“That was pretty striking, just actually seeing, like, this AI-generated sphere,” says Brian Hie, who leads the lab at the Arc Institute where the work was carried out.
Overall, 16 of the 302 designs ended up working—that is, the computer-designed phage started to replicate, eventually bursting through the bacteria and killing them.
J. Craig Venter, who created some of the first organisms with lab-made DNA nearly two decades ago, says the AI methods look to him like “just a faster version of trial-and-error experiments.”
For instance, when a team he led managed to create a bacterium with a lab-printed genome in 2008, it was after a long hit-or-miss process of testing out different genes. “We did the manual AI version—combing through the literature, taking what was known,” he says.
But speed is exactly why people are betting AI will transform biology. The new methods already claimed a Nobel Prize in 2024 for predicting protein shapes. And investors are staking billions that AI can find new drugs. This week a Boston company, Lila, raised $235 million to build automated labs run by artificial intelligence.
Computer-designed viruses could also find commercial uses. For instance, doctors have sometimes tried “phage therapy” to treat patients with serious bacterial infections. Similar tests are underway to cure cabbage of black rot, also caused by bacteria.
“There is definitely a lot of potential for this technology,” says Samuel King, the student who spearheaded the project in Hei’s lab. He notes that most gene therapy uses viruses to shuttle genes into patients’ bodies, and AI might develop more effective ones.
The Stanford researchers say they purposely haven’t taught their AI about viruses that can infect people. But this type of technology does create the risk that other scientists—out of curiosity, good intentions, or malice—could turn the methods on human pathogens, exploring new dimensions of lethality.
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