Globally, at-scale use of AI in oncology care is still in its early stages for most providers. When used, it's usually to support clinical decision-making in cancer diagnosis (e.g., reading scans and flagging abnormalities) or in cancer treatment (e.g., suggesting drugs that may be a good fit for a patient's genetic mutations). And it's almost always used within a single organization to iteratively improve the care they deliver.
But that scope may soon become outdated. In our recent research on global trends in oncology, our international team looked at dozens of AI start-ups, products, and partnerships that are expanding AI's role and prevalence in transforming cancer care.
While every example we encountered was interesting and newsworthy, there are three that our team will be watching over the next year, as their growth could foreshadow larger impacts that will reshape every part of the cancer journey over the next decade.
1. Company: GRAIL, Inc.
What it does: Use AI and machine learning to enhance its multi-cancer liquid biopsy test.
Why we are watching it: A successful expansion into the United Kingdom will make it clear that AI can be a catalyst for broader adoption of new, otherwise-hard-to-scale diagnostics.
GRAIL, Inc., based out of the United States, is a world leader in liquid biopsy testing. Its Galleri test can detect more than 50 different types of cancer in asymptomatic patients by measuring methylation patterns in cell-free tumor DNA in the blood. In trials, the test demonstrated 99.3% specificity across these 50+ cancer types, with 93% accuracy in identifying tissue of origin.
Liquid biopsies have numerous benefits, the most notable of which is that they are precise and are non-invasive. But manually testing for methylation can be a tedious process. GRAIL has found a solution to this: The company uses AI and machine learning to examine patterns of natural DNA modifications that signify if a cancer is present or not, and which type of cancer it is likely to be.
GRAIL takes advantage of more than one million gigabytes of data amassed through clinical study programs, against which they can compare tests and speed up diagnosis. Plus, because the algorithms use machine learning, the more tests they do, the faster and more accurate they will become.
In March 2021, GRAIL partnered with one American health system—Providence—to implement the Galleri test in the clinical setting. Through this partnership, Providence will be able to grant early access to its patients as a complement to single cancer screening tests.
And to the point of achieving scale—in June 2021, it announced a partnership with England's NHS to test the clinical and economic viability of the service in England. About 165,000 people are enrolled in the trials, and depending on initial results, the trial will expand to one million people by 2024-2025.
2. Company: Allcyte
What it does: Use AI to analyze hundreds of drugs at a time on live cancer tissue samples and uncover targeted treatment options for each patient.
Why we are watching it: We see companies like Allcyte serving a critical role in convening and providing outcomes data to support ecosystem-wide pursuits of value-based cancer care in the future.
Allcyte, a tech start-up from Austria, is at the forefront of precision medicine in cancer. The company takes blood cancer samples from a patient and then tries 100+ medicines on those samples in a lab to see which treatment has the best chance of working.
Using an AI-based technology, Allcyte classifies images of each sample to measure how the cells respond to each drug. In its recent publication, 54% of patients for whom Allcyte found new therapies experienced longer symptom-free survival compared with prior lines of therapy.
Allcyte sees itself as an answer to inaccuracies that "normal" genetic testing can bring—in an interview in March 2021, the CEO and co-founder stated, "instead of trying to extrapolate from DNA, here we take the actual tumor, and we ask the tumor the question of 'what will work'."
This clearly has a use case for providers and physicians—imagine seeing into the future which therapy may work best. But it also can help pharmaceutical manufacturing and research and development. Allcyte has partnerships with 10 large pharmaceutical companies to use the same technology to assist in the discovery of new drugs. And it is testing old therapies on patient cancer cells to find potential opportunities to repurpose outdated treatments for different conditions than originally intended.
While the company is still in its early stages—it needs regulatory approval in the United States and Europe and will need more funding to offer the same service for solid tumors—the early indications are promising.
Its partnerships and drug-related use cases prove that it cannot only use AI to help find or develop treatments, but also to unite physicians, drug makers, and patients around cancer drug R&D and outcome definition. Because of this, we expect Allcyte, and companies like it, to have a critical role in convening future conversation about value in cancer care and in trialing new models in tow.
3. Company: caresyntax
What it does: Use AI-driven 'smart surgery' platforms to predict outcomes and inform real-time care decisions before, during, and after surgery
Why we are watching it: This partnership signals the next evolution of AI's role in cancer care surgery standardization and variation reduction
Caresynthax is a health tech company with two global headquarters, one in Boston and the other in Berlin. Its AI and machine learning-powered digital surgery platforms essentially function as surgical Alexas—they analyze hundreds of inputs like video, audio, images, and clinical and operational data in and around the OR which enables care teams to predict outcomes and improve surgical performance. Its platforms are used in around 4,000 ORs globally and have helped improve surgery for more than two million patients.
To bring this to cancer care specifically, the company is building a new oncology-specific platform in partnership with Sheba Medical Center, the largest AMC in Israel and a provider known for its advanced digital medicine innovation center.
In this partnership, caresyntax will analyze electronic records and data from 3,000+ oncology surgeries, measuring 300+ variables in the OR for each one. The outcome will be a set of algorithms that will offer feedback to help surgeons make informed, patient-specific decisions before, during, and after surgery.
While smart surgery has reached other clinical services, this is the first we have heard of it making its way specifically to cancer surgery. And while we know that clinician pushback to new technologies—AI in particular—can limit uptake, Sheba's tech-forward culture bodes well for clinicians allowing this "over-the-shoulder" tool a place on their clinical toolbelts.
If successful, this tool will lead to more consistent standards, improving payers' and providers' ability to analyze risk and predict outcomes around cancer care.