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AI in HealthcareFortune AIPublished: Jun 15, 2026, 22:00 JST1 min read

A startup founded by researchers who created the first AI-designed virus has raised $50 million(約80億円) to build AI models that can read and write the language of biology—DNA, RNA, proteins, and beyond—all in a single system.

A startup founded by researchers who created the first AI-designed virus has raised $50 million(約80億円) to build AI models that can read and write the language of biology—DNA, RNA, proteins, and beyond—all in a single system.

3 Key Points

  1. What happened

    Radical Numerics emerged from stealth with a $50 million(約80億円) seed round led by Emergence Capital, with participation from Obvious Ventures, Triatomic Capital, Factory, and First Spark Ventures. The founding team—Eric Nguyen, Michael Poli, Stefano Massaroli, and Armin Thomas—built Evo and Evo 2, AI models that generate DNA at scale and are trained on the genomes of more than 100,000 species. Last September, researchers using Evo's open-source weights produced the world's first fully AI-designed functional virus (harmless to humans).

  2. Why it matters

    Most AI biology companies today focus on a single area—proteins or RNA—but Radical Numerics is betting that drug development's real bottleneck is understanding how molecules behave inside an entire biological system. The company has two early commercial partnerships: one applying its model to pancreatic and multi-cancer detection, and one with a national laboratory to detect and characterize pathogens. The overall AI drug discovery market is projected to reach $25 billion(約4兆円) by 2035.

  3. What to watch

    The company's revenue model is still taking shape and includes API licensing, fine-tuned proprietary models for pharma partners, and milestone payments. A major tension shadows the enterprise: the same models that could accelerate cancer diagnostics could also lower the barrier to designing biological weapons. The company brought on Andrew Weber, former U.S. assistant secretary of defense for nuclear, chemical and biological programs, as an advisor, and future model releases won't automatically be open-source.

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