Researchers have achieved a significant milestone in artificial intelligence by using the technology to create entirely new viruses. While this breakthrough is noteworthy, it also raises concerns about the potential for AI to develop viruses more dangerous than those found in nature.
The newly created viruses are not monstrous mutations. They share more than 90 percent of their genetic material with existing bacteriophages, which are viruses that infect bacteria. These viruses specifically target Escherichia coli and were developed using an AI model not trained on viruses that could infect plants or animals.
Although these safety measures are commendable, they were mostly self-imposed. The research, published recently in Science, highlights the rapid pace of AI-driven biotechnology, which is advancing more quickly than regulatory measures can keep up with.
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“The frontier is moving very quickly,” says Toby Webster, a program director at Sentinel Bio, a nonprofit focused on biotech safeguards.
The Science paper detailing the AI-designed bacteriophages is already considered outdated. Initially released as a preprint on the bioRxiv server in September 2025, the model remains open-source and has been fine-tuned for other tasks since then.
With further development, future AI models could propose entirely new gene sequences for viruses or bacteria that evolution has not yet discovered, according to Doni Bloomfield, an associate professor of law at Fordham University, who specializes in biosecurity. AI could also guide individuals without expertise in the subtleties of biological design, potentially enabling malicious actors to create novel bioweapons.
“We should be very cautious about extending this work into viruses that can infect more complex life,” Bloomfield advises. “I don’t think we are at the point where we should be doing that without safeguards.”
Science is not starting from scratch in terms of biosecurity. Existing regulations govern laboratory safety, biological research, genetic modifications, and handling dangerous pathogens, says Filippa Lentzos, an associate professor at King’s College London who studies biosecurity.
“The challenge,” Lentzos explains, “is to connect that existing governance to the new upstream capability to design biology digitally.”
Research enabled by AI holds significant promise. New bacteriophages could target antibiotic-resistant bacteria, and innovative viral “shells” could deliver gene therapies or other medical treatments safely. AI models might also uncover new insights about genome organization, Bloomfield suggests.
To manage the risks and benefits, Bloomfield and colleagues propose a tiered access system for AI training data. This system would restrict information that could teach AI to enhance viral transmissibility, virulence, immune evasion, or resistance to medical treatments. The concept is similar to the current biosafety level system that limits access to pathogens like the Ebola virus to specific high-security labs.
Another precaution could be enhancing the screening of DNA and RNA sequences ordered by scientists from specialty suppliers. Many suppliers voluntarily check orders to ensure no dangerous sequences are being requested. However, last year Microsoft found that AI-generated toxic protein sequences, which are simpler than viral genomes, bypassed these safety checks. They quickly released software patches to address this vulnerability.
Knowledge gaps complicate the formation of new regulations. For instance, it’s unclear how training data translate to model capabilities, says Allison Berke, a senior engineer at the RAND Center on AI, Security, and Technology. Would models need specific flu virus data to recreate the 1918 pandemic flu, or could they extrapolate it from a general viral genome dataset? The latter scenario poses a greater challenge for protection.
The learning curve also remains uncertain.
“If we see indications of the beginnings of a viral design capability, does that mean we will get full 100 percent viral design capabilities in a year, in six months?” Berke asks. “We don’t have a great sense of how that capability curve is progressing.”
Both scientists and policymakers are increasingly discussing these issues, says Tessa Alexanian, a technical lead at the International Biosecurity and Biosafety Initiative for Science. The authors of the bacteriophage study advocate for more effective biosecurity measures in their paper. However, Alexanian notes that policymakers fear excessive regulation could hinder beneficial research. In the U.S., lawmakers may be waiting for a “shocking demonstration” of biological capabilities before taking action, Berke observes.
This could mean that research will continue to outpace regulation for the foreseeable future.
“It’s great to see lots of people in this field caring about creating and releasing these powerful models responsibly, but they aren’t required to and often lack official guidance to navigate this properly,” Webster remarks. “Currently we’re running on a lot of goodwill.”
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