The AI oncology startup ConcertAI recently acquired CancerLinQ, one of the largest oncology real-world data and quality of care technology service entities. Originally developed by the American Society of Clinical Oncology (ASCO) in 2013, CancerLinQ aims to use real-world data and technology to improve cancer care and advance evidence-based research.
CancerLinQ has developed one of the “deepest, broadest, most generalizable, least biased single standalone data sources that exists in oncology,” according to Jeff Elton, CEO of ConcertAI. This real-world data asset encompasses clinical data across more than 7 million patients, 100 care sites and more than 10 EMR systems.
Boosting CancerLinQ’s scope and capabilities
The acquisition will bring considerably more resources to CancerLinQ, which had a dedicated staff of between 50 and 60 people in comparison to ConcertAI, which has more than 1,100 employees. Under terms of the deal, ASCO will maintain access to CancerLinQ data and remain involved in a cooperation agreement. All CancerLinQ staff members were offered employment by ConcertAI. Additionally, ConcertAI plans to enhance CancerLinQ with new data sources and renewed features related to clinical trial accessibility, clinical decision support, and automated EMR integration.In all, ConcertAI plans to invest more than $250 million in technology over the next few years. “In some of the meetings we had, during the process of working with CancerLinQ and ASCO and talking about where this would go, the words ‘AI’ and ‘generative AI’ came up a lot,” Elton said.
CancerLinQ acquisition occurred in a pivotal year for generative AI
Generative AI famously had something of a breakout year in 2023, and in terms of oncology research, the technology can help explore complex relationships. “Generative AI is very good at establishing the context of a question and activities in a process,” Elton said.
This evolution in data handling and interpretation in evidence-based cancer research can be further extended by incorporating a mixture of large language models, NLP and other technologies. Ultimately, such tools can streamline the research process by providing researchers with context-rich data. “Contextualized data means things that would have taken months or even years of complex custom coding can now be done in days to weeks,” Elton said.
In a recent interview on our AI Meets Life Sci podcast, Elton further shared his perspective on the promise of generative AI.
ConcertAI’s plans to expanding CancerLinQ’s impact
Under the stewardship of ConcertAI, ASCO researchers will maintain uninterrupted access to the CancerLinQ database. Meanwhile, the synergy between ConcertAI’s technological focus and ASCO’s research mission will support expanded use of CancerLinQ data for a broader set of research purposes.
In broad terms, the implications of AI in oncology are considerable in terms of both clinical care and new drug development. Elton expressed confidence in the near-future capabilities of augmenting the decision-making processes of clinical decision-makers and healthcare providers, highlighting the promise of potential of emerging tools to inform these professionals about new drugs that could be relevant for patients currently undergoing treatment.
Clinical trial recruitment is another promising area. “When you start thinking about the difference between what drives quality, identifying patients for clinical trials they may be eligible for, and informing other aspects of that decision, you see a continuum emerging,” he said. “That’s where the power of different technological approaches, particularly driven by combinations of generative and predictive AI, comes into play.”
Elton noted the healthcare community’s optimism around AI’s future role given that physicians are “seeing more patients with the same base of clinical resources.” At the same time, there’s been a notable dip in new medical oncologists or radiologists. This trend extends across medicine in the U.S. The Association of American Medical Colleges (AAMC) warned in 2021 that the country could see an estimated shortage across healthcare of between 37,800 and 124,000 physicians by 2034, including shortfalls in both primary and specialty care.
Those facts are part of the reason fueling interest in technologies such as generative AI. “Providers are excited about that. If you actually interview people in the specific areas of oncology, the radiology communities, etc., they all know that AI is going to be a significant part of their business,” Elton said.
Filed Under: Data science, machine learning and AI, Oncology