10 Startups Competing to Do What Watson Health Couldn’t, Part 1

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IBM’s standard line was that there was literally no limit to the number of ways its Peril!-Watson winning computer could be applied in health care. Advising oncologists on treatment has perhaps been the most publicized.

Lesser-known use cases on Watson’s plate ranged from assisting frontline physicians in diagnosing rare diseases to assisting insurers in settling claims. The unit has also partnered with a legion of drug and device makers to embed access to Watson into a host of products and services, as well as to help discover new therapies.

Lost in the fog of marketing and hype, however, was the outsized scale of his ambition. The sale of Watson Health’s assets last month to a private equity firm finally closed that chapter.

Today, the hope of using data, analytics, and cloud computing to improve healthcare lives on, not with a single vendor, but scattered across the industry. A number of startups, for example, are looking to revolutionize cancer treatment through artificial intelligence. Others apply AI to pathology to improve diagnosis.

MM+M has compiled a list of 10 AI-focused startups that are picking up where Watson Health’s foray into diagnostics and treatment left off. Today we feature five companies in the field of diagnostics; Early next week, we will feature five organizations working on treatment.

For each, we show what they’re solving for (and for whom), their level of funding (if venture-backed), and the evidence demonstrating their potential (if any).

DIAGNOSTIC

Cardiac flow

What are they solving for (and for whom)

Cardiac flow aims to guide cardiologists in tailoring treatment for coronary heart disease, which remains the leading cause of death in the United States

Total funding

Founded in 2007, the company has raised a total of $577.7 million, per CrunchBase. HeartFlow was supposed to go public as part of a $2.4 billion deal with a SPAC, but the two terminated their reverse merger on February 4, citing “current adverse market conditions.”

The product

The FFR of the companyCT leverages deep learning (a machine learning technique), medical imaging data from a coronary scanner, and highly trained analysts to render its own color-coded digital 3D model.

The proof

The diagnostic accuracy of FFRCT helping cardiologists determine whether patients should have an invasive procedure (like a stent) or can be medically managed, has been supported by over 500 peer-reviewed studies. A study has shown that an FFR-guided

revascularization strategy is associated with a 43% lower all-cause mortality than a

Year, compared to a strategy of revascularization by angiography alone.

Offers, deployments and amendments

The technology has been recognized in the 2021 ACC/AHA Chest Pain Guidelines as a Class 2a recommendation, making it the first AI-enabled technology to be included. It is available at approximately 90% of the top 50 US cardiac hospitals and covered by 96% of payers.

PathAI

What are they solving for (and for whom)

PathAI is one of many startups leveraging machine learning to make more accurate (read: less subjective) diagnoses of biopsies and tissue samples, which are typically analyzed by pathologists on glass slides under a microscope. It targets a wide range of stakeholders, primarily biopharmaceutical and drug discovery companies, academic research institutes, laboratories and suppliers.

Total funding

Founded in 2016, PathAI has raised a total of $315 million, per Rock Health. Investors include Labcorp, Merck Global Health Innovation Fund and Bristol Myers Squibb.

The product

PathAI’s digital pathology platform is built on a library of millions of pathology slides, annotated by millions of board-certified pathologists who have trained and tested its deep learning models.

The proof

PathAI’s AI-powered image analysis algorithm was found to be more sensitive to biomarker detection than visual assessment by pathologists. The company cites a retrospective analysis of clinical trial data looking for the expression of PD-L1, a biomarker associated with immune checkpoint inhibitor drugs. Compared to manual assessment of PD-L1 expression samples in bladder cancer and skin cancer cases, respectively, PathAI’s image analysis algorithm was between 7% and 22 % more sensitive, and between 10% and 25% more sensitive.

Offers and deployments

The company has partnerships with Labcorp and with Roche Diagnostics to deploy its algorithms across a broad portfolio of programs and software, as well as with commercial biobanks, academic medical centers and private laboratories. PathAI also integrates other critical platforms into its own.

Paige.AI

https://vimeo.com/617897967/411fa6a05f

What are they solving for (and for whom)

Paige.AI merges AI and pathology in cancer. The company aims to help pathologists and oncologists make better diagnoses and help life science companies pursue targeted therapies.

