In the complex, high-stakes world of modern oncology, the gap between cutting-edge clinical research and day-to-day patient care is often measured in missed opportunities. For over a decade, the American Society of Clinical Oncology (ASCO) sought to bridge this divide through CancerLinQ, a massive initiative designed to aggregate electronic health record (EHR) data into a living, learning system. However, in the rapidly evolving landscape of artificial intelligence, the platform needed more than just data—it needed an engine.
In December 2023, the acquisition of CancerLinQ by ConcertAI, a leader in AI-driven real-world data and oncology research, marked a pivotal shift. What was once a static reporting tool has been transformed into a sophisticated, point-of-care intelligence platform. This evolution is not merely technological; it represents a fundamental change in how oncologists interact with patient data, how clinical trials are populated, and ultimately, how survival outcomes are achieved in the face of increasingly complex cancer biology.
The Chronology of a Transformation
To understand the magnitude of this shift, one must look at the trajectory of CancerLinQ. Launched by ASCO more than ten years ago, the platform’s original mission was to "learn" from the routine patient encounters occurring in oncology practices across the United States. Its primary value proposition for years was automated quality reporting—a software solution designed to help practices track and meet the quality measures required for ASCO certification.
"Before we bought it, CancerLinQ largely just delivered software that automated the measurement of ASCO certification quality measures," explains Eron Kelly, CEO of ConcertAI. It was a digital filing cabinet of sorts, vital for compliance but limited in its ability to influence the actual trajectory of patient treatment in real-time.
Following the December 2023 acquisition, the focus shifted from compliance to intelligence. ConcertAI began integrating its own proprietary AI models into the infrastructure, expanding the platform’s scope to include trial-matching, dynamic research datasets, and, most importantly, clinical decision support (CDS) that operates within the physician’s live workflow. The goal was to move the platform from the administrative back office to the patient bedside.
The Data Engine: Chaining Intelligence for Precision
At the heart of the new CancerLinQ is a robust, AI-driven data pipeline that treats oncology data as a dynamic, rather than static, asset. ConcertAI’s system ingests a massive spectrum of clinical information, ranging from structured EHR fields to highly unstructured content such as physician progress notes, complex pathology reports, and genomic/Next-Generation Sequencing (NGS) laboratory reports.
"We use a chain of AI models and agents to parse all that information," Kelly explains. "We are tasked with understanding really challenging concepts like disease progression or the specific timelines within a diagnosis journey." The result is a structured data model that is updated weekly, ensuring that clinicians are not making decisions based on stale information.
The accuracy of this system is paramount. To ensure clinical trust, ConcertAI employs a "layered check" mechanism. One set of agents evaluates abstraction accuracy—ensuring the model is reading the chart correctly—while a secondary layer monitors clinical coherence, flagging sequences that are medically illogical (e.g., a treatment that contradicts standard protocols). By maintaining a precision and recall rate of 0.9 and higher, the platform aims to provide oncologists with reliable insights that they can act upon without hesitation.
Bridging the Care-Research Gap
Dr. Shaalan Beg, Chief Medical Officer of Oncology at ConcertAI, emphasizes that the platform is designed to reconcile the widening chasm between standard care and clinical research. In the modern era of oncology, the "best" treatment is frequently only available through a clinical trial.
"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," Dr. Beg notes, citing recent ASCO data where a new agent nearly doubled median survival in metastatic pancreatic cancer from six to 12 months.
The platform functions as an "efficiency layer" for overburdened oncology teams. Clinical trial matching, a historically labor-intensive process, has been compressed to a fraction of the time. When the system identifies a potential match, it automatically maps the patient’s clinical data against 20 to 30 specific trial eligibility criteria, providing a transparent link back to the source record. This allows clinical trial coordinators to bypass hours of manual chart-scouring, effectively extending the reach of trials to satellite clinics and community-based practices that were previously underserved.
Lane Assist for the Modern Oncologist
The integration of AI into medicine is no longer a futuristic concept; it is an active, growing reality. According to recent American Medical Association (AMA) surveys, physician use of AI has surged from 38% in 2023 to 72% in 2026. Awareness has followed a similar upward trajectory, rising to 81%.
Dr. Beg uses an automotive analogy to describe the current state of AI in oncology: "For most of the clinical care doctors are asking for right now, it’s more like lane assist—keeping the car in its lane and giving nudges along the way."
These "nudges" represent a significant leap in patient safety and quality control. For instance, the system might alert a physician that a colon cancer patient is missing essential molecular data required for a specific treatment pathway. This is not about the AI taking over the role of the doctor, but about the AI acting as a force multiplier in a system where no single clinician can track every clinical nuance.
"The era of one physician taking care of all your needs is decades over," Dr. Beg says. "We’re not working under the assumption that these tools will autonomously care for patients." Instead, the platform is designed to handle the logistical and information-management burden, allowing the care team—which today includes nurses, geneticists, dietitians, and physical therapists—to function with a higher degree of coordination.
Implications: The Power of "Ground Shots"
Perhaps the most compelling implication of ConcertAI’s work is the potential to revisit patients who were previously considered ineligible for certain therapies. Because the platform retains access to longitudinal pathology reports, it can identify patients who were once classified as HER2-negative under older scoring systems but would qualify for newer, highly effective antibody-drug conjugates under modern criteria.
This represents a "ground-up" approach to cancer care. While the medical community often celebrates the "Moonshots"—the massive, singular breakthroughs—Dr. Beg advocates for what he calls "ground shots": the systematic, rigorous application of the highly effective treatments we already possess to the people who need them today.
By refining biomarkers, surfacing forgotten patient populations, and streamlining the path to clinical trials, ConcertAI is essentially "democratizing" precision medicine. The platform acts as a bridge, ensuring that the benefits of scientific innovation are not confined to elite academic centers, but are instead accessible to patients across the broader CancerLinQ network.
Looking Toward the Future
The transformation of CancerLinQ signals a broader industry trend. Companies like Flatiron Health, Tempus, and Komodo Health are all racing to convert aggregated clinical data into actionable, agentic AI tools. However, ConcertAI’s platform-agnostic approach—being able to ingest data regardless of the underlying EHR vendor or the specific genomic lab—provides a unique advantage in a fragmented healthcare landscape.
As the industry moves forward, the primary hurdle remains the same as it has always been: trust. By focusing on clinical coherence, source-linked transparency, and efficiency-driven workflows, ConcertAI is positioning itself not as a disruptor of the physician-patient relationship, but as its essential support system.
The oncology field is currently experiencing a data explosion that far exceeds the cognitive capacity of any single human. In this environment, tools like the new CancerLinQ are no longer optional "value-adds"; they are becoming the necessary infrastructure for delivering 21st-century medicine. By turning routine clinical encounters into a sophisticated learning and intelligence network, ConcertAI is helping to ensure that the "lane assist" for cancer care keeps the focus where it matters most: on the patient, their survival, and their quality of life.
About the Author
