Australian-Indian research team creates new model to predict the effectiveness of COVID-19 vaccines

With the help of this model, new vaccines may be able to be produced much faster by allowing scientists to "make decisions before clinical trials are over."

Researchers based at Australia’s the University of Queensland (UQ) have developed a new mathematical model.

With the help of this model, researchers can “predict the efficacy of COVID-19 vaccines, potentially speeding-up the development of new vaccines.”

The Queensland Brain Institute’s Dr Pranesh Padmanabhan, working with researchers from the Indian Institute of Science (IIS) has produced this model.

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This research was a result of an international collaboration between the Queensland Brain Institute and the Indian Institute of Science and was published in Nature Computational Science.

Dr Padmanabhan said the research established a framework for predicting the efficacy of new vaccines against future strains of the SARS CoV-2 virus.

“The ability to predict vaccine efficacies could expedite vaccine development by helping shortlist promising candidates and minimise reliance on expensive and time-consuming clinical trials.”

Since 2020, researchers and scientists have been working hard to develop vaccines and keep ahead of its mutations.

A COVID model
COVID-19: Image Source: The University of Queensland

According to UQ, Dr Padmanabhan and his colleague analysed 80 individual antibodies from 20 studies to construct a mathematical model of SARS-CoV-2 antibodies.

Dr Padmanabhan said:

“The model we developed reliably predicted the diversity of the antibody response within and across vaccinated individuals.”

The team then analysed clinical trial data for eight major vaccines. They found a relationship between vaccine protection against SARS CoV-2 and the potential antibody response.

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Dr Padmanabhan adds:

“The main predictions are the influence of vaccination on the severity of disease and the population-level protection conferred by the eight approved COVID-19 vaccines. Using this model, we aim to predict the efficacies of new vaccines against different variants without relying heavily on clinical trials.”

Prof. Narendra Dixit from the IIS said the major challenge was to understand and describe the vast variability in the antibody responses elicited by the vaccine.

“Overcoming this challenge would allow predicting the fraction of the vaccinated individuals who would generate strong enough responses to be protected from serious infection.”

Prof. Dixit further adds:

“By deducing links between the activity of antibodies, its variability, antibody generation by vaccination, and the resulting protection conferred upon populations, our study offers exciting insights into the workings of COVID-19 vaccines.”

With the help of this model, new vaccines may be able to be produced much faster by allowing scientists to “make decisions before clinical trials are over”.