London-based Basecamp Research has pulled in a $140 million Series C to push its biological foundation models toward clinical-stage drug discovery.
The round was led by S32, a California VC firm, and sets an ambitious target: move beyond protein design into medicines built directly from its AI platform.
The funding marks one of Europe’s largest biotech AI raises this year. It follows a $56 million Series B in 2023 and signals growing investor appetite for startups combining generative AI with wet-lab biology.
Basecamp Research says its advantage lies in proprietary data. Unlike rivals that train models on public databases, the company gathers biological information from extreme environments around the world, including rainforests, deserts, and deep-sea vents. This “novel biodiversity” approach, the company argues, creates models that understand biology more deeply than anything currently available.
“We are building the largest and most diverse biological dataset on Earth. That lets us train models that simply cannot be matched by anyone else,” said a Basecamp Research spokesperson. “AI-designed medicines using this data could reach human trials faster than people expect.”
The fresh capital will fund expansion of its data collection network and accelerate the development of its next-generation biological models. Basecamp Research also plans to build internal drug discovery programs and partner with pharmaceutical companies.
Meanwhile, S32’s involvement brings significant Silicon Valley credibility. The firm has backed major AI infrastructure plays, including an investment in Anthropic, one of the leading AI labs. Basecamp Research now joins that portfolio alongside some of the most heavily funded names in machine learning.
Basecamp Research was founded in 2019 and operates as a hybrid between a biotech company and an AI research lab. The company claims its models outperform industry standards on protein structure prediction and design tasks.
With the new capital, Basecamp Research expects to file its first investigational new drug applications within the next two years.
