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Tech News
In its IPO filing, Anthropic acknowledged it lacks experience in physical lab experimentation and drug development, even as it continues to tout AI's potential to compress decades of scientific progress into years. The filing softened earlier claims about a 'Crispr-like' enzyme discovered by its Claude model, now describing it only as something that 'might have the potential' to become a gene-editing tool.
Kevin Weil, formerly OpenAI's science lead, has launched Warp Sciences, a startup that trains robots using camera and sensor-glove data from human chemists to automate wet-lab drug discovery work. The company has raised $215 million at an $865 million valuation in a round led by Lightspeed, with IVP, Premji Invest, and Lux Capital also participating, Weil announced on X.
OpenAI announced Tuesday it has acquired Orchestra Bio, a four-year-old startup that builds AI agents to help biotech firms manage drug discovery operations, including finances and clinical trial scheduling. Deal terms were not disclosed, though Orchestra had reportedly raised about $20 million from investors including Andreessen Horowitz, Atria, and 8VC. OpenAI plans to fold Orchestra's team and technology into Rosalind, its life sciences AI model, and the Rosalind Workbench tool used by customers such as Moderna and Novo Nordisk.
AstraZeneca has agreed to pay AI-driven biotech company Insitro $40 million upfront, with potential milestone payments bringing the total deal value to as much as $1.46 billion. The partnership centers on using Insitro's machine learning platform for drug discovery.
PostEra, a Y Combinator-backed biotech company, is hiring AI researchers to expand its agentic research team. The company uses its Proton platform to speed up medicinal chemistry work, has nominated multiple clinical candidates in women's health and fertility, and has secured over $1 billion in AI partnerships with firms including Pfizer and Amgen. It also runs an antiviral drug discovery center backed by a major NIH grant.
A commentary argues that the rapid expansion of AI computing infrastructure—chips, data centers, cloud systems and new power sources—needs applications that convert that capacity into real economic and human value. It points to medicine, particularly drug development, as a leading candidate for where that value could materialize.
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 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 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.
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.
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.
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.