HomeProjectsBiomedical Sciences and Healthcare TechnologiesVirus Mutation Prediction and Vaccine Antigen Design

Virus Mutation Prediction and Vaccine Antigen Design

Project Quick Facts

Principal Investigator

  • Prof. WANG Haitian Maggie

    The Jockey Club School of Public Health and Primary Care

  • Funding

    Research Grants Council

  • Collaboration

    Beth Bioinformatics Co., Ltd

    *The technology is exclusively licensed to Beth Bioinformatics. The company is currently in collaboration with pharmaceutical companies regarding vaccines.

  • Patent

    1 PCT, National Phase: China, US, Europe

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.

Virus evolution trajectory and estimation
Prediction of vaccine effectiveness using genome information

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

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