NEW YORK – When Clarified Precision Medicine launched in 2020, the goal was to take something that the firm's founding experts were already being asked to do — help oncologists make clinical decisions for their patients based on comprehensive genomic profiling results — and commercialize the model to scale. This meant doing something somewhat unprecedented: turning what was, at its core, a virtual molecular tumor board (MTB) into a for-profit company.
Four years later, the firm has inked several key partnerships with payors and health tech firms and has just raised $1.2 million in seed funding. Clarified's new CEO Rajni Natesan says the funds are testament to the fact that investors recognize the need for this type of service and that they're eager to back it.
"This seed round signals that there's tremendous market awareness that there needs to be a scaffolding of support at the last mile to ensure that these tremendous innovations get to the patient and are utilized by the provider," Natesan said. "There's a realization by the market and investors that this is a key piece to the puzzle that's been missing."
This missing puzzle piece, which has been coined the "last mile problem" in precision oncology, is the decision support that's needed to go from patients' comprehensive genomic profiling results to actionable next steps, especially when the results don't neatly match up to one clear, US Food and Drug Administration-approved targeted treatment. Surveys show that three-quarters of community oncology doctors say they'd love some sort of assistance in parsing their patients' test results, said Natesan. From next-generation sequencing to multi-cancer early detection, germline genetic testing, pharmacogenomic testing, and rapidly emerging new test approaches, the amount of information gleaned for each patient is challenging for most oncologists to keep track of, let alone translate into sound clinical decisions with confidence.
"There's confusion, there's overutilization, there's underutilization [and] it's only going to get more complex," Natesan said.
San Francisco-based Clarified, which lists precision oncology experts Lincoln Nadauld and Howard McLeod among its cofounders, provides oncologists who need it with decision-making help, in selecting not only the best treatment to give a patient but also which treatments to avoid for that patient, and how best to sequence treatments.
Most oncologists, especially those at community oncology practices, where 80 percent of patients receive care, aren't able to keep up with constantly changing guidelines and keep tabs on the lengthy list of experimental drugs their patients may be able to access in a clinical trial based on their biomarker status. Only a select population of oncologists, most of whom work in ivory tower institutions, have the precision oncology expertise to confidently draw these conclusions, and even then, these oncologists often need to meet with one another in the context of an MTB to collectively come up with the right next step. Through Clarified, oncologists can tap into the collective expertise of a group of reviewers to help parse a patient's comprehensive genomic profiling test results and come up with the best next step.
'The right tech at the right time'
Even though Natesan said Clarified's roster of 20 or so expert reviewers is actively growing, the idea that these oncologists will be able to start from scratch reviewing every single molecular test result for every patient who needs it is untenable. For this reason, Natesan said about 85 percent of the "lift" for Clarified's services comes from the firm's machine-learning platform and algorithm, which Natesan called its "computational workhorse."
"What we've built is this machine learning platform and algorithm that sits behind the medical group … and every aspect of that, from the way it's been built to the final recommendations for treatment are fully handheld and shepherded and guided by this expert medical group," she said.
The rules-based algorithm, which Natesan said has more than 50,000 rules and pertains to more than 200 cancer types, is built on a range of data types. It includes all the FDA-approved precision medicine targeted therapies and takes inputs such as DNA, RNA, proteomics, methylation, and available clinical guidelines such as those from the National Comprehensive Cancer Network. On top of those data and inputs, the algorithm learns from the core practice patterns for the oncologists Clarified works with.
"The algorithm is a living, breathing, adapting, and ever-learning algorithm honed by the medical group, patient by patient," Natesan said. Every time one of Clarified's expert reviewers provides a suggested treatment for a patient, that recommendation is fed back into the algorithm to improve its capabilities.
"The right treatment for the right patient at the right time" has become somewhat of an adage in precision oncology. Natesan said Clarified is "the right tech at the right time," too.
Expert reviewers still key
Even though Clarified's algorithm does the heavy lifting, Natesan underscored that every patient's individual case and results still undergo real human review, which she sees as the key differentiator between the firm and the many companies that market artificial intelligence-based clinical decision support tools for oncologists.
"When we look at how AI or [machine learning] are standing on their own two feet in this space, we see that it's very difficult for providers to trust the algorithm alone," she said, explaining that after Clarified's algorithm produces a preliminary report — the 85 percent of the lift — the expert reviewers can come in and tweak and adjust the recommendations, and the algorithm can then learn from those changes made.
"It's a very important differentiator for how Clarified is approaching the problem at hand," she said. "We're building physician and patient trust with our actual physical medical group."
The reviewers at Clarified can offer direct clinical recommendations, which is something commercial labs can't always do in their reports. Some lab reports may be as long as 40 pages and list many variants, some more actionable than others. "When you look at how far labs can go … they aren't able to practice medicine," she said.
Clarified sees itself as picking up where these reports leave off. The expert reviewers that Clarified employs can provide a patient-specific, clinically actionable report.
Reimbursement, sustainability
Clarified Precision Medicine hopes that the seed financing it just received will be a first step, and that the firm will receive additional funds as it grows. Ultimately, though, sustaining the business model requires getting payors on board to cover these services.
To this end, Natesan said the firm is partnering with plans across the US including MultiPlan, Medicare, Select Health, and Blue Cross Blue Shield, and is actively engaging with payors to grow these partnerships.
"We cover almost 100 million covered lives today, and we're very proud of that," Natesan said, noting that the way this works is through leveraging existing CPT codes that are already in use.
"The model of second opinions and referrals, particularly in oncology, is well received and accepted," she said. "It's been a very fluid go-to market for us."
From a payor perspective, Natesan said that a support service can be cost saving. Targeted therapies often have price tags in the five-to-six-figure range. "The [return on investment] to the payor is immense," she said. According to Natesan, the cost savings just in the first eight weeks from getting guidance from Clarified is, on average, $7,500 to $10,000 per patient. "It's been a very productive and easy dialogue with payors."
Beyond partnering with additional payors, Clarified is also working to ink partnerships with health tech companies to expand its reach and services. In 2022, for instance, the firm partnered with VieCure to integrate its clinical decision support into VieCure's algorithms in the hopes of making precision oncology more accessible, including in community oncology settings.
At the time, Clarified Cofounder McLeod said he sees the model — one in which precision oncology experts are available within VieCure's artificial intelligence platform — as similar to how tax experts are available through tax-filing software.
Looking ahead, Natesan said she envisions models like Clarified's, which pair both computational algorithms and real human expertise, as playing an increased role in precision medicine on the whole.
"The computational engines are getting smarter over time, but the critical oversight, the nuance, the judgment, the ultimate sign-off … when you provide that from a human expert at the top of their game, that's a combination that can be trusted by patients and providers and can scale with this explosive growth in genomics," she said.