Jerwood gave her answer: “I am so hungry for something new all the time.” Standing there, above the automated lab, she imagined the regions of chemistry where no one has yet gone, structures and reactions that lie on the far side of unknown processes. The sun was just pulling itself over the horizon. She thought of all the things the machines might do, all the things that she will do no longer. “It’s down to the untouched space, yeah? Because then I will have time to look into that space,” she said. “I will have time to take that risk.”
For some pharmaceutical researchers, though, the promise of AI goes beyond pushing scientific boundaries or even treating disease. Alex Zhavoronkov, the CEO and cofounder of Insilico, says the company favors targets that are implicated in both illness and aging. Its drug candidate for idiopathic pulmonary fibrosis, for example, is designed to prevent scarring of the lungs by dampening certain biological pathways, but it also may slow the aging of healthy cells. Zhavoronkov hopes to bring new drugs to the clinic, perhaps faster and cheaper, even as he uncovers new treatments for aging-related disease and decline.
When I speak with Zhavoronkov, he’s at a company-wide retreat in Chongqing, China. “In 20 years, I’m going to be 66,” he says. “I saw my dad when he was 66, and it’s not pretty.” He is frank about having high expectations, about his desire for speed in an industry where speed isn’t always readily available. He shows me a video of an automated lab in Suzhou, China. “We built it during Covid,” he says, explaining that some of the laboratory scientists on the project worked around the clock, sleeping in the facility, to get it up and running.
There is something vaguely science-fictional about the setup, and about Zhavoronkov’s particular form of pragmatism. Zhavoronkov has scars on his arm where he’s had skin removed to make induced pluripotent stem cells, which can be reprogrammed to grow into many types of tissue. “If you want to buy my IPSC, give us a call. We’ll ship it to you,” he says. “The more data there is about you in the public domain, the higher chances you have to get a real good treatment when you get sick, especially with cancer.”
In the lab video, the camera glides through a black hallway, then through an anteroom, past a wall of glass. The glass can be dimmed, if the work going on behind it is confidential. Behind the wall are machines loaded with trays of reagents and cells, with arms that swivel as they move components around. Humans are rarely needed.
Animation: Balarama Heller
Sooner or later, in some form, AI tools will be standard in drug discovery, suspects Derek Lowe, the medicinal chemist and blogger. He calls himself a short-term pessimist, long-term optimist about these things. It’s happened again and again in the industry: New strategies arrive, ride a wave of hype, crash and burn. Then some of them, in some form, rise again and quietly become part of what’s normal. Already, big pharmaceutical companies—the behemoths of drug discovery—are starting their own AI-related research groups. Recursion, meanwhile, is exploring the use of AI not only to dream up and test new molecules but also to find trial participants, speeding along those last, costliest steps to market.
The transformation isn’t going to be without casualties. “These techniques, both the automation part and the software, are going to make more and more things slide into that ‘humans don’t do that kind of grunt work’ category,” Lowe says. Large numbers of jobs held by human chemists will wink out of existence. Those “who know how to use the machines are going to replace the ones who don’t,” Lowe says. Even Peter Ray no longer feels it’s accurate to describe him as a medicinal chemist. “I’m something else,” he muses. “I don’t know what to call it, to be honest.”
