Chai Discovery Secures $70M for AI-Driven Molecular Discovery in Drug Development

Chai Discovery raises $70M to build molecular discovery foundation AI models - SiliconANGLE

Chai Discovery raises $70M to build molecular discovery foundation AI models Chai Discovery, a company that builds frontier artificial intelligence models to predict and reprogram interactions between biochemical molecules, today announced it has raised $70 million to continue its mission to accelerate how scientists create therapeutic medicines. Menlo Ventures led the company's Series A round, which brings the total funding raised by Chai to $100 million. The round included investment from Menlo's Anthology Fund, a joint partnership with Anthropic PBC to identify and back promising AI companies, with additional participation from new investors Yosemite, DST Global Partners, SV Angel, Avenir, DCVC, and existing investors Thrive Capital, OpenAI, Dimension, Neo and others. Founded in 2024, the company develops and deploys foundation models for AI-driven drug discovery. Last month, the Chai team unveiled Chai-2, what the company calls a breakthrough AI model for zero-shot molecular design, achieving "unprecedented double-digit success rates when designing fully de novo antibodies." This means Chai-2 can design and program antibodies, the Y-shaped proteins produced by the body's immune system for defense against foreign objects like bacteria and viruses, more effectively than previous methods. When testing just 20 designs using Chai-2, the model routinely discovers viable hits across a multitude of targets, the company said, claiming a near 20% hit rate, making it a clear contender for rapid and precise atomic-level molecular engineering. In comparison, traditional laboratory methods must test millions of samples and billions of antibodies to find hits, and the previous computational analysis methods had a hit rate of only 0.1%. "Progress toward game-changing drugs and treatments is far too slow, stymied by costly trial-and-error experiments," said co-founder and Chief Executive Joshua Meier. "Chai Discovery exists to push the boundaries of what's possible in this field, applying frontier AI to transform biology from science to engineering, so that breakthroughs can be designed rather than simply discovered." Drug discovery is an industry where AI and AI models can have a significant impact, and many companies have emerged to capitalize on this opportunity. AI model developers and AI platform companies such as Alphabet Inc.'s Google DeepMind, Latent Labs Inc., Terray Theraputics and Synfini Inc. have put AI to use with protein, molecular and biochemical discovery for therapeutics across numerous domains. According to Chai, its models have already shown significant promise. The company intends to use the funding to develop its platform further, applying it towards formerly inaccessible targets and bringing on board more partners. "Before Chai-2, the process was not unlike searching a giant bunch of keys for the right fit for a lock -- but there are millions of keys," said co-founder Matthew McPartlon. "Now, it's like having a master locksmith design exactly the right shape key, based only on your description of the lock."

OpenAI-Backed Biotech Startup Chai Discovery Raises $70 Million Led by Anthology | AIM

The startup will use the funds to advance its flagship AI platform, including its latest model, Chai‑2. AI-driven biotech startup Chai Discovery has secured $70 million in series A funding, elevating its valuation to approximately $550 million. The round was led by Menlo Ventures through its Anthology Fund -- a joint effort with Anthropic -- alongside new investors Yosemite, DST Global Partners, SV Angel, Avenir, DCVC, and contributions from returning backers Thrive Capital, OpenAI, Dimension, Neo, Lachy Groom, and Fred Ehrsam. https://twitter.com/joshim5/status/1953157471272616442 The startup will use the funds to advance its flagship AI platform, including its latest model, Chai‑2, which delivers fully de novo antibody design with a ~20% hit rate -- far above the ~0.1% success rate of traditional lab-based methods. Mikael Dolsten, former chief scientific officer at Pfize