Chai Discovery nabs $400M Series C as ai-designed antibodies reach big pharma. Chai Discovery Inc., a company that develops artificial intelligence models to predict interactions between biochemical molecules, today announced it has raised $400 million in Series C funding, nearly tripling its valuation to $3.8 billion. Index Ventures led the round alongside Kleiner Perkins, Sequoia Capital and Dimension. New investors joining the investment included Bain Capital Ventures, Battery Ventures, Baillie Gifford, BDT & MSD, Sapphire Ventures, Avra Capital and other notable investors. Existing investors included Thrive Capital, OpenAI, Oak HC/FT, Menlo Ventures and General Catalyst, among others. The round raises the company's total funding to around $630 million to date, including $130 million at a $1.3 billion valuation in December. Chai Discovery builds frontier AI models designed to accelerate drug discovery. They act by predicting and reprogramming molecular interactions, a necessary first step toward fully understanding how chemistry works for pharmaceutical and life sciences companies. "Tomorrow's medicines should be designed with the precision, speed and scale of modern engineering, and this support helps us move faster towards that future," said co-founder and Chief Executive Joshua Meier. "AI drug discovery has moved from promise to deployment." The company says that its latest model Chai-3 is a "step-change" over the previous generation Chai-2. It reportedly doubles success rates for molecular interaction targets, implying around 35% to 40% hit rates. The company targets enhanced bonding affinity and broader antibody design foundations. Chai Discovery targets antibodies because they are part of the body's primary defense against foreign invaders. Antibodies act as custom locks designed to identify and lock down attackers. The problem: there are roughly a quintillion (1 with 18 zeroes) customizations that can uniquely target foreign bodies. The old way of discovering which ones worked involved screening millions of potential molecules and testing them one by one. To tackle this problem, Chai created an AI system that can perform rapid simulations based on disease targets to design a molecule that fits correctly. It doesn't need to guess, no pile of random molecules, instead it curates the vast set of possibilities to generate a likely high-quality candidate. Recent commercial traction for the company includes a landmark licensing agreement with Pfizer Inc., granting access to Chai-3, as well as an AI model trained on the pharmaceutical company's proprietary data. It has also signed a customer agreement with the American multinational pharmaceutical company Eli Lily and Co. and formed a formal collaboration with the Swiss multinational drug company Novartis AG. Chai faces a very real climb within the drug discovery industry. According to an executive report from Excelra Knowledge Solutions Pvt. Ltd., an AI life sciences company, despite around $20 billion being poured into generative AI drug discovery, no AI-discovered drug has been approved yet. According to OncoDaily, a news site about cancer research and treatments, there are more than 173 AI-originated drug programs now in clinical development, up from almost two dozen in 2023. Around 15 to 20 are expected to reach working trials in 2026. The reason is that although AI-driven discovery achieves fairly high accuracy, with Phase I pass rates at 80% to 90%, it drops to around 40% in Phase II. This matches up with the rates of traditional methods. Ideally, drug discovery and life sciences will need to overcome this hurdle by gaining a better understanding of candidates and their effects as they advance into clinical trials. 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Chai Discovery, an AI-driven drug startup, has secured $400 million in funding, valuing the company at $3.8 billion. The round was announced on 14 July 2026 and includes venture capital firms and strategic investors. The startup uses machine learning and data analytics to streamline drug discovery. Its platform analyses vast datasets to identify potential drug candidates more efficiently than traditional methods, potentially reducing development time and costs. The investment reflects growing venture capital interest in AI technologies within healthcare. The funding will enable Chai Discovery to expand its research team and operational capabilities. As AI becomes more integrated into pharmaceuticals, collaboration between AI startups and traditional pharmaceutical companies is expected to increase. The success may encourage similar startups to pursue innovative solutions in drug development.

Transforming biology from science to engineering: its investment in Chai Discovery. When you first meet Joshua Meier, it's impossible not to notice his intense curiosity, clarity of thinking and passion for the problem he's working on. Within just a few minutes of talking to Josh, I knew this was someone Bit Odd had to get to know. Josh has been seeking a better way to do drug discovery since he was a teenager, when he was researching in his high school's stem cell lab. After graduating from Harvard University, double majoring in CS and Chemistry, Josh joined OpenAI in 2018, where he was exposed to the cutting edge of what AI could do. Despite being one of the most promising young hires there, he left to seek out a place that was truly focused on applying this problem of AI to biology, first at Meta's FAIR Lab, then at Absci, and ultimately deciding to start Chai Discovery. Josh and his co-founder, Jack Dent have been friends since their days together in CS125, a notoriously difficult computer science class at Harvard. I'd heard Jack's name through the Stripe ecosystem, where he became the company's youngest staff engineer, leading multiple special projects, like Stripe Capital, Stripe Link, and Stripe Billing. Together, their vision and drive are exactly the combination needed to tackle a problem as deeply rooted as the one they're trying to solve at Chai. That problem - drug discovery as Bit Odd know it today - is essentially a brute-force search problem. Bringing a single drug to market can take 10-15 years and $2-3 billion in R&D. The process of finding a drug is a sequence of iterative wet-lab cycles. Early molecular discovery often requires repeated experimental and computational cycles to identify molecules that meet therapeutic properties. The fundamental challenge is that the molecular search space is essentially infinite: there are more possible drug-like molecules than atoms in the observable universe, and biology has given Bit Odd an incomplete map. Chai takes a radically new approach, building AI models that predict and reprogram molecular interactions and a software platform that puts those models into the hands of scientists at leading life sciences companies. Instead of relying on large experimental screens of molecular combinations in a lab, scientists can use Chai's platform to predict how an antibody would bind to a particular target - like designing the perfect key before you ever touch a lock. As the team puts it, the model is the breakthrough, but the product is how it reaches every scientist on earth. Earlier this year, Chai announced a partnership with Eli Lilly to accelerate the development of its biologics therapeutics, with Lilly deploying Chai's core models and software platform and Chai building a custom foundation model on Lilly's data. Just a few weeks ago, Chai announced a second agreement with Pfizer to deploy Chai's platform for drug discovery. And more recently, they announced a collaboration with Novartis to apply Chai's AI models to antibody discovery across multiple therapeutic programs. When three of the world's largest pharma companies publicly commit to Chai within months of each other, it tells you how quickly this is moving from promise to practice. It also speaks to the talent and conviction of the team behind it. At Chai, Josh and Jack are joined by co-founders Matt McPartlon, who leads research, and Jacques Boitreaud, who leads applied science. Together they've assembled what they call a RenTec-style guild of mathematicians, physicists, systems hackers, comp-bio PhDs, GPU-kernel wizards, and engineers, describing themselves as a "craft-obsessed team of micro-pessimists and macro-optimists who love what we do." Biology is one of the largest and most consequential markets AI has yet to touch. Bit Odd has been building conviction here for years, with disruptive investments in companies like Cradle and Causaly. Chai is the latest expression of that thesis, and Bit Odd is excited to continue to invest in this space. Bit Odd is delighted to partner with Josh, Jack, Matt, Jacques, and the entire Chai team as they continue on their mission to transform biology from science to engineering and build the platform for a new era of drug discovery. Published - July 14, 2026