New USF study tests whether AI can reliably predict immune responses

Key takeaways:

• The study shows why AI tools require more real-world testing beyond lab data before they can be trusted in medicine.
• Tools like PanPep AI can help predict how the immune system targets disease but can still miss or misread important signals.
• Better-validated AI could speed up drug discovery and immunotherapy, but it’s not ready to guide patient care on its own.

TAMPA, Fla. (May 6, 2026) – Artificial intelligence is increasingly being used to help scientists accelerate drug discovery and search for new treatments. But for AI tools to work effectively, researchers need to know whether they can be validated and applied in real-world situations.

A research team at the University of South Florida is taking a step in that direction by merging AI and immunology in ways that could enhance oncology treatment and the development of new drugs and vaccines.

In an embargoed new study publishing Wednesday, May 6, at 5 a.m. ET in Nature Machine Intelligence, researchers at the USF Health Morsani College of Medicine examined how well AI tools can predict one of the immune system’s most important jobs: recognizing when something does not belong in the body.

That process is central to fighting infections and plays a major role in the development of immunotherapies, which are treatments designed to help a patient’s own immune system attack disease.

“AI tools are playing an increasingly important role in helping researchers develop vaccines, drugs and cancer therapies,” said Dong Xu, professor in the USF Health Informatics Institute. “However, if these tools aren’t carefully tested in real-world conditions, they can produce misleading or biased results.”

The study was led by Xu and Fei He, assistant research professor also with the USF Health Informatics Institute. Xianyu Wang, an intern from the University of Missouri-Columbia, was also a co-author.

Working with an AI model called PanPep — short for Pan-peptide meta learning — the researchers developed a systematic and comprehensive evaluation framework for testing how well computational tools can predict whether certain cells in the body will recognize and respond to antigens, which substances that trigger immune responses.

The question is crucial to drug discovery, because the immune system’s ability to recognize these targets helps determine whether the body can detect and respond to infections, tumors or vaccines.

Their new framework can be applied to a broad class of immunology prediction problems, including peptide–HLA (human leukocyte antigen) binding; peptide–T-cell receptor interaction; antigen presentation; and other peptide- or antigen-driven interactions. These vital processes help immune cells identify what belongs in the body and what may be a threat.

“Our study tested how well AI tools can predict an important immune-system interaction that could help guide the development of cancer immunotherapies and vaccines,’’ He said. “Our findings highlight the strengths and weaknesses of current AI approaches and provide guidance for building safe, more reliable AI tools for healthcare.”

Immune cells recognize and react to antigens, which are proteins on bacteria, viruses or tumor cells that can act as foreign markers, alerting the immune system to a possible threat.

Adaptive immune cells, including T and B cells, use specific receptors to recognize harmful invaders such as viruses, allergens, toxins or cancer cells. Other immune cells ingest these invaders, break them into pieces of antigens and present those pieces to activate a targeted immune defense.

The team used PanPep and other tools to predict how T-cell receptors behave in binding to antigens. Developed to address the challenges of limited data the tool can create scenarios to predict binding for unseen or rare peptides, which are small chains of amino acids that can serve as key immune-system targets.

Accurately predicting peptide and T-cell receptor binding allows scientists to identify and design the right “trigger” peptides for specific immune cells. Those trigger peptides could accelerate immunotherapies and save lives.

By narrowing down the best candidates for laboratory testing, researchers can reduce the need for large-scale biological experiments that are time-consuming and costly.

The USF research represents a significant step toward more reliable AI-guided, personalized cancer therapies and vaccines. For example, with tools such as PanPep, scientists may be able to simulate oncology screening processes on computers, potentially reducing time frames from months or years to a matter of days.

If doctors can quickly identify a promising treatment for a person with stage-4 cancer, for instance, it could extend their life. But the authors note that while meta-learning approaches can build accurate, target-specific models using only a small amount of experimental data, they require careful testing and refinement before they can be safely used to guide personalized care.

“Since real-world applications often involve entirely new immune targets, it remains unclear to what extent these models can handle truly unseen cases,” the authors said. “This is the initial rationale of this study.”

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About the University of South Florida

The University of South Florida is a top-ranked research university serving approximately 50,000 students from across the globe at campuses in Tampa, St. Petersburg, Sarasota-Manatee and USF Health. In 2025, U.S. News & World Report recognized USF with its highest overall ranking in university history, as a top 50 public university for the seventh consecutive year and as one of the top 15 best values among all public universities in the nation. U.S. News also ranks the USF Health Morsani College of Medicine in the highest tier, placing it as one of the top 16 medical schools in the nation and inside the top 10 among public universities. USF is a member of the Association of American Universities (AAU), a group that includes only the top 3% of universities in the U.S. With an all-time high of $750 million in research funding in 2025 and as a top 20 public university for producing U.S. patents, USF uses innovation to transform lives and shape a better future. The university generates an annual economic impact of nearly $10 billion for the state of Florida. USF’s Division I athletics teams compete in the American Conference. Learn more at www.usf.edu.