MIT researchers develop AI tool to improve flu vaccine strain selection

VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.

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.

This challenge became even more familiar to scientists in the years during the Covid-19 pandemic. Think back to the time (and time and time again), when new variants emerged just as vaccines were being rolled out. Influenza behaves like a similar, rowdy cousin, mutating constantly and unpredictably. That makes it hard to stay ahead, and therefore harder to design vaccines that remain protective.

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