Scientists use AI to design new viruses never seen before in nature

Scientists have used artificial intelligence to create new viruses – a hopeful step toward medical advances that also raises serious concerns around potential misuse.

Researchers from Stanford University and the Arc Institute used the AI to generate thousands of genome combinations within a specific framework – specifically one that could be hosted by an E. coli bacteria cell.

Of the thousands of genomes that the AI generated, scientists built and tested about 300 in the lab and found that 16 were viable viruses.

The new viruses are bacteriophages, which infect bacteria but cannot affect humans.

The study, published on Thursday in the journal Science, says that genetic sequences from millions of sources “from all domains of life” served as the language library for the AI tool Evo.

Much like Chat-GPT and other large language models, AI tool Evo was trained on large sets of existing text material.

According to the research, the genetic library helped the AI “learn the evolutionary constraints” of natural genomes.

However, the model appeared to go further, with scientists finding that one of the new viruses had an aspect that was “evolutionarily distant” – suggesting the AI prompted changes that could have taken millions of years for natural evolution to prove possible.

Tests showed that a mixture of the new viruses could overcome antibacterial resistance in some of the E. coli strains, something that a “comparable mixture of naturally sourced” bacteriophages could not.

This “lays out a path for generating adaptive and resilient phage therapies against rapidly evolving pathogens,” the authors wrote.

The work is a significant scientific milestone, especially as scientists race to combat rising drug resistance within germs such as E. coli but it also raises questions about potential misuse.

“Although this is promising for life sciences applications, it also raises urgent biosafety and biosecurity questions,” doctors from the Johns Hopkins Center for Health Security wrote in a corresponding article published in Science.

“The ability to compose viral genomes using generative AI now exists; the governance to safely steer it does not.”

The researchers addressed the biosecurity considerations directly in their research, but the Johns Hopkins doctors wrote that they “engage with biosafety and biosecurity questions more deliberately than most developers of powerful biological AI models”.

The new research focused on E. coli bacteria and was in a certain type of virus that can’t affect humans – and it’s unclear how well the work would apply to other viruses.

The authors of the response article single out one particularly risky area that they say should not be pursued: eukaryote-infecting pathogens (spread by organisms with complex cells and nuclei).

These can cause a variety of illness in humans including malaria an yeast infections.

“Such genomes might encode new pathogens that can infect humans, animals, or plants in ways that cannot be contained by existing countermeasures,” the authors wrote.