SAS, the Cary, North Carolina, data and AI software company, and North Carolina State University announced on October 1, 2026 the SAS Think & Do Tank, a research partnership that embeds SAS’ data, AI and analytics expertise in interdisciplinary work at NC State’s College of Agriculture and Life Sciences. NC State Chancellor Kevin Howell unveiled the initiative at an event celebrating SAS’ 50th anniversary. The partnership will apply data and AI to human health as well as nutrition and environmental resilience, and one of its first projects goes after a stubborn problem in drug development: predicting how diseases and potential therapies will behave in people before those therapies reach the clinic.
“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.”
Inside the First Research Effort
The opening project centers on translational predictive biology, a field that combines advanced biological models with data and AI to forecast how diseases and candidate treatments may act in humans. NC State researchers are building a process that links studies in living systems with advanced lab models, including organoids (small, simplified organs grown from cells) and organ-on-chip devices that mimic aspects of human organ function. Translational predictive biology is also the name of one of NC State’s existing Chancellor’s Faculty Excellence Program clusters, though the announcement does not say which faculty or labs will lead the work.
According to the partners, better predictive models could eventually help researchers spot promising treatments sooner, understand why some interventions succeed while others fail, and cut the time and cost of moving therapies toward clinical use. The catch is the data. These experiments generate enormous detail across cells, tissues, molecular pathways and time, yet they draw on relatively few biological subjects. In that setting, conventional AI models can latch onto patterns that fail to hold up across studies or to translate from one biological system to another.
What SAS Brings to the Lab
To tackle that problem, the team plans to test statistical and AI methods designed for small, information-dense datasets. The models are meant to account for biological relationships, quantify uncertainty and show researchers why a model reached a particular conclusion. SAS will act as a technical partner across the research working groups, supplying data and AI software along with expertise and responsible AI guidance. Faculty and students are expected to get hands-on experience applying advanced analytics to active research. Over time, the partners say, the work could also produce AI-ready research datasets that let scientists compare findings across studies and generate new hypotheses.
A Two-Year Pilot Built to Scale
The Think & Do Tank is structured as a scalable two-year pilot. Its first job is to establish a governance and research collaboration model that could later expand to additional disciplines and institutions, according to the release. There is also the hope that the resulting analytical model could eventually be used by other universities or companies. Neither organization disclosed financial terms of the partnership.
