Researchers are betting that AI and automation can cut drug discovery from five years to six months: Automating antivirals

Abstract

WITHIN MOMENTS OF MEETING EACH OTHER at a conference last year, Nathan Collins and Yann Gaston-Mathe began devising a plan to work together. Gaston-Mathe runs a startup that applies automated software to the design of new drug candidates. Collins leads a team that uses an automated chemistry platform to synthesize new drug candidates. • “There was an obvious synergy between their technology and ours,” recalls Gaston-Mathe, CEO and cofounder of Paris-based Iktos. • In late 2019, the pair launched a project to create a brand-new antiviral drug that would block a specific protein exploited by influenza viruses. Then the COVID-19 pandemic erupted across the world stage, and Gaston-Mathe and Collins learned that the viral culprit, SARS-CoV-2, relied on a protein that was 97 percent similar to their influenza protein. The partners pivoted. • Their companies are just two of hundreds of biotech firms eager to overhaul the drug-discovery process, often with the aid of artificial intelligence (AI) tools. The first set of antiviral drugs to treat COVID-19 will likely come from sifting through existing drugs. Remdesivir, for example, was originally developed to treat Ebola, and it has been shown to speed the recovery of hospitalized COVID-19 patients. But a drug made for one condition often has side effects and limited potency when applied to another. If researchers can produce an antiviral that specifically targets SARS-CoV-2, the drug would likely be safer and more effective than a repurposed drug.