Research partnership applies data and AI to speed the path to new treatments and strengthen nutrition and environmental resilience
CARY, N.C., Oct. 1, 2026 /PRNewswire/ — Fifty years after SAS grew out of an agricultural research project at North Carolina State University, the two organizations are launching a new research partnership to apply trusted data and AI to challenges in human health, nutrition and environmental resilience.
SAS and NC State today announced the SAS Think & Do Tank, integrating SAS’ data, AI and analytics expertise into interdisciplinary research through NC State’s College of Agriculture and Life Sciences. The initiative is designed to move promising discoveries toward real-world impact while building trusted and responsible AI practices into the research from the start.
“The next generation of innovators will need more than powerful technology. They’ll need the judgment to use it responsibly,” said SAS CEO Jim Goodnight. “By connecting NC State’s interdisciplinary research with SAS’ data, AI and industry expertise, we can help students and researchers build trusted approaches to problems that matter.”
“This partnership extends a relationship that has shaped discovery in North Carolina for decades,” said NC State Chancellor Kevin Howell. “True to our Think and Do spirit, NC State and SAS will collaborate to create new opportunities for students, faculty and industry partners to apply AI in service of society.”
Can AI help promising treatments reach patients faster?
One of the first research efforts will focus on translational predictive biology, an emerging field that uses advanced biological models, data and AI to better predict how diseases and potential treatments may behave in humans.
NC State researchers are building a process that connects studies in living systems with advanced lab models, including organoids, small, simplified versions of organs grown from cells, and organ-on-chip technologies that mimic aspects of human organ function.
The long-term promise is significant: Better predictive models could help researchers identify promising treatments earlier, understand why interventions succeed or fail, and reduce the time and cost required to move new therapies toward clinical use.
But the work also creates a difficult data challenge. Researchers can collect enormous detail across cells, tissues, molecular pathways and time, but from relatively few biological subjects. Conventional AI models can struggle in this environment, identifying patterns that may not hold up across studies or translate from one biological system to another.
The team will explore statistical and AI approaches designed for these complex datasets. The models will aim to account for biological relationships, quantify uncertainty and help researchers understand why a model reaches a conclusion.
The effort will give researchers more actionable insight into biological responses and better evidence for deciding which potential interventions warrant further study.
Over time, the work could also help create AI-ready research datasets that allow scientists to compare findings across studies, identify new patterns and generate new hypotheses.
SAS will serve as a technical partner across the research working groups, providing data and AI software, expertise and responsible AI guidance. Faculty and students will gain hands-on experience applying advanced analytics to active research while emphasizing ethical data practices and transparency.
A partnership 50 years in the making
Designed as a scalable two-year pilot, the Think & Do Tank will establish a governance and research collaboration model that could eventually extend to additional disciplines and institutions. It aligns with SAS’ broader Trust in Innovation efforts and NC State’s “Think and Do” approach to turning knowledge into impact.
For SAS, the partnership brings its story with NC State full circle: returning to the place where the company began to invest in the next generation of research, technology and talent.
Learn more about how SAS supports students, educators and independent learners in developing data and AI expertise.
About SAS
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Editorial Contact:
Shannon Heath
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919-531-2676
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