Riccio Digital Medicine and Health Technology Initiative Awards Inaugural Pilot Grants to Joint UMass Amherst and UMass Chan Teams

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Daniel J. Riccio and Chancellor Javier Reyes at the rollout of the Riccio Digital Medicine and Health Technology Initiative

Research into a wearable biosensor to help manage gout and artificial intelligence tools to predict the progression of age-related macular degeneration are among the first pilot projects to be funded through the Riccio Digital Medicine and Health Technology Initiative, a collaboration between the University of Massachusetts Amherst and UMass Chan Medical School. Four projects received inaugural awards, including two led by faculty in the Riccio College of Engineering and two led by faculty in the Manning College of Information and Computer Sciences.

UMass Amherst, the Riccio College of Engineering, and UMass Chan are providing funding for this year’s four awarded pilot projects, each receiving $100,000 for a 12-month project term. It is expected that these projects will lead to deeper research collaborations between the campuses and follow-on funding from external sources, such as the U.S. National Institutes of Health.

As part of his historic $50 million donation to the university in 2025 to name the college of engineering, Daniel J. Riccio ’86, ’24MS, designated that a portion of his gift provide seed funding to catalyze new initiatives, including this initiative on digital health research conducted by teams comprised of scientists from both campuses.

“My investment in the Riccio College of Engineering and UMass was inspired in part by the belief that combining the strengths of UMass Amherst and UMass Chan Medical School could accelerate the development of innovative digital health technologies that improve patient care and make a meaningful impact on the common good,” said Riccio. “These inaugural pilot projects demonstrate what’s possible when we bring talented researchers together across disciplines and campuses. I’m excited to see where these collaborations lead and the impact they can have.”

“These projects represent a terrific collaborative portfolio in digital medicine spanning chronic disease management, population health, metabolic health and disease prediction, with clear potential impacts on human health,” said Mike Malone, UMass Amherst vice chancellor of research and engagement.

“The goal of the initiative is to leverage the strengths of our multicampus system to become a driver for where digital technologies are heading,” said Govind Srimathveeravalli, director for the UMass Amherst Center for Personalized Health Monitoring. “As the share of senior citizens in our commonwealth grows, it is important they are provided accessible and quality healthcare so they may age in place with their families. Digital health technologies are central to this vision, where the engineers from UMass Amherst and the clinicians from UMass Chan are actively collaborating to advance digital health technologies.”

“We’re grateful to Mr. Riccio for his philanthropic support of UMass,” said David D. McManus, Chan ’02M.D., Chan ’12Sc.M., MBA, Chancellor of UMass Chan Medical School. “The initiative will enhance the partnership between UMass Chan and UMass Amherst and will lead to a deeper understanding of how digital healthcare can improve human lives.” 

The two Riccio College of Engineering pilot projects are:

A Machine Learning-Assisted Wearable Biosensor for Multiplexed Biomarker Monitoring

Led by Nianqiang Wu, distinguished professor of chemical and biomolecular engineering in the Riccio College of Engineering at UMass Amherst, co-PI Chao Zhao, associate professor of chemical and biomolecular engineering, and Timothy McAlindon, M.D., M.P.H., professor of medicine at UMass Chan

Management of gout—a painful type of arthritis caused by a buildup of uric acid crystals in the joints—depends on timely monitoring of both urine and the kidneys through intermittent clinic-based blood tests, which cannot capture dynamic biomarker changes during daily activities, acute flares and recovery phases. This project will develop a wearable sensor platform for stage-specific monitoring of metabolic waste products, enabling personalized management of gout.

Leveraging AI in OCT/OCTA Ocular Images to Determine Biomarkers of Progression to Advanced Age-Related Macular Degeneration and Apply to Clinical Practice

Led by Joyita Dutta, professor of biomedical engineering in the Riccio College of Engineering at UMass Amherst and Johanna M. Seddon, M.D., Sc.M., FARVO, FASRS, the Dr. Eileen L. Berman Foundation Chair in Biomedical Research II and professor of ophthalmology & visual sciences at UMass Chan

People with early stages of age-related macular degeneration (AMD) often have normal vision, making it difficult to predict, before vision loss occurs, who will progress to more advanced stages and blindness. Optical coherence tomography (OCT) and OCT angiography (OCTA), used to diagnose and monitor many retinal diseases including AMD, is a time-consuming and tedious process for clinicians. This research will use AI to incorporate OCT/COTA images and baseline clinical, demographic and lifestyle features to predict progression from non-advanced AMD to advanced AMD.

This story was first published by the UMass News Office.