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Combining bioinformatics, virology and artificial intelligence, our team developed a robust model that can characterize and predict genetic mutations of viruses. The model could be applied to antigen design to improve vaccine effectiveness (VE), or to accurately estimate the VE of different vaccines in-silico. For instance, when applied to influenza, we could improve seasonal influenza vaccines’ effectiveness by 20-40%. The model could also take geographical factors into consideration to provide region-specific antigen designs and VE predictions, assisting vaccine producers and governments around the world make better informed decisions. Besides Influenza, the technology is also transferrable to other viruses.
Uniqueness and Competitive Advantages:
- Forwardly-predictive, accurate even when predicted one year in advance for influenza
- Vaccine antigen designs that improve VE
- Accurate VE estimation without the need of additional clinical trials
- Region-specific designs and predictions
- Transferrable to other viruses and vaccines