A conceptual visual of digital network connections and complex data pathways representing artificial intelligence implementation in R&D.

Putting AI to Work Across R&D

How Regeneron is turning AI’s potential into practical impact to enhance drug discovery and development.

Regeneron

November 12, 2026

Key Takeaways:

Regeneron teams across R&D are applying AI to enhance decision-making with the goal of helping bring medicines to patients faster.
The Regeneron Genetics Center (RGC) provides a foundation for high-value AI implementation with one of the world's largest collections of de-identified electronic health records linked to molecular data.
In early research and preclinical development, AI helps researchers identify targets, analyze complex datasets and improve operational efficiency.
Clinical teams are applying AI to help make clinical trials more efficient with the goal of getting new medicines to patients faster.
Human expertise remains central to AI implementation.

Imagine being able to efficiently search vast amounts of data for important clues that could shape the development of new medicines. Picture scientists spending less time on routine, time-consuming tasks and more time on work that demands human ingenuity and deep strategic thinking. And, before a clinical trial even begins, consider the value of seeing around corners—equipping teams with sharper insights to guide important early decisions and mitigate potential challenges as they develop protocols and conduct clinical research.

Across Regeneron’s research and development (R&D) organization, teams are putting AI to work against real scientific and operational challenges. Combined with Regeneron’s differentiated data, scientific rigor and human expertise, AI can help us work faster and make better-informed decisions as we discover and develop new medicines.

“Everyone has access to the same AI models. What sets Regeneron apart is our data and the scientists who know which questions to ask of it. AI amplifies what Regeneron has spent decades building.”

Ryan Steinberger, Chief Digital & Technology Officer

Why AI Needs Robust, High-Quality Data

AI is only as powerful as the data behind it. Through the Regeneron Genetics Center® (RGC), we’ve built one of the world’s largest collections of de-identified electronic health records linked to molecular data, including exome and genome sequencing, proteomics and imaging. We work to curate and assess the dataset for bias to support scientific insights.

“We invest significant time defining the right questions to ask, organizing our genetic and health data and bringing it all together with AI and other computational approaches. When questions, data and approach align, AI and our scientists can answer important scientific questions and generate truly new insights. The result is remarkable.”

Goncalo Abecasis, Senior Vice President, Chief Genomics and Data Science Officer, RGC

As these datasets continue to grow, AI helps our researchers analyze them more efficiently. The resulting insights support target discovery, validation and indication expansion. These efforts have already contributed to important discoveries such as CIDEB, a potential target for liver disease, and FNIP1, a potential target for cardiometabolic disease as highlighted in our recent Nature publication.

Putting AI to Work in Research

AI is creating new opportunities across research—from uncovering biological insights and designing molecules to analyzing complex data and accelerating everyday scientific work.

Our goal is not simply to adopt AI, but to democratize its use by putting powerful new capabilities directly into the hands of scientists. Increasingly, the potential to make an impact starts with a compelling scientific idea and the ability to leverage AI tools to pursue it. By combining AI with our scientific expertise and experimental capabilities, we can empower more scientists to explore ideas, ask better questions and accelerate discovery.

“We are building a digital and AI-enabled R&D organization where data and knowledge flow seamlessly, our collective knowledge is at the fingertips of every scientist, scientists spend more time on science and great ideas move faster from insight to impact.”

Hanne Bak, Senior Vice President, Product, Analytical and Process Development

Across Research, we are turning this vision into practice by prioritizing high-impact applications, building shared capabilities and enabling scientists to use AI effectively and responsibly.

Rethinking Clinical Trials: Integrated AI Tools

Clinical trials have become increasingly complex, creating new challenges for sponsors, investigators, sites and participants. At Regeneron, we’re reengineering the workflow to use AI and automation purposefully without compromising rigor or oversight. We’re applying a human-in-the-loop model that combines the efficiencies of AI with the expertise of our teams, allowing them to devote more time to high-value work.

“AI and automation have the opportunity to remove bottlenecks in clinical development. But AI is not a silver bullet, nor a substitution for expertise. It’s an enabler that will help clinical teams make faster, better decisions and free their time to focus on areas where human expertise matters most."

Bari Kowal, Senior Vice President, Development Operations & Portfolio Management

We use AI to help design protocols with the realities of participants and research sites in mind, assess which clinical trial locations may be well positioned to conduct a study and flag factors to consider that could create challenges for enrollment, safety or execution. We are rethinking our process to incorporate AI to help teams review complex data and reduce time spent on routine, administrative tasks while upholding quality and safety standards. We’re already seeing the impact of these efforts, including improvements in site selection, enrollment and a reduction in time spent on standard tasks. Continued investments in our global digital and data capabilities, including our new Global Capability Centre in Hyderabad, strengthen the infrastructure needed to expand the impact of these efforts.

Shaping What’s Possible in R&D with AI

AI is playing a growing role across Regeneron’s R&D organization, and we are applying the same rigor to using AI to guide our most important decisions. Its greatest value comes when it strengthens human expertise rather than substitutes for it. By focusing on practical applications that support our science and teams, AI has real potential to support the acceleration of drug discovery and development.