We're launching Challenge 1 of the Anthropic x Adaptyv Protein Design Competition on @proteinbase: design a conditional binder to EGFR, a key cancer target. The goal: bind EGFR under the acidic conditions of the tumor environment, but not at the normal pH around healthy cells. Moreover, the proteins must bind to both the human and the mouse variant of EGFR to support easier preclinical testing

Entry is free and open to everyone, with up to 20 designs per participant. We only accept de novo designs, meaning their amino acid sequences must be substantially different from those of known binders. Designs must be 10–250 amino acids long, in single-chain, scFv or Fab format.

Back in 2024, BindCraft1 emerged as one of the strongest methods in our protein design benchmarks, winning our first EGFR competition and becoming one of the most widely used approaches in the following round. We’re happy to see BindCraft2 released just in time for our new protein design competition with Anthropic, where more than 5,000 designs will be experimentally tested in our lab. Show us what you can do with BindCraft2!

We’re partnering with @Anthropic to launch the biggest Protein Design Competition in the world, challenging people around the world to use AI to design new potential drug candidates for diseases that affect millions of lives. The competition will feature five challenges, each focused on a specific disease or biological mechanism. Compared to previous competitions, it will be a big step-up in complexity and scale to push the boundaries of AI-driven protein design. Together with Anthropic, we’re sponsoring over $1 million in experimental validation, making it possible to test more than 5,000 protein designs in our automated lab at no cost to participants. Anthropic is providing an additional $1 million in Claude credits. All experimental results will be published openly on @Proteinbase, including designs that didn’t work, so anyone can access the data and build on what we learn. The competition is open to everyone and free to enter. It will feature 3 tracks: - Track 1 is aimed at expert protein designers, with up to 20 teams to be selected. - Track 2 is targeting life science academics and industry researchers. - Track 3 is open to everyone from tech enthusiasts to high-school students. By combining Anthropic’s models with access to our automated lab, we want to make it possible for anyone with a laptop and an internet connection to join the global effort to advance human health with AI. A big thanks to @Modal for contributing compute for protein design and to @TwistBioscience for contributing the DNA for the experimental validation! Sign up link below -

We're bringing experimental validation to @OpenAI's Rosalind Workbench through the Adaptyv API. Rosalind Workbench is a new way to orchestrate complex life science research workflows across models and specialized scientific tools. Through the Adaptyv API, those workflows can now run full design–build–test–learn cycles in our wet lab, with real experimental data feeding directly into the next round of designs.

We raised a $40M Series A to build the automated lab for agentic biology. Last week, we shared the work we did with @Anthropic: Claude designed proteins, sent them to our automated wet lab, and got real experimental data back. We believe this is where biology is going: AI agents designing experiments, running them in automated wet labs, learning from the results and iterating. But AI can only move as fast as the experiments behind it. To use the potential of AI to cure all diseases, we need to build high-throughput wet lab infrastructure: a “biological gigafactory”. That’s exactly what we’re doing at Adaptyv. Over the past year we’ve grown our lab throughput by over 5x and onboarded more than 100 customers, ranging from bio AI labs like @chaidiscovery and @boltz_bio to pharmas like @Roche and @novonordisk to dozens and dozens of new startups that use AI to radically speed up drug discovery.

The round was led by @HighlandEurope with existing investors ACE Ventures, @byFounders and @ycombinator doubling down.