Nine Diagnostics co-founder Daniel A. Heller, PhD was featured in Women’s Health, in an article examining why ovarian cancer remains so difficult to detect early and how emerging nanosensor technology could change the story.
Ovarian cancer ranks among the top five causes of cancer death for women in the United States, yet has no reliable routine screening test for asymptomatic women. Unlike breast cancer, there is no standard diagnostic tool available in clinical practice. Nearly 80% of cases are first diagnosed at advanced stages, when treatments are less effective and outcomes are substantially worse. The disease produces vague symptoms (bloating, pelvic discomfort, changes in digestion) that are easily mistaken for other common conditions, and ovarian cancer is thought to originate in the fallopian tubes, adding further complexity to early detection.
Heller, who heads the Cancer Nanomedicine Laboratory at Memorial Sloan Kettering Cancer Center, spoke to the funding gap that has long constrained progress. “There is certainly not enough funding for ovarian cancer, and also not enough for detection and prevention of cancer in general,” he told Women’s Health. “There have been foundations that help to fill the gap, but generally not enough resources for prevention and early detection research.” His lab has been developing carbon nanotube nanosensor arrays that emit distinct fluorescent signals when exposed to molecules in blood, with machine learning applied to decode those signals and identify molecular fingerprints that differentiate cancer-associated samples from healthy ones. In early studies, the approach has outperformed CA-125, the long-standing but unreliable current clinical biomarker for ovarian cancer. The lab is also exploring whether the platform could one day detect precancerous changes in the fallopian tubes, which could shift detection years earlier than is currently possible.
The scientific foundation underlying this work is the same that drives Nine Diagnostics. Heller’s lab, together with co-founder Mijin Kim, PhD, published a landmark clinical validation of the nanosensor platform in Nature Biomedical Engineering in 2022, demonstrating 87% sensitivity and 98% specificity for high-grade serous ovarian cancer detection across 269 patient samples, outperforming CA-125 and establishing a clinical benchmark for the approach. Nine Diagnostics is advancing this platform toward broader oncology applications, with the same AI-enabled, multi-omic nanosensor architecture at its core.
About Nine Diagnostics
Nine Diagnostics is an AI-enabled multi-omic nanosensor company advancing precision medicine. The platform simultaneously captures proteomic, metabolomic, and lipidomic signals alongside patient clinical context to generate a multi-omic fingerprint, using machine learning to identify disease-relevant patterns without requiring prior knowledge of which biomarkers matter. This enables pre-treatment patient stratification, on-treatment response monitoring, and post-treatment minimal residual disease detection. Founded by Freddy T. Nguyen, MD, PhD (CEO), Daniel A. Heller, PhD (CSO), and Mijin Kim, PhD (Scientific Advisor), Nine Diagnostics is based in Cambridge, Massachusetts.