Chai Discovery

We raised $130M in Series B funding at a $1.3B valuation to build the computer aided design suite for molecules. The round was led by @GeneralCatalyst & @OakHCFT along with existing investors @ThriveCapital, @OpenAI, @_DimensionCap, @Neo, @lachygroom, @MenloVentures, @svangel, and Yosemite. We're also joined by new investors including @EmCollective and Glade Brook.

There are only a few other areas where AI has the potential to change lives more than the discovery and development of new medicines to improve lives for patients. We thank @jackdent and @BenjamineYLiu for this discussion about how America needs to continue to lead in biopharma R&D and harness AI to accelerate treatments and cures.

Pharma Bets Big on AI Platforms with Flurry of New Year Deals @chaidiscovery, @NOETIK_ai, and #Boltz have entered multi-year pharma partnerships focused on models, not molecules, hinting at AI’s “infrastructure moment” #biopharma #AI #drugdiscovery hubs.li/Q04050X10

Thank you @LucasRopek1 for this feature in @TechCrunch highlighting our journey at @chaidiscovery. Grateful to our partners @GeneralCatalyst and @EliLillyandCo for adding your perspectives on how Chai is helping to unlock medicines that have historically been difficult to drug.

Seeing a leading pharma organization move quickly to adopt these technologies reinforces our belief that many future drugs will be discovered with AI. Grateful to the teams on both sides who made this possible. Excited to see the medicines that get created from here.

As part of this work, Chai and Lilly are building a custom foundation model, trained on Lilly’s proprietary data and tailored to their internal discovery efforts.

We’re thrilled to announce our collaboration with @EliLillyandCo. We’ll be deploying Chai’s AI models to power biologics discovery across a broad set of drug programs at Lilly. This is a major step forward in pharma’s adoption of AI-native R&D.

The folks @chaidiscovery have been producing potential drug designs at an incredible clip. We get into the latest (and hopefully more real) era of AI-aided drug discovery on this week's pod corememory.com/p/is-the-era-o…

.@chaidiscovery raised a Series B just three months after their Series A, and we co-led it. GC's Elena Viboch recently joined @Bloomberg's @CarolineHydeTV alongside Chai Discovery co-founder @joshim5 to discuss our life sciences investment strategy and the breakthrough technology behind Chai Discovery. We believe 2026 will be the year of deployment for AI in pharma. Chai Discovery’s latest model, Chai-2, has achieved an 85% success rate in computationally designing molecules that meet drug-like properties. In our view, pharmaceutical companies that adopt this technology will leapfrog those who do not. We partner with companies like Chai Discovery to turn known biology and impossible chemistry into lifesaving treatments. Why we invested → generalcatalyst.com/stories/our-in… More on our life sciences thesis → generalcatalyst.com/stories/the-fu…

Thank you @NasdaqExchange!

Thank you Bloomberg @business for covering the story: x.com/business/statu…

We are actively growing our team of interdisciplinary engineers, researchers, and scientists. If you are excited by our work, we would love to hear from you: chaidiscovery.com/careers

We raised $130M in Series B funding at a $1.3B valuation to build the computer aided design suite for molecules. The round was led by @GeneralCatalyst & @OakHCFT along with existing investors @ThriveCapital, @OpenAI, @_DimensionCap, @Neo, @lachygroom, @MenloVentures, @svangel, and Yosemite. We're also joined by new investors including @EmCollective and Glade Brook.

Our team is attending NeurIPS this week and co-hosting a special event on Friday. Reach out if you're excited about deep learning x bio

I'll be at NeurIPS and MLSB this week in San Diego. DM me if you want to meet up and chat AI x Bio! 🎉

De novo antibody design — and broadly generative drug design as a whole — has been laser focused on optimizing target binding. But in order for these antibodies to actually become translatable therapeutics, we need to consider a host of other developability criteria including stability, aggregation, immunogenicity, manufacturability, etc. Today, Chai-2 breaks this mold by designing full length mAbs against difficult targets (GPCRs and pHLA) with both high affinities AND clean developability profiles, taking a huge step forward for rationale drug design in silico. Huge congrats to the entire Chai team!