Scientists have achieved a milestone by creating the first viruses designed entirely by artificial intelligence, a breakthrough that offers hope for new medicines but also raises urgent questions about biosecurity. The viruses, known as bacteriophages, are specific to bacteria and are already used worldwide to treat patients with persistent infections. In laboratory tests, a cocktail of these AI-designed viruses successfully killed E. coli bugs that were resistant to natural bacteriophages, demonstrating a potential solution to antibiotic resistance.
Breakthrough in Phage Therapy
Dr. Brian Hie, a chemical engineer at Stanford University in California, led the research using genome language models—the genetic equivalent of the large language models behind AI chatbots—to design functioning genomes for bacteriophages. The viruses were then synthesized in the laboratory and tested against E. coli in a petri dish. The researchers reported in the journal Science that the ability to “rapidly design” genomes and tune them for specific bugs while overcoming resistance could “transform phage therapy” and “expand biotechnological toolkits.”
The team used AI models called Evo1 and Evo2, which were trained on genetic data from 2 million bacteriophages. Importantly, the genetic code for viruses that can infect plants, humans, or other animals was intentionally excluded from the AI’s training to reduce the risk of it designing dangerous viruses. The AI generated thousands of potential genomes, from which the researchers selected nearly 300 to produce in the lab. These were introduced into bacteria, which read the genetic code and produced the new bacteriophages. The process was not efficient—only 16 bacteriophages proved viable—but a cocktail of them swiftly overcame resistance in two different strains of E. coli.
Biosecurity Concerns Raised
Beyond the potential benefits, the scientists acknowledged that the work raised “important biosafety, biocontainment and biosecurity considerations.” They urged others designing whole genomes to “consult both safety and security professionals throughout the project.” In an accompanying article, Prof. Tom Inglesby and Dr. Moritz Hanke at the Center for Health Security at Johns Hopkins University in Baltimore reinforced the warning, writing: “Although this is promising for life sciences applications, it also raises urgent biosafety and biosecurity questions. The ability to compose viral genomes using generative AI now exists; the governance to safely steer it does not.”
Inglesby and Hanke noted that while bacteriophage genomes are tiny, the work proved that generative AI could create functioning viral genomes. Whether the same approach could be applied to other viruses is unknown, but they argued that work on pathogens that could infect humans, animals, or plants should not be pursued. “Such genomes might encode new pathogens that … cannot be contained by existing countermeasures,” they wrote.
Expert Reactions and Future Implications
Tom Ellis, a professor of synthetic genome engineering at Imperial College London, described the work as impressive but highlighted how difficult it would be to make more complex genomes. “This is literally the smallest and easiest genome to make,” he said. Ellis warned that an AI trained on the genetic code of dangerous bugs could be used to design more harmful viruses, but suggested that controlling access to genetic data and imposing restrictions on making genomes that look dangerous would help. “Governments are working hard to do this already,” he added. “But honestly, the threat from full AI design and writing of a genome of a virus or bacteria is very overblown when we consider that just taking existing pathogens and making gain-of-function changes to their genomes is so much easier and much more likely to be a real pathogenic threat.”
Dr. Filippa Lentzos, a reader in science and international security at King’s College London, emphasized that the most important point to intervene is when DNA is being manufactured. “It’s important to see the bigger governance picture and not focus regulation solely on the AI model,” she said. “A layered approach makes more sense: safeguards around model development and access, responsible research review, synthesis screening, and established laboratory biosafety and biosecurity.”
The development marks a significant step forward in synthetic biology, with potential applications in medicine, but it also underscores the need for robust governance to ensure that such technology is used safely and responsibly. As AI continues to advance, the scientific community and policymakers must work together to address the ethical and security implications of designing life at the genetic level.
