The process of discovering new drugs, which involves identifying novel molecules for pharmaceutical development, is famously slow and challenging. Conventional methods such as high-throughput screening are costly and inefficient, often yielding limited success. Today, a wave of biotech firms is turning to artificial intelligence and sophisticated data tools to speed up and refine this workflow. Among them is Chai Discovery, an AI startup established in 2024. In just over a year, its founders have secured hundreds of millions in funding and gained support from top Silicon Valley investors, positioning the company as a standout in an expanding sector.

In December, Chai closed a Series B round, raising an additional $130 million and reaching a valuation of $1.3 billion. Then, last Friday, the startup revealed a partnership with pharmaceutical leader Eli Lilly, under which the company will use Chai’s software to aid in developing new treatments. Chai’s algorithm, named Chai-2, is built to design antibodies—the proteins essential for combating disease. The startup aims to function as a “computer-aided design suite” for molecular development.

This announcement comes at a pivotal time for the field. Shortly before the Chai deal, Eli Lilly also disclosed a $1 billion collaboration with NVIDIA to establish an AI drug discovery lab in San Francisco. Dubbed a “co-innovation lab,” the initiative will integrate large-scale data, computational power, and scientific knowledge to hasten the creation of new medicines.

Still, the industry faces skepticism. Some experienced observers caution that, given the inherent difficulties of drug development, emerging technologies may not deliver transformative results. Yet for each doubter, there appears to be an equally strong believer. “We believe the biopharma companies that move the most quickly to partner with companies like Chai will be the first to get molecules into the clinic, and will make medicines that matter,” said Viboch. “In practice that means partnering in 2026 and by the end of 2027 seeing first-in-class medicines enter into clinical trials.”

Aliza Apple, who leads Lilly’s TuneLab program—an effort using AI and machine learning to advance drug discovery—also voiced optimism about Chai. “By combining Chai’s generative design models with Lilly’s deep biologics expertise and proprietary data, we intend to push the frontier of how AI can design better molecules from the outset, with the ultimate goal to help accelerate the development of innovative medicines for patients,” she explained.

Though Chai was officially founded less than two years ago, its origins trace back about six years, to discussions between its co-founders and OpenAI CEO Sam Altman. Co-founder Josh Meier had worked at OpenAI in 2018 on its research and engineering team. After he departed, Altman reached out to Meier’s former college friend, Jack Dent, to explore a potential business venture. Meier and Dent had first met in computer science classes at Harvard, but at the time Dent was an engineer at Stripe—another company Altman supported early on.

Altman inquired whether Meier might be interested in collaborating on a proteomics startup focused on protein research. “He messaged me to say that everyone at OpenAI thought highly of him and asked if I thought he’d be open to working with them on a proteomics spinout,” Dent recalled. Dent responded positively, but there was an obstacle: Meier believed the underlying technology wasn’t yet ready. The AI systems powering such ventures were still evolving, and Meier was committed to joining Facebook’s research and engineering team, which he did.

At Facebook, Meier contributed to developing ESM1, the first transformer-based protein-language model—a significant forerunner to Chai’s current work. He later spent three years at Absci, another AI-driven biotech focused on drug creation. By 2024, Meier and Dent felt equipped to pursue the proteomics company they had initially discussed with Altman. “Josh and I reached back out to Sam and told him we should pick up that conversation where we left off—and that we were starting Chai together,” Dent said.

OpenAI subsequently became one of Chai’s earliest seed investors. Meier and Dent, along with co-founders Matthew McPartlon and Jacques Boitreaud, actually launched Chai while working out of OpenAI’s offices in San Francisco’s Mission district. “They were kind enough to give us some office space,” Dent noted.

Now, just over a year later, as Chai celebrates its new alliance with Eli Lilly, Dent attributes the company’s rapid growth to bringing together an exceptionally skilled team. “We really just put our heads down and pushed the frontier of what these models are capable of,” he said. “Every line of code in our codebase is homegrown. We’re not taking LLMs off the shelf that are in the open source [ecosystem] and fine-tuning them. These are highly custom architectures.”

Looking ahead, Dent remains confident in the practical application of such models. “There are no fundamental barriers to deployment of these models in drug discovery,” she stated. “Companies will still need to take drug candidates through testing and clinical trials, but we believe there’ll be significant advantages to those who adopt these technologies—not just in compressing discovery timelines, but also in unlocking classes of medicines that have historically been difficult to develop.”