Sarah Gurev

With each new variant of SARS-COV-2—not to mention annual variants of the flu—another wave of people are sickened, and their lives disrupted. Viruses mutate and evolve, keeping ahead of vaccines. EVEScape aims to predict those evolutions and mutations by using artificial intelligence. The project, which is co-led by Sarah Gurev, a doctoral student at Harvard Medical School in the Debora Marks Lab, uses AI to process data on viral evolution over an extended period, alongside information on the biology and structures of different viruses. The team, including co-leaders Nicole N. Thadani, Debora Marks, Pascal Notin, and Noor Youssef, published a study last fall showing that if the tool had been available at the start of the pandemic in 2020, it would have been able to predict the most concerning variants before they appeared. Gurev designed the AI models that underpinned those predictions.

Gurev and her colleagues also collaborate with labs that can evaluate vaccines and therapies that can stop future variants of a virus from wreaking havoc. “The direct partnership between computationalists and experimentalists will really drive AI to become impactful in different biological applications,” she says.

Gurev and her collaborators are now using the tool to keep up with the Lassa and Nipah viruses, which lead to serious illnesses in West Africa and South Asia respectively, and are more virulent that SARS-COV-2 but much less studied. Vaccine design is typically slow and laborious, but AI may speed up and streamline the process. Gurev says the tool can also help researchers design broader coronavirus vaccines that would be “future proof.”