? The hype began in 2012 [TTA 23 May 2013] with Indiegogo funding, competing for the XPRIZE, and breathless pronouncements at nearly every healthcare conference. By 2016, it missed the Qualcomm Tricorder XPRIZE finals (with Northern Ireland’s Intelesens), bricked all sold units to date to comply with FDA regulations on investigational devices, and with Chinese money in hand, moved into other testing devices. Those looking for Scanadu today will be disappointed as their website is unreachable. The DeBrowers and medical director Alan Greene, all of whom were fêted on the healthcare scene, are engaged over at Doc.ai with a new mission of decentralizing precision medicine onto the blockchain using AI, using your medical data gathered on an app (of course).

Google X was up next as Scanadu was fading. There were various devices they were hyping and testing as Google’s life sciences skunk works morphed into Verily, but to date they have all petered out, with some questions raised about people and project churn at the Alphabet unit [TTA 6 April 2016] .

Basil Leaf Technologies (as Final Frontier Medical Devices) wound up winning last year’s final Qualcomm XPRIZE with DxtER, which could diagnose and interpret a defined set of 13 health conditions to various degrees, while continuously monitoring five vital health metrics, using a mix of sensors and an AI-powered diagnostic engine. What they are planning to market first is not DxtER, but a single-disease device to monitor congestive cardiac failure (CCF) since FDA approval for DxtER “would take aeons to be approved.”

Urine tests are also a ‘wet’ way into a tricorder state, with both Basil Leaf and the University of Glasgow working on devices which could quickly scan for metabolites in urine that indicate particular diseases.

QuantuMDx’s Q-POC, from Newcastle UK, is expected to launch in 2019 with handheld diagnostics for bacterial and viral infections. In addition to quick diagnostics for outbreaks in less developed countries, they are also developing diagnostics to prescribe the right antibiotic the first time. This is critical in treatment superbugs such as MRSA and MSSA, as well as more garden variety infections which can go wrong quickly. TTA profiled their crowdfunding launch in 2014.

The ZDNet article wraps up with a bit of romance about how a tricorder is needed for Mars, but down here on Earth, the reality is that a tricorder will likely be a combination of devices and analytics, stitched together by machine learning and AI.