IISc Bengaluru Develops New Model That Predicts COVID Vaccines Efficacy

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IISc Bengaluru Develops New Model That Predicts COVID Vaccine's Efficacy

Queensland Brain Institute, Australia, co-developed this model that predicts how antibodies generated by COVID-19 vaccines confer protection against symptomatic infections.

All the Indian Institutes of eminence have given an ardent contribution to combating COVID-19. In yet another development Indian Institue of Science (IISc), Bengaluru, has added one more feather to its cap by designing a mathematical model that predicts how antibodies generated by COVID-19 vaccines confer protection against symptomatic infections to what extent.

The model was co-developed by Queensland Brain Institute, Australia and the study was published in the journal Nature Computational Science.

The researchers claim that predicting the efficacy of the vaccines would assist in further development of vaccine and their usage procedures. The researchers devised a multi-scale mathematical model that proposes mechanistic links between COVID-19 vaccine efficacies and the neutralising antibody (NAb) responses they stimulate.

Several vaccine candidates have conferred a high degree of protection, with some decreasing the number of symptomatic infections by over 95% in clinical trials. But what factors go into determining the level of protection? The solution to this question would aid in the efficient use of existing vaccinations and the development of new ones.

Development Of Model

Initially, the researchers examined over 80 different neutralising antibodies reported being generated after vaccination against the surface spike protein of SARS-CoV-2, the virus that causes COVID-19. These antibodies are typically present in the blood for months and control virus entry by barring the spike protein.

The researchers hypothesised that these 80 antibodies include a 'landscape' or 'shape space', and each individual produces a unique 'profile' of antibodies, a small, random subset of this landscape.

Later, the team developed a mathematical model to simulate infections in a virtual patient population of about 3,500 people with different antibody profiles and predict how many would be protected from symptomatic disease following vaccination.

The researchers also perceived that vaccine efficacy was linked to a readily measurable metric called antibody neutralisation titre. The study authors suggest that this opens up the possibility of using such models to test future vaccines for their efficacies before elaborate clinical trials are launched.

Study Based On Current Vaccines

However, Narendra Dixit, Professor at the Department of Chemical Engineering, IISc, and the paper's senior author cautioned that the study is based on current vaccines designed to work on the original SARS-CoV-2 strain. He said, "Our formalism is yet to be applied to the new variants, including Omicron, where other arms of the immune system and not just antibodies appear to be contributing to vaccine efficacies. Studies are ongoing to address this," quoted the Indian Express.

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