Researchers develop a mathematical model to predict COVID-19 vaccine efficacy

Researchers at The University of Queensland have developed a mathematical model that 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 produced a model that predicts the effectiveness of the antibody response in patients receiving one of eight major vaccines.

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 minimize reliance on expensive and time-consuming clinical trials."

Dr Pranesh Padmanabhan, Queensland Brain Institute

Since the start of the COVID 19 pandemic, researchers and scientists have been scrambling to develop vaccines candidates to protect against the SARS-CoV-2 virus and keep ahead of its mutations.

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

"The model we developed reliably predicted the diversity of the antibody response within and across vaccinated individuals," he said.

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

"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," Dr Padmanabhan said.

"Using this model, we aim to predict the efficacies of new vaccines against different variants without relying heavily on clinical trials."

Professor Narendra Dixit from the Indian Institute of Science 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," Professor Dixit said.

"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."

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.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
COVID-19 raises the risk of type 2 diabetes in children, study reveals