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<\/a>In a study published last week in Science<\/a>, AI models generated hundreds of new phage designs. Of 285 designs tested in the laboratory, 16 produced functioning viruses capable of reproducing and attacking E. coli bacteria. The researchers later showed that combinations of several of the newly created phages could also attack bacteria that had developed resistance to the original phage.<\/p>\nThe finding could eventually help scientists develop new treatments against antibiotic-resistant bacterial infections. But it also demonstrates how rapidly AI is gaining the ability to design biological systems, raising questions about safety, oversight and what happens when these tools become much more capable.<\/p>\n
To understand how AI can design a virus, Prof. Ran Nir-Paz, an infectious disease specialist at Hadassah Medical Center and clinical lead of the Israeli Phage Therapy Center, suggests thinking of DNA as a language.<\/p>\n
The researchers developed models trained on enormous quantities of genetic information, enabling them to learn patterns and rules governing how genomes are constructed and function. \u201cJust as there is Claude and Gemini, which can use ordinary language to produce sentences, paragraphs or even books, the researchers developed two models, Evo 1 and Evo 2, whose job is to use the language of DNA and RNA,\u201d Nir-Paz said.<\/p>\n
In this analogy, conventional language models generate text of different lengths and complexity. The biological models generate genetic sequences. \u201cFrom short words and sentences to long books,\u201d Nir-Paz said. \u201cA long book might be a monkey, a human, a dog or another large, complex animal, while the paragraphs or short sentences would be bacteriophages, the subject of this paper, viruses that infect bacteria.\u201d<\/p>\n
Designing biological systems on computers is not entirely new. Nir-Paz pointed to American geneticist Craig Venter, one of the pioneers of the Human Genome Project, whose research institute has worked on creating simple forms of life using DNA designed and synthesized in the laboratory.<\/p>\n
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Prof. Ran Nir-PazPhoto: Hadassah Medical Center<\/p>\n
One major breakthrough came about a decade ago, before generative AI models entered everyday life, when scientists created a bacterium with a minimal genome designed on a computer and built in a laboratory so it could divide and reproduce.<\/p>\n
\u201cThe aim was fairly similar to what the researchers did here: use existing knowledge, which still contains gaps in our understanding, to create a life form capable, in their case, of dividing independently and give it certain characteristics,\u201d Nir-Paz said. \u201cThey demonstrated that 10 years ago. It was a very impressive and remarkable breakthrough.\u201d<\/p>\n
What has changed is the power of the computational tools. Nir-Paz said the researchers behind the latest study used technologies resembling those behind language models to learn from vast quantities of genetic data and generate new sequences.<\/p>\n
\u201cEvo 2 was trained on enormous amounts of genetic information from databases, and from that it learned to build, let\u2019s say, a new paragraph that can be read and understood, or in this case a bacteriophage virus that attacks bacteria,\u201d he said.<\/p>\n
One of the greatest potential contributions of such tools, Nir-Paz believes, may be helping scientists understand biological functions that remain mysterious. \u201cIn the bacteriophage genome, we know the function of roughly 40% of the genes and proteins,\u201d he said. \u201cWe understand much less about the rest.\u201d Models capable of detecting patterns across huge genetic datasets could potentially help scientists decipher parts of biology that remain poorly understood.<\/p>\n
New bacteriophages could one day be used to treat bacterial infections <\/p>\n (Photo: shutterstock)<\/p>\n Another possibility, already explored in the new study, is designing bacteriophages that might one day treat bacterial infections, particularly those resistant to antibiotics.<\/p>\n But Nir-Paz cautioned that the field remains in its infancy. One unresolved question is whether the future of phage therapy lies in engineered viruses designed in laboratories or in naturally occurring phages that can be identified, studied and adapted for medical use. \u201cThere is no answer to that,\u201d he said. \u201cIt is an open question.\u201d<\/p>\n The study itself also demonstrated the technology\u2019s limitations. Only a small proportion of the designs generated by the models became functioning phages. \u201cThere is still a huge learning process here,\u201d Nir-Paz said, adding that researchers will need substantially more data and much better models before their outputs can be relied upon consistently. \u201cLike ChatGPT and similar systems, we don\u2019t know how to identify when the machine is lying,\u201d he said. And alongside those limitations comes the other side of the equation. \u201cThe machine can also generate dangers,\u201d he said.<\/p>\n That concern sits at the heart of the growing debate over AI and biology. As models become better at designing biological systems, the same capabilities that could help scientists understand nature or develop new treatments could potentially be used to create systems with properties that did not previously exist.<\/p>\n Prof. Tal Brosh, director of the Infectious Diseases Unit at Assuta Ashdod Hospital, stressed that the bacteriophages involved in the current study do not directly threaten humans. Bacteriophages occur naturally in the human body, but they attack bacteria rather than human cells. \u201cBacteriophages are not something that endangers us in any way, because these are viruses of bacteria,\u201d Brosh said. \u201cThey can harm bacteria, not human beings.\u201d<\/p>\n \u201cWhat this does show us is the improving capabilities of what is called synthetic biology, the ability to use very advanced biological tools and genetic manipulation to change living organisms or create living organisms from scratch.\u201d<\/p>\n The medical possibilities are significant. Synthetic biology could help produce new bacteriophages against antibiotic-resistant bacteria and improve existing applications of engineered viruses for treatment. \u201cThere can be many very beneficial uses for these technologies,\u201d Brosh said.<\/p>\n But the same ability to alter biological systems could also be misused or produce dangerous unintended consequences. \u201cThere could be misuse or a laboratory accident that ends with someone taking a virus, bacterium or some organism and making it more virulent, more contagious or resistant to existing treatments or vaccines,\u201d Brosh warned. \u201cThere are certainly laboratories and scientists capable of doing such things.\u201d<\/p>\n![\"\u05d1\u05e7\u05d8\u05e8\u05d9\u05d5\u05e4\u05d0\u05d2'\u05d9\u05dd\"](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2026\/08\/r1UHmVei8Ml_0_0_1000_667_0_x-large.jpg\" "\\"New")
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Prof. Tal BroshPhoto: Courtesy<\/p>\n
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