It takes on average a decade to go from the initial discovery stage of a drug to approval and, with a high failure rate, the pharmaceutical industry estimates it costs $2.7bn to bring each one to market. Clinical trials make up the bulk of this time and cost, but discovery and pre-clinical tests can still take three or four years.
During the pandemic, AI was primarily used as a tool to save scientists’ time, accelerating this notoriously slow discovery process, while often using drugs and vaccines designed for similar viruses such as Mers as a starting point. But advocates of AI believe its wider use during the crisis is just the start of a revolution in drug discovery that will harness growth in biological and chemical data, computing power and smarter algorithms that could reduce soaring healthcare bills and create treatments for conditions where we have none.
They argue AI proved itself in the crisis. AbCellera sorted through 6mn cells in three days to find an antibody that could be mass produced — in this case by Eli Lilly — as a drug called bamlanivimab that has helped more than 1mn Covid patients. A supercomputer helped in Pfizer’s quest for an antiviral that could be taken orally.
Demis Hassabis co-founder of Isomorphic Labs which is part of Google presents on the future of AI
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