USC researchers have developed a new method to counter emergent mutations of the coronavirus and hasten vaccine development to stop the pathogen responsible for killing thousands of people and ruining the economy.
Using artificial intelligence (AI), the research team at the USC Viterbi School of Engineering developed a method to speed the analysis of vaccines and zero in on the best potential preventive medical therapy.
The method is easily adaptable to analyze potential mutations of the virus, ensuring the best possible vaccines are quickly identified—solutions that give humans a big advantage over the evolving contagion. Their machine-learning model can accomplish vaccine design cycles that once took months or years in a matter of seconds and minutes, the study says.
“This AI framework, applied to the specifics of this virus, can provide vaccine candidates within seconds and move them to clinical trials quickly to achieve preventive medical therapies without compromising safety,” said Paul Bogdan, associate professor of electrical and computer engineering at USC Viterbi and corresponding author of the study. “Moreover, this can be adapted to help us stay ahead of the coronavirus as it mutates around the world.”
The findings appear today in Nature Research’s Scientific Reports
When applied to SARS-CoV-2—the virus that causes COVID-19—the computer model quickly eliminated 95% of the compounds that could’ve possibly treated the pathogen and pinpointed the best options, the study says.
The AI-assisted method predicted 26 potential vaccines that would work against the coronavirus. From those, the