Ken Dec, CMO, mTuitive
ASCO 2026 made it crystal clear that the next wave of innovation in oncology will be won or lost on one thing – whether we can turn rich pathology and biomarker findings into structured, computable data that actually flows into AI, trials, and clinical decision‑making at scale. What we heard in dozens of conversations is that everyone is investing in AI, precision therapeutics, and real‑world evidence, but they are all hitting the same bottleneck in unstructured reports.
1. Precision medicine is outpacing pathology data
Across sessions and hallway conversations, we saw an explosion of biomarker‑driven therapies and nuanced disease definitions – HER2‑low, HER2‑ultralow, and increasingly granular molecular signatures that directly shape treatment choices. Yet many of these critical details still live as prose in pathology reports, not as discrete fields that downstream systems can reliably use.
Oncologists, pharma teams, and diagnostic manufacturers told us the same story in different ways: precision medicine is only as good as the data it sits on. When an eligibility‑defining biomarker is buried in paragraph three of a scanned PDF, it might as well not exist for AI models, trial matching engines, and population‑level analytics.
Top lesson: precision medicine now requires precision data, not just better drugs
2. AI is hungry, but starved for computable inputs
ASCO 2026 was packed with AI content, from digital pathology risk models to “glass‑box” AI explanations and multimodal biomarkers that combine images with clinical data. The ambition is huge: earlier detection, better risk stratification, more personalized treatment selection, and smarter decision support at the point of care.
But again and again, presenters and vendors came back to one blocker: the lack of consistent, structured, machine‑readable data from core clinical systems, especially pathology. Models cannot be safely deployed or scaled when their inputs vary by site, by pathologist, or by reporting template, and when key fields are inconsistently captured or missing altogether.
Top lesson: AI in oncology does not just need more algorithms, it needs computable pathology and biomarker data as a first‑class input
3. Real‑world evidence is only as real as the data capture
The meeting’s focus on translating science into impact for every patient was reflected in a strong emphasis on real‑world evidence, pragmatic trials, and outcomes research. Regulators, payers, and life sciences companies are all leaning into RWE to understand how therapies perform outside of tightly controlled trials and across diverse populations.
Yet the conversations we had with RWE teams and clinical leaders underscored a hard truth: you cannot do serious evidence generation on top of loosely documented, narrative‑heavy reports. If tumor characteristics, staging elements, and biomarker statuses are recorded differently in every report, or not discretely captured at all, any cross‑site or longitudinal analysis becomes slow, expensive, and potentially unreliable.
Top lesson: real‑world evidence starts with standardized data capture at the source, not with cleaning data months or years later
4. Clinical trials are becoming biomarker‑first
Another clear theme at ASCO 2026 was the acceleration of biomarker‑driven and basket trials, as sponsors push to find the right patients for increasingly targeted therapies. Enrollment criteria are tightening around specific molecular alterations, expression thresholds, and composite profiles that depend heavily on pathology and biomarker readouts.
Sponsors, CROs, and health systems all described the same friction: trial‑eligible patients are hiding in plain sight because their data is locked in free‑text or scanned documents that are not easily queried. Sites that have invested in structured pathology data and computable biomarker capture are already reporting faster feasibility assessments and more efficient patient identification.
Top lesson: if trial enrollment is going to keep pace with biomarker innovation, structured pathology and biomarker data must become the default, not the exception
5. Pathology is becoming the starting point, not the endpoint
From our perspective at mTuitive, one of the most important shifts at ASCO 2026 was how often pathology was discussed not as a service line, but as a strategic data engine for the entire oncology ecosystem. Presenters emphasized the need to empower pathologists as core contributors to precision medicine and to equip them with tools that make structured, standardized reporting the easiest path, not an extra burden.
In conversation after conversation, it was clear that the diagnostic report is no longer the end of the story – it is the beginning of downstream clinical decisions, AI applications, therapeutic development, and real‑world evidence programs. When that report is structured, computable, and interoperable, it becomes the connective tissue between pathology, oncology, life sciences, and population‑scale learning health systems.
Top lesson: the future of oncology data is being written inside the pathology report, and the next step is to make that report inherently structured and actionable
Where mTuitive fits into this ASCO 2026 story
For us, ASCO 2026 validated what we see every day with our customers across health systems, pathology groups, and life sciences partners. High‑quality oncology care now depends on turning rich narrative findings into structured, computable data that can power AI, precision therapeutics, clinical trials, and real‑world evidence, without adding friction to the pathologist’s workflow.
That is the problem mTuitive exists to solve: helping pathology and oncology teams capture the right data, the right way, the first time, so it can be reused everywhere it needs to be in the oncology ecosystem. Coming out of ASCO 2026, we are more convinced than ever that structured, standardized pathology and biomarker data is not a nice‑to‑have – it is the backbone of the next decade of cancer innovation.
mTuitive is revolutionizing reporting, data, and analytical software for digital pathology and surgical oncology. Their innovative synoptic reporting software allows for the aggregation of a patient's data with thousands of different reports, giving medical professionals new insights and understanding to elevate the standard of care and benefit the patient. Learn more at www.mtuitive.com.
#ASCO2026 #Oncology #Pathology #PrecisionMedicine #DigitalPathology #CancerCare #Biomarkers #HER2 #ArtificialIntelligence #RealWorldEvidence #ClinicalTrials #HealthcareData
