SUNY Funds Binghamton’s AI Cancer Detection and RNA Therapy Innovations

On September 14, the State University of New York announced a new tranche of seed money from its Technology Accelerator Fund. In total, $400,000 will be spread across five campuses, and Binghamton University walked away with two sizable slices of that pie.

One of the recipients is Nancy Guo, an assistant professor in the Department of Biomedical Engineering. She’s putting artificial intelligence to work on something we all dread: cancer. Her system, dubbed ClinSegAI, combs through ordinary pathology slides and flags subtle biomarker patterns that might otherwise slip by. In plain language, the software could tell doctors "hey, this looks suspicious" weeks or even months before a tumor becomes obvious.

Guo’s approach leans on deep‑learning models that have been trained on thousands of digitized slides. The hope is that, once the algorithm is polished, clinics across New York—and eventually the nation—could run a quick scan on a standard tissue sample and get an early‑warning score. Early detection, as we all know, translates into a broader range of treatment options and, frankly, better odds of survival.

Across the campus, another scientist is tackling a different kind of hurdle. John Fetse, a post‑doctoral researcher in the School of Pharmacy, is fine‑tuning the delivery vehicle for RNA‑based therapies. Current RNA drugs ride on lipid nanoparticles that, while effective, can irritate cells and cause unwanted side effects. Fetse’s tweak involves stitching specific amino acids directly into the lipid shell, a move that promises to smooth the ride and reduce toxicity.

"Think of it like adding a cushion to a delivery truck," Fetse explained in a recent press release. "The cargo—our therapeutic RNA—gets there safer, and the road (our body) suffers less wear and tear." Early lab tests suggest the modified particles slip into target cells more efficiently, which could mean lower doses and fewer side effects for patients.

The SUNY Board of Trustees highlighted the strategic value of these projects in their statement, noting that “revolutionary breakthroughs fuel economies and empower communities.” That phrasing sounds grand, but the reality is more tangible: both initiatives have clear pathways toward commercialization, whether through startup spin‑offs or licensing deals.

Binghamton President Anne D'Alleva echoed the sentiment, emphasizing that the university’s “new technologies could have a real impact on delivering timely, safer, and more effective treatments.” She added a personal note of gratitude to SUNY, saying the funding helps push discoveries out of the lab and into the hands of doctors and patients who need them.

While the $400,000 figure may seem modest compared to multi‑million‑dollar grants, for seed‑stage research it’s a lifeline. It lets Guo and Fetse hire a research assistant, rent additional compute time, and push prototypes toward the next round of validation. And, perhaps most importantly, it signals confidence from a public system that it’s willing to bet on home‑grown innovation.

In the coming months, both teams plan to publish their findings and begin dialogues with industry partners. If all goes well, we might soon hear about a Binghamton‑born AI tool on hospital screens and a gentler RNA therapy in clinical trials—proof that a modest boost from SUNY can ripple far beyond the university’s ivy‑covered walls.