Biologists at Anthropic announced on Sept 23 that they had used artificial intelligence (AI) to identify genes in viruses that produce enzymes that work in a new way, the first discovery emanating from a research lab the company opened this spring.
“We have chosen biology and medicine as the primary way that we believe the benefits from AI can come about,” said Eric Kauderer-Abrams, the head of life sciences at Anthropic.
Kauderer-Abrams and his colleagues described their work in a technical report posted on the company’s website. The results have not yet been submitted to a scientific journal for publication.
Anthropic CEO Dario Amodei saw great potential in the finding. “Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism,” he wrote on social platform X on Sept 23.
Outside experts said that such claims jumped far ahead of the evidence the team has gathered so far.
“It’s not yet a breakthrough,” said Philip Kranzusch, a microbiologist at Harvard Medical School. “It’s a wrinkle on what we know in the field.”
Anthropic’s foray into biology comes amid intense controversy about the safety of AI. This month, Anthropic reported potentially dangerous uses of its models, including queries that could potentially assist people in building biological weapons.
Two days after that announcement, Amodei called for slowing development so that humanity can enjoy the benefits of AI without risking catastrophe.
Amodei, who has a doctorate in biophysics, has long argued that one of those benefits will be new treatments for diseases. “The first step is showing that AI can first help with, and then drive, biological discoveries,” he wrote on X.
In hopes of safely demonstrating that, Anthropic opened a biology lab this year, as first reported last week by Reuters.
“Our team is still relatively small, but we are growing very rapidly,” Kauderer-Abrams said. “This is one of the most significant investment areas for the company.”
Anthropic is far from the first organisation to use artificial intelligence to probe biology. A number of academic labs and startups are training AI models to discover hidden molecular machines, design new proteins or even predict how entire cells will respond to drugs.
Kauderer-Adams and his colleagues are using Anthropic’s products, such as the large language model Mythos and Claude Code, which writes computer programs on demand.
In the new report, Anthropic’s biologists describe their search for enzymes, called reverse transcriptases. These enzymes can read the sequence in an RNA molecule and produce a matching piece of DNA.
Viruses and bacteria make reverse transcriptases for many purposes, and scientists have found them to be powerful tools. One type of Covid-19 test, for example, uses reverse transcriptases to detect the coronavirus. Scientists have also harnessed the enzymes to develop new ways to edit genes.
As promising as these enzymes are, however, scientists have barely begun to document their diversity in the natural world. Kauderer-Adams and his colleagues created AI agents to search through databases of viral and bacterial genes in search of new reverse transcriptases.
The agents wrote their own programs to examine genes that serve as blueprints for 1.9 billion kinds of proteins. They searched for molecular patterns that were similar to known reverse transcriptases, along with the proteins and RNA molecules that help the enzymes do their job.
The search yielded a list of 17 possible reverse transcriptases, but 14 turned out to be errors. In some cases, they were not new. In other cases, they were not reverse transcriptases at all. But the remaining three held up to scrutiny.
The researchers claim that one of the new kinds works differently from previously discovered ones.
The enzymes, which the scientists call array-associated reverse transcriptases, are carried by viruses. They are produced along with a set of RNA molecules that appear to work with them in some way.
But outside experts said that the Anthropic researchers have yet to do the research required to confirm that they’ve found something new.
Yuzhen Ye, a computational biologist at Indiana University, said that the researchers should have tested their hypothesis by using software created specifically to analyse reverse transcriptase genes.
“I think we should be a little more careful before jumping to something being a new discovery,” Ye said.
For Kauderer-Abrams, one of the most revealing insights was not about enzymes, but about the capacity that AI has to perform science. “There’s been a lot of debate about whether AI can have creativity, or is it only good at just executing on instructions,” he said.
Kauderer-Abrams saw evidence of scientific creativity in the transcripts that the agents generated as they carried out their assignments.
When an agent inspected array-associated reverse transcriptases, it initially determined that they were not something worth examining. But then it flagged the RNA molecules that accompanied the proteins, which were peculiar enough to warrant a second look.
“You can see the agent say, ‘Huh, that’s interesting,’” Kauderer-Abrams said. – ©2026 The New York Times Company
This article originally appeared in The New York Times.
