A biotechnology startup, 10x Science, has raised $4.8 million in a new funding round to accelerate the use of artificial intelligence in drug discovery and development, the company announced on Thursday.
The round was led by early-stage investors focused on deep-tech and healthcare innovation, with participation from several venture capital firms and angel investors. The fresh capital will be used to expand 10x Science’s AI platform, grow its research team, and advance preclinical drug candidates.
“The people building AI have historically not been life scientists, and the life scientists have not been building AI; we come from both worlds,” said co-founder and CEO David Stephen Roberts, describing the company’s interdisciplinary approach to drug discovery.
Founded with a focus on integrating machine learning into biomedical research, 10x Science is developing tools to accelerate target identification, optimise molecular design, and improve the prediction of clinical outcomes. The company says its platform aims to reduce the time and cost traditionally associated with bringing new therapies to market.
Roberts added that the company aims to build systems capable of “reasoning about proteins at the level of expert scientists, but at a speed and scale that traditional research workflows cannot match.”
According to the startup, the funding will also support partnerships with academic institutions and pharmaceutical companies to validate its AI-driven drug discovery models.
Initialised Capital, one of the participating investors, said the founding team has deep domain experience in computational biology and artificial intelligence. “The 10x Science founders helped build this field, and they’re now applying that expertise to solve a critical bottleneck in drug development,” a partner at the firm said.
Industry analysts note that AI adoption in biotechnology is increasing rapidly, with startups and established pharmaceutical companies racing to improve efficiency in early-stage research pipelines. In any case, 10x Science remains silent about a timeline for its first drug candidate to enter clinical trials.
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