Sylvester secures BCRF funding to bring an AI 'companion' to breast cancer survivor follow-up

By Zendoric · September 7, 2026.

The Sylvester Comprehensive Cancer Center, the University of Miami's cancer center, has received an award from the Breast Cancer Research Foundation (BCRF, one of the largest private funders of breast cancer research in the U.S.), co-funded by the Dolphins Cancer Challenge — the charitable initiative of the Miami Dolphins football team — to develop My Wellness Support, an artificial intelligence platform designed for the follow-up of breast cancer survivors. The project is led by Dr. Frank Penedo, of Sylvester's Cancer Survivorship and Supportive Care Institute, as the center itself explained on LinkedIn.

The platform is not starting from scratch. It builds on My Wellness Check, a Sylvester program that has already collected data from more than 34,000 outpatient cancer patients. The idea is to cross-reference that data — patient-reported outcomes, clinical information — with an 'AI companion' trained in oncology that detects unmet needs between one appointment and the next, and refers the survivor to the appropriate resource before the problem worsens.

'Our vision is to harness advances in artificial intelligence to expand the delivery of personalized, evidence-based support that helps survivors manage symptoms, improve their quality of life and stay connected with their medical team,' Penedo said. The stated longer-term goal is to turn the project into a scalable model of supportive care that does not depend on the hospital's walls.

It is worth being precise about what we know and what we do not. The source does not detail the size of the grant, a deployment timeline or efficacy data: for now this is funding to develop and validate a tool, not a product already tested on real survivors at scale. That is an important nuance in a field — that of healthcare 'AI companions' — where the institutional announcement usually runs well ahead of the published clinical evidence.

But the problem it targets is real and poorly solved. Cancer care concentrates on diagnosis and active treatment; the 'after' — the years, sometimes decades, in which a survivor lives with physical after-effects, fear of relapse or isolation — is left with far scarcer resources and widely spaced visits. A system that monitors continuously between appointments, supported by data the center already collects, addresses exactly that gap: it does not replace the oncologist, it filters what deserves their attention and when.

The move fits a broader trend in AI in oncology: shifting from detection (reading a mammogram, flagging a nodule) to managing the disease's entire life cycle, including relapse prediction and support after discharge. In general, it is a logical shift: models that already work reasonably well at detecting patterns in imaging or medical records have a lot to contribute to continuous follow-up as well, which is data-intensive but poor in available staff. The risk, as always, is adoption: that the digital divide leaves out older patients or those with fewer resources, that alert fatigue dilutes the important signals, or that an 'AI companion' ends up replacing — for lack of time on the human team's part — the contact it was supposed to reinforce.

In the long run, projects of this kind are precisely the application of AI that interests us most: not the one that promises to cure cancer in one stroke, but the one that makes the years after beating it more bearable, with less friction and more attention where it is really needed. If it works — and that validation is still pending — a model like this could be scaled to other types of cancer and to health systems with far fewer resources than a university center in Miami, which is where the promise of healthcare abundance really starts to be felt.