Challenge 4 of the Anthropic × Adaptyv Protein Design Competition on @proteinbase is open: design a pH-sensitive protein to help shuttle drugs into the brain. TfR1 is a receptor protein that brings iron-loaded transferrin into cells. It is highly expressed in the blood-brain barrier and drug developers can use this receptor to get drugs to pass the blood-brain barrier. The drug is fused to a binder to TfR1, which makes cells absorb the protein complex. If the binder is pH-sensitive it will release from the receptor inside the endosome and then exit the cells on the brain-facing side to deliver the therapeutic into the brain. In this challenge, the goal is to make a pH-sensitive binder to TfR1 that targets precisely the right region on the receptor in order to allow absorption into the cell.

We’re sponsoring wet-lab validation for the Defense Bio Hackathon, hosted by American Bioenhancement today in San Diego 180+ designers, 300 designs wet-lab tested in 5 tracks: - Frontier bio - Biological data - Human performance - Biomanufacturing - Biosecurity See you there! luma.com/kfgh2fvu

Challenge 3 of the Anthropic × Adaptyv Protein Design Competition is open. You have to design a protein that switches on GLP1R, the receptor that semaglutide (Ozempic, Wegovy) and tirzepatide act on in type 2 diabetes and obesity.

Announcing Challenge 2 of the Anthropic x Adaptyv Protein Design Competition! Humira, the best-selling drug ever, blocks TNF-α, an inflammation marker protein that’s overexpressed in rheumatoid arthritis and Crohn’s disease. In this challenge, the goal is to make a better binder for TNF-α that also releases selectively at pH 6.0 in the endosome of cells to improve drug half-life. The protein must also bind both human and mouse TNF-α, making it easier to test the same design in preclinical models.

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.

Everything's open. Designs and binding affinity data on @proteinbase, all open-source under ODC-BY. Blog: adaptyvbio.com/blog/agents-v… Proteinbase collection: proteinbase.com/collections/…

What happens when you let frontier LLMs design proteins, and then synthesize and test them in a wet lab? We ran a protein design competition with @muni_bio where AI agents competed against humans to design molecules that bind TREM2, a key receptor linked to Alzheimer’s. Results: GPT 5.2 and Grok 4.1 both placed in the top 5, with molecules showing strong binding to TREM2 when tested in our lab.