Cancer Research Redefined: AI Titans Forge Massive Data Alliance

CAMBRIDGE, Mass. & BOSTON – January 12, 2026 – In a landmark move poised to reshape oncology research, AI and real-world data leader ConcertAI has joined forces with precision medicine pioneer Foundation Medicine. The collaboration integrates vast stores of clinical and genomic data, creating what the companies describe as the largest and most comprehensive clinically-linked oncology dataset, encompassing nearly half a million patients.

This strategic alliance aims to tackle one of the most pressing challenges in modern medicine: the soaring complexity and cost of developing new cancer therapies. By merging ConcertAI’s deep longitudinal clinical data with Foundation Medicine’s extensive genomic testing portfolio, the partnership promises to equip life science researchers with an unprecedented tool to accelerate drug development and bring personalized treatments to patients faster.

A New Era of Data-Driven Oncology

The collaboration comes at a critical time for the biopharmaceutical industry. Drug developers are under immense pressure to innovate more quickly while navigating tighter budgets and increasingly complex clinical trials. The traditional R&D model, often fraught with guesswork in its early stages, is proving too slow and inefficient for the era of precision medicine.

This new integrated dataset is designed to provide a panoramic view of the cancer patient's journey, from pre-diagnosis and initial genomic profiling through the full course of treatment and long-term outcomes. ConcertAI brings its high-quality electronic health record (EHR) data, which it notes is curated for its socioeconomic, ethnic, and geographic diversity. Foundation Medicine contributes its de-identified multimodal dataset, derived from its FDA-approved genomic tests that are capable of detecting all four major classes of genomic alterations.

“Drug developers are increasingly pushed to accelerate their research pipelines but require more robust insights into both early genomic signals and patient outcomes to make this a reality,” said Eron Kelly, CEO of ConcertAI. “By combining the largest and deepest set of clinical data with genomic insights, including whole slide imaging, we can help teams set a clearer plan and speed up their projects.”

Navigating a Crowded and Competitive Landscape

While the claim of creating the “largest and most comprehensive” dataset is bold, the partnership firmly establishes ConcertAI as a top-tier competitor in the fierce oncology real-world evidence (RWE) market. The combined asset of nearly 500,000 clinically-linked patient records is a formidable resource. However, the field is crowded with well-funded and highly capable players.

Companies like Tempus have built massive data libraries, claiming over 40 million de-identified research records and deep integration with a majority of U.S. academic medical centers. Similarly, Flatiron Health, a recognized leader in cancer RWE, cites a network encompassing over 5 million patient journeys. Notably, Flatiron has its own existing data partnerships, including a Clinico-Genomic Database with Foundation Medicine and a separate Clinical-Molecular Database with Caris Life Sciences, highlighting the intricate web of alliances shaping the industry.

This new collaboration between ConcertAI and Foundation Medicine can be seen as a strategic power play to consolidate data dominance. By creating a distinct and deeply integrated offering, the partners are betting they can provide unique insights that differentiate them from competitors and set a new standard for data-driven translational research.

The Power of Integrated Genomic and Clinical Insights

The true value of the partnership lies not just in the volume of data but in its depth and synergy. The combined dataset includes not only raw genomic sequences but also gene expression data, immunohistochemistry (IHC) results, and whole-slide pathology images. Linking this molecular-level information with ConcertAI’s rich clinical data—which includes treatment histories, lab results, and outcomes—allows researchers to ask and answer more complex questions than ever before.

This integration is critical for unlocking the full potential of precision medicine. Studies have shown that drug candidates developed using genomic biomarkers have more than double the success rate of those without. By leveraging AI to analyze these vast, integrated datasets, researchers can identify novel drug targets, discover biomarkers to predict patient response, and design more efficient clinical trials. This can shorten drug development timelines by years and significantly reduce costs.

“By integrating our high-quality genomic data with ConcertAI's electronic health data, we have created one of the most powerful new real-world data sets that enables insights to be turned into strategic decisions at critical milestones for our partners,” said Dan Malarek, CEO of Foundation Medicine. “AI is the future and through our AI-driven analytical capabilities via FoundationInsights®, our biopharmaceutical and research partners can access the right data when they need it and uncover answers faster.”

Regulatory Tailwinds and Ethical Hurdles

This major data-sharing initiative is buoyed by a favorable regulatory climate. Global regulators, including the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA), are increasingly embracing RWE in their decision-making processes. In 2024, a reported 82% of drug submissions to the FDA included RWE, signaling a clear shift in how new therapies are evaluated and approved. This regulatory acceptance provides a powerful tailwind for companies like ConcertAI and Foundation Medicine, validating their investment in high-quality, large-scale data assets.

However, the path forward is not without significant challenges, particularly concerning ethics and privacy. Genomic data is uniquely sensitive; it is personal, permanent, and carries implications not only for the individual but also for their family members. While the companies stress that all data is de-identified, the risk of re-identification, though small, is a persistent concern in the age of powerful data-linking technologies.

Navigating the complex patchwork of data privacy laws, such as HIPAA in the U.S. and emerging state-level regulations, is paramount. Ensuring robust patient consent and maintaining public trust are critical for the long-term sustainability of such data-driven research models. As these powerful datasets grow and AI tools become more sophisticated, the industry will face mounting pressure to uphold the highest standards of data stewardship and ethical responsibility.