Introduction to the Challenge of Flu Season
Every year, global health experts face a high-stakes decision: choosing which influenza strains to include in the next seasonal vaccine. This decision must be made months in advance, 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. However, if the prediction is off, protection can drop significantly, leading to potentially preventable illness and strain on healthcare systems.
The Similarity with Covid-19
This challenge became even more familiar to scientists during the Covid-19 pandemic. New variants emerged just as vaccines were being rolled out, making it hard to stay ahead and design vaccines that remain protective. Influenza behaves similarly, mutating constantly and unpredictably, which makes it hard to predict and prepare for.
Introducing VaxSeer
To reduce this uncertainty, scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the MIT Abdul Latif Jameel Clinic for Machine Learning in Health created an AI system called VaxSeer. VaxSeer is designed to predict dominant flu strains and identify the most protective vaccine candidates, months ahead of time. 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.
How VaxSeer Works
VaxSeer adopts a large protein language model to learn the relationship between dominance and the combinatorial effects of mutations. Unlike existing protein language models, VaxSeer models dynamic dominance shifts, making it better suited for rapidly evolving viruses like influenza. The system has two core prediction engines: one that estimates how likely each viral strain is to spread (dominance), and another that estimates how effectively a vaccine will neutralize that strain (antigenicity).
The Future of Flu
VaxSeer produces a predicted coverage score: a forward-looking measure of how well a given vaccine is likely to perform against future viruses. The scale of the score could be from an infinite negative to 0, with scores closer to 0 indicating a better antigenic match of vaccine strains to the circulating viruses. In a 10-year retrospective study, VaxSeer’s recommendations outperformed those made by the World Health Organization (WHO) for two major flu subtypes: A/H3N2 and A/H1N1.
Real-World Implications
For A/H3N2, VaxSeer’s choices outperformed the WHO’s in nine out of 10 seasons, based on retrospective empirical coverage scores. For A/H1N1, it outperformed or matched the WHO in six out of 10 seasons. In one notable case, for the 2016 flu season, VaxSeer identified a strain that wasn’t chosen by the WHO until the following year. The model’s predictions also showed strong correlation with real-world vaccine effectiveness estimates, as reported by the CDC, Canada’s Sentinel Practitioner Surveillance Network, and Europe’s I-MOVE program.
Outpacing Evolution
By modeling how viruses evolve and how vaccines interact with them, AI tools like VaxSeer could help health officials make better, faster decisions — and stay one step ahead in the race between infection and immunity. VaxSeer currently focuses only on the flu virus’s HA (hemagglutinin) protein, but future versions could incorporate other proteins like NA (neuraminidase), and factors like immune history, manufacturing constraints, or dosage levels.
Conclusion
VaxSeer is an innovative AI system that aims to improve the accuracy of vaccine selection and reduce the uncertainty associated with flu season. By leveraging deep learning models and large datasets, VaxSeer can predict dominant flu strains and identify the most protective vaccine candidates, months ahead of time. This technology has the potential to revolutionize the field of vaccine development and help health officials stay ahead of the evolving flu virus.
FAQs
- What is VaxSeer?: VaxSeer is an AI system designed to predict dominant flu strains and identify the most protective vaccine candidates.
- How does VaxSeer work?: VaxSeer 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.
- What are the benefits of VaxSeer?: VaxSeer can help health officials make better, faster decisions and stay one step ahead in the race between infection and immunity.
- Is VaxSeer currently being used?: VaxSeer is still in the development stage, but it has shown promising results in retrospective studies.
- Can VaxSeer be applied to other viruses?: Yes, VaxSeer can be applied to other viruses, but it would require large, high-quality datasets that track both viral evolution and immune responses.
