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Enveda raises $311M to test AI-discovered natural drugs

Biotech startup Enveda has raised $311 million in Series E funding to accelerate human clinical trials for AI-discovered medicines derived from plants and microbes.

TechCrunch AI1 day agoBusiness
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Biotech startup Enveda has secured $311 million in a Series E funding round, propelling its valuation to $2 billion. Led by Catalio Capital Management with participation from Iconiq and other investors, this latest injection of capital doubles the valuation the company achieved just 12 months ago. The funding will be used to advance Enveda's pipeline of nature-derived, AI-discovered drug candidates further into human clinical trials.

Founded in 2019 by Viswa Colluru, a former early employee of Recursion Pharmaceuticals, Enveda aims to revolutionize medicine by identifying therapeutic compounds within plants and microbes. Rather than synthesizing molecules from scratch in a laboratory, the startup leverages artificial intelligence to rapidly scan and identify complex natural compounds that hold medicinal potential. This approach aims to dramatically accelerate the early stages of drug discovery, which traditionally take years of manual laboratory screening.

The startup is currently testing several of its AI-discovered candidates in human clinical trials. These include a treatment targeting severe skin conditions and another therapeutic designed to help patients maintain weight loss after they stop taking GLP-1 agonists. While the broader biotech industry has yet to see an AI-discovered drug receive final approval from the U.S. Food and Drug Administration, Enveda's progress represents a significant step forward for computational biology.

For practitioners and researchers in the pharmaceutical industry, Enveda's massive funding round and clinical progress validate the shift toward AI-driven natural product chemistry. By proving that machine learning can systematically unlock the therapeutic potential of the natural world, the company provides a blueprint for bypassing traditional synthetic chemistry. This shift could ultimately lower development costs and introduce entirely new classes of complex, nature-derived molecules to clinical pipelines.

This is our own summary of reporting by TechCrunch AI

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