Prognosia’s AI-based imaging tech could improve prevention, early detection of breast cancer
An innovative biotech startup founded by researchers at Washington University School of Medicine in St. Louis has been acquired by Lunit, a leading company in developing AI-based technologies for cancer prevention and early detection. The WashU startup, Prognosia, was created to develop software that harnesses AI to analyze mammograms and more accurately predict a woman’s five-year risk of developing breast cancer.
The startup’s first software package, Prognosia Breast, received Breakthrough Device Designation from the Food and Drug Administration (FDA) earlier this year, putting it on a fast track to full market approval. Lunit’s acquisition of Prognosia can help accelerate the final steps of the process to bring the technology into the clinic.
Prognosia was co-founded by Graham A. Colditz, MD, DrPH, the Niess-Gain Professor of Surgery at WashU Medicine and associate director of prevention and control at Siteman Cancer Center, based at Barnes-Jewish Hospital and WashU Medicine; and Shu (Joy) Jiang, PhD, an associate professor of surgery in the Division of Public Health Sciences in the Department of Surgery at WashU Medicine and a research member at Siteman.
“We are excited to work with Lunit to bring this technology to the clinic,” Jiang said. “Lunit already has the infrastructure in place to streamline production and clinical implementation of our software that would be extraordinarily difficult for a new startup to build from scratch. Integrating our software into their existing systems could help this new technology get into the hands of physicians and patients very quickly.”
The system produces a five-year breast cancer risk score that makes it possible to compare a woman’s personalized risk to an average risk based on national breast cancer incidence rates. This provides a meaningful estimate that is aligned with the U.S. national risk reduction guidelines, so that clinicians will know what options to discuss if a patient’s breast cancer risk is elevated.
“Improved risk prediction can help early detection, which has the potential to increase the likelihood of successful treatment that is less disruptive to people’s lives,” said Colditz, an internationally renowned cancer prevention researcher who has led the field for decades. “We recognized that there is a tremendous wealth of information about breast cancer development already stored and continuing to be newly collected in the form of regular mammograms. Until recently, there was no way to use this information to inform risk prediction or to develop new and better prevention strategies.”
Improving Accuracy
Past research led by Colditz and Jiang has shown their system is more than twice as accurate as the standard method of identifying individuals at high risk of developing breast cancer over the next five years. The standard method is based on questionnaires that include factors such as age, race and family history of breast cancer. Research also has shown that the technology maintains its high performance across multiple demographic groups, including among people of diverse races, ages and differing breast densities.
These results led to the technology’s recent FDA Breakthrough Device designation, which provides an accelerated review process for full market approval with the goal of giving patients and clinicians access to promising new medical devices sooner. The designation recognizes that the software already has undergone rigorous testing and has shown excellent promise in its potential to improve clinical care.
The developers said the technology could be easily integrated into existing clinical workflows and is compatible with both types of mammogram imaging available: the four 2D views of the breast produced by full-field digital mammography and the synthetic 3D view of the breast produced by digital breast tomosynthesis.
A Roadmap for Growth
Colditz and Jiang worked with WashU’s Office of Technology Management (OTM) to found their AI-based biotech startup.
“Prognosia is a superb example of harnessing all the resources available to WashU faculty to accelerate the launch of a company,” said Nichole R. Mercier, PhD, assistant vice chancellor and managing director of OTM. “Dr. Colditz and Dr. Jiang were proactive in adapting and learning through the resources and guidance of WashU’s OTM and the entrepreneurship ecosystem of St. Louis. Through Lunit’s acquisition of Prognosia, we’re excited to see this powerful startup venture become even better positioned to make transformative improvements in breast cancer risk estimation, prevention and early detection.”
Colditz and Jiang said Prognosia would not have been possible without OTM’s GAP funding program, which allowed them to do the work required for the FDA’s Breakthrough Device designation, as well as support from BioGenerator Ventures, which provided both financial support and expertise in business strategy from Entrepreneur-in-Residence David Smoller, PhD.
“With the guidance of OTM and David Smoller, we broadened our perspective beyond the technical aspects of the software to focus on the needs of the health-care providers who will use it to care for patients,” Colditz said. “That shift in mindset has been crucial to developing a technology that’s truly useful in the clinical setting.”
Colditz and Jiang will hold advisory roles at Lunit during the pre-market review process that precedes full FDA approval of the technology and for ongoing development projects. The regulatory plan includes an initial submission for the static model of risk prediction based on mammograms taken at a single timepoint, with a roadmap to expand functionality of the software by analyzing mammograms from the same person taken at multiple timepoints to improve the accuracy of the prediction.
