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Drug Discovery

6 GoKawiil briefs on this topic

Enveda raises $311M Series E at $2B valuation for AI-driven natural drug discovery

Enveda, a biotech startup using AI to identify drugs from plants and microbes, closed a $311 million Series E funding round at a $2 billion valuation. Catalio Capital Management led the round, with Iconiq and other investors participating. The valuation doubles what the company achieved a year earlier.

Anthropic opens Bay Area wet lab to test AI-driven biology research

Anthropic has quietly opened a physical biology lab in the San Francisco Bay Area, confirmed by its Head of Life Sciences Eric Kauderer-Abrams to Reuters. The lab supports both in-house experiments and outside collaborations, and is linked to but not limited to Claude Science, the drug discovery initiative Anthropic launched in June.

Novo Nordisk Teams Up With Anthropic to Apply Claude AI in Drug Discovery

Novo Nordisk has entered a partnership with Anthropic to integrate the Claude AI model into its drug-discovery operations. The collaboration is designed to build targeted tools and workflows aimed at resolving persistent bottlenecks in pharmaceutical research.

Quantum computing nears practical use, raising encryption security concerns

Executives from Nord Quantique and QuSecure discussed how quantum computing is moving from theoretical research toward real-world application, with heavy investment from governments and companies. They highlighted potential across drug discovery, materials science, finance and logistics, alongside the parallel risk quantum poses to current encryption standards.

AI-designed anti-aging drug shows promise in early human trials

Researchers testing an AI-designed anti-aging drug reported that it lowered participants' biological age, as measured by aging clocks, in every case in the trial. The drug's development leaned on artificial intelligence tools to identify compounds likely to slow or reverse aging markers in the body.

AI-driven lab in Shanghai identifies novel non-opioid pain drug candidate

Researchers using an automated laboratory in Zhangjiang, Shanghai encountered an unexpected experimental result that led to the identification of a new non-opioid pain treatment candidate. The discovery reportedly emerged from AI-assisted experimentation rather than traditional hypothesis-driven research, suggesting machine learning systems can surface biological insights humans might not have anticipated.