Total funding

Founded in 2018, Paige.AI has raised a total of $291 million, per Rock Health. Investors include Johnson and Johnson Innovation, KKR and Goldman Sachs.

The product

The Company’s first product is Paige Prostate, a clinical-grade AI tool for prostate cancer detection that received de novo marketing authorization from the FDA last year. The approval allows pathology labs to introduce the tool into their clinical workflow.

The proof

Pathologists using Paige Prostate have been shown to increase the correct diagnosis of cancer by more than seven percentage points (from 89.5% to 96.8%). Pathologists also saw a 70% reduction in false negative diagnoses and a 24% reduction in false positives. The improvements were maintained regardless of the pathologist’s level of specialization or years of experience, and whether the analysis was performed remotely or onsite. Non-specialist pathologists using the software were as accurate as non-specialist prostate specialists.

Offers and deployments

Paige has a licensing agreement with Memorial Sloan Kettering Cancer Center that gives her exclusive access to anonymized digitized images from Memorial’s archive of 25 million pathology slides. Last year, it secured partnerships to implement its software in commercial labs Quest Diagnostics and Inform Diagnostics, as well as throughout the University of Louisville healthcare system.

exo

What are they solving for (and for whom)

exo (pronounced “echo”) applies AI to medical imaging to help doctors triage, diagnose and treat patients at the point of care. The company is working to “democratize ultrasound,” as one investor put it, by bringing affordable, easy-to-use, non-radiating imaging technology to a broad market.

Total funding

Founded in 2015, Exo has raised a total of $307.6 million, per CrunchBase. That includes last year’s $220 million Series C round, which included investors BlackRock, Avidity Partners and Sands Capital. Action Potential Venture Capital (APVC), a GlaxoSmithKline venture capital fund, is also among its backers.

The product

The company is looking to provide physicians with a portable probe to image the whole body. The portable ultrasound device is built using nanoscale piezoelectric materials with semiconductor capabilities, along with an additional layer of AI and computational photography algorithms. Exo has also developed a software platform, Exo Works, designed to solve imaging workflow issues. The system combines exam review, documentation and billing into one platform and works with almost any point-of-care ultrasound device. Neither has obtained regulatory approval.

The value proposition

Exo compares to cart-based ultrasound equipment. The company says its tools can improve accuracy by generating better image quality, definition, and depth for about the cost of a laptop computer, and its system streamlines the process of reviewing, documenting, and billing with less one minute.

Offers and deployments

The software securely connects to the most common EMR and PACS systems used in hospitals to host imaging and communications. Exo envisions use in emergency rooms, rural clinics or in several departments of community hospitals.

Proscia

What are they solving for (and for whom)

What PathAI and Paige.AI are doing to drive the adoption of digital pathology in other areas of oncology, Proscia made in dermatology. Pathologists will benefit from the potential of its AI to deliver faster diagnoses, better outcomes, and increased lab productivity.

Total funding

Founded in 2014, the company has raised a total of $34 million, according to CrunchBase. Investors include Scale Venture Partners and Hitachi Ventures.

The product

Proscia’s platform, dubbed Concentriq, enables labs and life science companies to ingest, visualize, manage and analyze tissue biopsy images to power their data-driven pathology. Its DermAI app has been shown to be able to automatically detect melanoma with a high degree of accuracy. Neither has been approved by the FDA.

The proof

Concentriq users have seen between 13% and 21% gains in efficiency and productivity over traditional pathology, according to the company. In a study validating DermAI in a non-curative set of 1,422 sequential skin biopsies, its technology correctly identified invasive melanoma and in situ melanoma with 93% sensitivity and 91% specificity.

Offers and deployments

Proscia’s customer base includes 10 of the top 20 pharmaceutical companies, as well as the Johns Hopkins School of Medicine and the Joint Pathology Center. Its AI applications are also being deployed as part of a recently established Computational Pathology Center of Excellence with the University Medical Center of Utrecht. Approximately 5,000 pathologists and researchers in laboratories, research organizations and life science organizations currently use Concentriq.

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