For over a decade, the American Society of Clinical Oncology (ASCO) maintained CancerLinQ, a pioneering initiative designed to aggregate real-world data from oncology practices across the United States. Initially conceived as a means to transform routine patient encounters into a massive learning system, CancerLinQ functioned primarily as a reporting utility. It helped practices navigate the complexities of quality measurement and certification. However, following its acquisition by ConcertAI in December 2023, the platform has undergone a radical metamorphosis. It is no longer just a registry; it has emerged as a high-velocity, point-of-care intelligence platform, fundamentally shifting how oncologists interact with data, research, and clinical decision-making.
The Evolution: From Static Reporting to Dynamic Insight
To understand the significance of this shift, one must look at the limitations of the platform’s original design. Before the ConcertAI acquisition, CancerLinQ was largely defined by its utility in automated reporting. It was the backbone for practices seeking to demonstrate adherence to ASCO’s rigorous quality measures—a vital, yet essentially retrospective, process.
"Before we bought it, CancerLinQ largely just delivered software that automated the measurement of ASCO certification quality measures," explains Eron Kelly, CEO of ConcertAI.
Under ConcertAI’s stewardship, the platform has pivoted from a retrospective reporting tool to an active participant in the clinical workflow. By integrating advanced AI models and agentic workflows, the platform now provides real-time trial-matching, sophisticated research datasets, and proactive clinical decision support. This evolution reflects a broader trend in healthcare technology, where leaders like ConcertAI, Flatiron Health, Tempus, and Komodo Health are moving beyond simple data aggregation to create "agentic" systems—tools that perform tasks, make recommendations, and actively assist clinicians in navigating the complexities of modern cancer care.
A Chronology of Transformation
- 2013-2014: The American Society of Clinical Oncology (ASCO) initiates the development of CancerLinQ to address the "learning health system" gap in oncology.
- 2015-2022: CancerLinQ establishes itself as a leading registry for oncology data, providing practices with automated reporting to meet ASCO quality standards.
- December 2023: ConcertAI announces the acquisition of CancerLinQ from ASCO, signaling a shift toward AI-enhanced clinical intelligence.
- 2024-2025: ConcertAI begins integrating its proprietary AI engine, capable of parsing unstructured clinical notes, pathology reports, and genomic data.
- 2026: The platform achieves widespread deployment of point-of-care, agentic AI features, including automated trial matching and care-gap identification.
Closing the Care-Research Gap
One of the most profound challenges in oncology is the widening chasm between the rapid pace of drug discovery and the standard of care delivered at the bedside. Dr. Shaalan Beg, Chief Medical Officer for Oncology at ConcertAI, highlights that for many patients, particularly those with rare or aggressive malignancies like metastatic pancreatic cancer, the "best" standard of care is often found exclusively within clinical trials.
The data supports this urgency. Recent findings presented by ASCO showcased a new agent that nearly doubled median survival in previously treated metastatic pancreatic cancer—extending it from six months to 12 months. Without a systematic, AI-driven mechanism to match patients to these emerging trials, such breakthroughs often remain inaccessible to the average patient.
"If you’re a pancreatic cancer patient right now and you want the best standard of care, the only way you’re going to get it is through clinical trials," says Dr. Beg. By automating the screening process, ConcertAI’s platform reduces the time required for trial-matching to less than one-third of traditional manual methods. The system evaluates 20 to 30 eligibility criteria simultaneously, providing clinicians with verified matches without the need for manual chart scouring.
Supporting Data: The Rise of AI Adoption in Medicine
The transition toward AI-supported oncology is happening against the backdrop of a massive shift in physician sentiment. Data from the American Medical Association (AMA) underscores this rapid adoption:
- Physician Usage: In 2023, 38% of physicians reported using AI in their practice. By 2026, that figure has surged to 72%.
- Physician Awareness: Awareness of AI capabilities among clinicians climbed from 66% in 2025 to 81% in 2026.
- Workflow Preference: Nearly 40% of physicians now prioritize AI for summarization of research and clinical standards, a 26-point increase since 2024.
This data suggests that physicians are not looking for "autonomous care," but rather "efficiency layers" to manage the crushing cognitive load of modern medicine.
The "Lane Assist" Model of Oncology
Dr. Beg utilizes an analogy that resonates with many in the medical field: "lane assist" for oncologists. Modern oncology is no longer a solo endeavor; a patient’s care team often includes the oncologist, a nurse practitioner, a geneticist, a nutritionist, and a physical therapist. Coordination is difficult, and administrative staff is almost universally under-resourced.
The AI platform acts as an intelligent assistant, offering "nudges" at the point of care:
- Care Gap Identification: Alerting the physician to missing molecular markers for a colon cancer patient.
- Trial Flagging: Automatically identifying potential trial matches based on the patient’s unique genomic and diagnostic profile.
- Efficiency Gains: By handling documentation and preliminary screening, the system grants oncologists back valuable minutes per patient, allowing them to manage higher patient volumes without compromising the quality of interaction.
Technical Architecture: Chaining AI for Accuracy
The efficacy of the system relies on ConcertAI’s sophisticated data pipeline. The platform ingests structured EHR fields alongside unstructured data—pathology reports, clinical notes, and next-generation sequencing (NGS) laboratory reports. This information is processed through a "chain of AI models and agents."
"We use a chain of AI models and agents to parse all that information, understand really challenging concepts like progression, or timelines within a diagnosis journey, and summarize that into a structured data model," explains CEO Eron Kelly.
To ensure trust, ConcertAI employs a multi-layered validation process. One set of agents assesses "abstraction accuracy" (did the model read the chart correctly?), while a secondary layer checks for "clinical coherence" (does the sequence of events make medical sense?). For instance, the system would flag a treatment plan that incorrectly suggests an agent following a treatment modality that would typically not be paired with it. According to Kelly, this architecture currently achieves a precision and recall score of 0.9 or higher.
Implications: The Power of "Ground Shots"
While the industry frequently looks toward "moonshots"—the elusive, singular cure for cancer—Dr. Beg and the ConcertAI team are advocating for a strategy of "ground shots." This involves the systematic, data-driven dissemination of existing treatments and research insights to the patients who need them today.
A prime example of this impact is the platform’s ability to re-evaluate historical data. Because ConcertAI retains the underlying pathology reports, it can identify patients who were previously categorized as HER2-negative based on older scoring criteria but would be eligible for modern, targeted antibody-drug conjugates under current guidelines. This allows oncologists to "reach back" into their patient history to identify individuals who could benefit from life-extending therapies that were not available or understood at the time of their initial diagnosis.
Conclusion: A New Standard for Clinical Operations
The transformation of CancerLinQ into an AI-powered intelligence platform signifies a permanent shift in the oncology landscape. By moving from a passive reporting registry to an active, agentic participant in the clinical workflow, ConcertAI is addressing the fundamental bottleneck in cancer care: the inability of human clinicians to process the sheer volume of emerging data and research in real-time.
As these tools continue to mature, the focus remains clear: providing the clinician with the right information at the right time, minimizing administrative friction, and ensuring that no patient is left behind due to the complexities of clinical research or data fragmentation. In the era of precision medicine, the true innovation lies not just in the drugs themselves, but in the intelligent infrastructure that connects those drugs to the patients waiting for them.
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