Artificial intelligence has crossed a big milestone in biotechnology after researchers successfully used an AI model to create functional viruses that have never existed in nature. In a study conducted by scientists at Stanford University and California’s Arc Institute, an AI system called Evo was trained on trillions of genetic building blocks to learn the underlying patterns, or ‘grammar,’ of DNA. Using that knowledge, the model generated hundreds of entirely new viral genome designs.

Researchers then chemically synthesized the AI-created genetic sequences and introduced them into bacterial host cells. Sixteen of those designs successfully became working viruses, marking the first time AI-generated viral genomes have functioned in a laboratory. The viruses are bacteriophages based on the well-studied Phi X174 virus, meaning they infect only E. coli bacteria rather than humans.

The engineered viruses also proved capable of killing antibiotic-resistant bacterial strains that had evolved defenses against naturally occurring viruses. Scientists say the achievement could eventually help develop new treatments for drug-resistant infections and improve targeted gene therapies, while demonstrating AI’s rapidly expanding role in synthetic biology.

This breakthrough could have big implications for how scientists fight some of medicine's toughest challenges. Antibiotic-resistant bacteria have become increasingly hard to treat, as existing drugs lose their effectiveness over time, subsequently resulting in hundreds of thousands of deaths around the world each year…

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But AI-designed bacteriophages could offer a new way to target those infections by attacking bacteria that no longer respond to conventional antibiotics. The technology may also accelerate the development of personalized gene therapies and reduce the time needed to discover new biological treatments.

While it is a notable achievement, it also shows just how quickly artificial intelligence is advancing beyond its early models and into the designs of living organisms, drawing the attention of biosecurity experts who warn that similar AI systems could eventually be used to design more dangerous pathogens if adequate safeguards are not in place. Current regulations focus largely on physical laboratory research, leaving AI-generated genetic designs in a legal grey area.

In the near future, physicians may have access to treatments tailored to the specific bacteria causing an infection instead of relying on a wide spectrum of antibiotics that will lose their effectiveness over time. That could mean faster recoveries and fewer side effects, as well as more options for patients with infections that currently have limited treatments.

The technology could also speed up medical research by helping scientists test new ideas in mere months rather than over the course of years. If those efficiencies hold, new therapies could reach clinical trials sooner while also reducing many of the research costs.

A breakthrough like this could be the beginning of a new era where biology becomes increasingly programmable. As AI takes on a larger role in designing medicines and other biological systems, the pace of scientific discovery could accelerate far faster than laws and public policy can adapt. The challenge moving forward will be effectively optimizing the technology's enormous medical potential without allowing its capabilities to outpace the safeguards that are still being put in place.

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Mode Mobile received their ticker reservation with Nasdaq ($MODE), indicating an intent to IPO in the next 24 months. An intent to IPO is no guarantee that an actual IPO will occur.

Mode revenue and EBITDA numbers include full year revenue and EBITDA of businesses acquired by Mode Mobile in 2025.