Jun 11, 2026
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Tampa’s Moffitt Cancer Center Tests AI Tool

Tampa’s Moffitt Cancer Center is turning to artificial intelligence to build better treatment plans for patients with multiple myeloma, a complex and rare blood cancer.

Personalized Care

Doctors at the center are using a new artificial intelligence platform to personalize care for patients. The process begins in the lab, where teams take extra samples of cancer cells, break them apart, and treat them in a dish against 31 different drugs or drug combinations.

According to Dr. Ken Shain, a clinical investigator and physician at Moffitt Cancer Center, the AI tool can significantly speed up the process of finding the most effective treatment for each patient. "Something that would take us five years to do for a thousand patients takes us hours now," he said.

The artificial intelligence tool looks at a patient’s genetics, clinical data, and specific drugs to help doctors put the puzzle pieces together quickly. By running the numbers for thousands of patients at once, the technology provides critical information within six days to help doctors build a tailored treatment plan.

Expanding Patient Care

While the AI tool is currently being used to help individual patients, the team at Moffitt Cancer Center hopes to expand its use to the global public in the future. However, this will require going through several regulatory levels.

Ariosto Silva, a senior member and Moffitt researcher, emphasized the importance of patient participation in research. "Whenever you have a chance to actually consent to giving samples for research, or your data as well, the clinical history data, please do so, it makes a big difference," he said.

The team also emphasized that AI tools are designed to assist medical professionals, rather than replace human judgment. "But it’d be even better if I had a way to make that decision easier and based on more information," Dr. Shain said. "That’s what we hope AI does."


Original reporting: Tampa Bay Florida News (HLL/CB) — read the source article.

OBBM Network Editorial Staff

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Editorial team behind OBBM Network — independent, hyper-local journalism syndicated through HyperLocalLoop and OBBM Network TV.

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