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MIT researchers develop AI tool to improve flu vaccine strain selection

Every year, global health experts are faced with a high-stakes decision: Which influenza strains should go into the next seasonal vaccine? The choice must be made months in advance, long before flu season even begins, and it can often feel like a race against the clock. If the selected strains match those that circulate, the vaccine will likely be highly effective. But if the prediction is off, protection can drop significantly, leading to (potentially preventable) illness and strain on health care systems.
MIT News
The VaxSeer system developed at MIT can predict dominant flu strains and identify the most protective vaccine candidates. The tool uses deep learning models trained on decades of viral sequences and lab test results to simulate how the flu virus might evolve and how the vaccines will respond. Pictured: Senior author Regina Barzilay (left) and first author Wenxian Shi.
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