Researchers from Amity University, Noida and Baylor College of Medicine in Houston, USA have developed an artificial intelligence-based platform which can speed up the vaccine development process for deadly infectious diseases such as Covid-19 and Chagas Disease.

The results of this study have been published in the UK-based journal Scientific Reports and PubMed titled ‘Identification of vaccine targets in pathogens and design of a vaccine using computational approaches.’

The platform has been tested on 40 different pathogens including SARS-CoV-2 (Covid-19), Mycobacterium tuberculosis (TB), Vibro cholerae (cholera) and Plasmodium falciparum (malaria).

“The key innovation is using artificial intelligence to combine several hundred parameters to mine several thousand proteins and genes to reach to the right targets and design vaccines using these proteins,” said Dr Kamal Rawal, Associate Professor & Project Director, Amity Institute of Biotechnology.

Dr Rawal is the lead author of the article with Dr Peter Hotez, Dean of the National School of Tropical Medicine, Baylor College of Medicine, Co-Dean Dr Maria Elena Bottazzi and BCM Associate Professor Dr Ulrich Strych as senior co-authors.

Dr Rawal created a cloud-based server which can be used by researchers across the world to analyse their proteins and genes as potential vaccine targets. “In the wake of emergence of Delta variant of Covid-19, the team is also engaging with various pharmaceutical and biotechnology companies for customised deployment for commercial scale application to develop new vaccines against emerging infectious diseases,” Amity University said in a statement.

“As evidence, researchers tested this platform on several experimentally known vaccine targets including vaccines in the market. The team of researchers have long standing interest in neglected diseases of poverty, so they opted to analyse the whole genome and proteome (set of all protein sequences in a cell) of an important pathogen known as Trypanosoma cruzi (T. cruzi),” it said.

To “validate” the platform, over 335 experimentally verified antigens belonging to 40 different pathogens were shortlisted. It was found that the “system was correctly predicting most of them with reasonable accuracy levels”.

“These examples also include targets from FDA approved/marketed vaccines making strong case in favour of this platform. The next line of action is to inject mice with these computer-suggested vaccines to demonstrate that the designed vaccines are non-toxic and sufficiently immunogenic (produce enough antibodies) before entering into clinical trials,” the university said.

“Right now, it is too early to tell how this work will affect patients down the line, but initial data suggest that the platform will be beneficial in several ways,” Dr Strych pointed out.

Dr Bottazzi said, “An ideal vaccine target should not be similar to host proteins (humans) in order to avoid cross reaction and subsequent side-effects, therefore special care was taken to filter such data during the study.”

The research was supported by the Kleberg Foundation, USA and Baylor College of Medicine.

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By Lukas

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