Innovation & Impact

INNOVATIONS

Population Level Influenza Forecasting

IP & Licensing Entrepreneurship

Innovations & Impacts

Influenza vaccinations are important, given the mortality of over half a million people each year. However, as the influenza virus is constantly mutating, it is increasingly important to identify the vaccine strains accurately for vaccine production. At present, influenza activities are usually studied in from two separate angles. In microbiology, mutations sites and strain family are analyzed by polygenic analysis; while in epidemiology, only case numbers and climate information are used to model influenza epidemics, without reference to molecular information.



In this light, it is desirable to develop a method that integrates these two areas, using population information to evaluate mutation effectiveness, and genetic evolution information to produce population level influenza forecasting. A technology developed by a research team led by Professor Maggie Haitian WANG and Professor Benny Ying-chung ZEE from the Jockey Club School of Public Health and Primary Care which meets this need has been licensed to a Hong Kong-based startup this year. With the licensed technology, the company aims to collaborate with pharmaceutical companies with influenza vaccine production capability in order to produce more effective influenza vaccines in the future.



During the COVID-19 pandemic, the team has further developed a real-time bioinformatics platform to predict COVID-19 vaccine effectiveness against SARS-CoV-2 variants with 95% accuracy. The innovative approach can be applied to design vaccines with optimal estimated effectiveness and improve vaccine clinical trial design and the evaluation of vaccines before they are deployed.


From Research to Market

  • RESEARCH

  • ENTREPRENEURSHIP

  • IP & LICENSING

The research team led by Professor WANG and Professor ZEE has been dedicated to the research on bioinformatics and biostatistics. In 2022, they have discovered the world’s first in-silico method to evaluate any given COVID-19 vaccines’ effectiveness against different SARS-CoV-2 variants strains in real-time by genetic analysis, while also accounting for the differences in VE resulted from using different vaccine platforms such as mRNA. Their findings have been published in Nature Medicine.

In 2020, with the support of the Technology Start-up Support Scheme for Universities (TSSSU), Beth Bioinformatics Company Limited was founded with the mission to develop AI-assisted vaccine antigen design and accurate complex disease risk prediction technologies. The startup is also admitted to the Incu-Bio Programme supported by the Hong Kong Science and Technology Parks Corporation (HKSTP). The company developed the APP “vaccine4u” to make vaccination appointment simpler and easier for citizens. Paired along with 3rd generation sequencing, the biotechnology startup hopes to provide a quick and reliable method for primary care, direct-to-customer genetic testing companies and insurance companies to identify disease risk early in wide-range screening setting. The biotechnology startup won the Winning Start-up Award in the 5th Start-up Express (2022).

The silico bioinformatics algorithms to predict vaccine effectiveness (VE) invented by Professor WANG and Professor ZEE was patented in 2018.

Video

Photo