Carterra enables Anthropic's autonomous AI protein design study - Scientist Live

Carterra, a provider of high-throughput surface plasmon resonance (HT-SPR) platforms for antibody and small molecule drug discovery, has highlighted the role of Carterra HT-SPR in one of the largest published wet-lab validations of AI-designed proteins to date.

In a study published August 18, 2026, Anthropic reported that its Claude models automatically ran de novo protein binder design campaigns against 15 challenging targets, researching each target, selecting epitopes, running open-source design tools, and providing ranked designs per target without human input into design decisions. Anthropic sent the protein designs to Twist Bioscience and Adaptyv Bio for analysis. Both use Carterra HT-SPR platforms to generate binding kinetics and affinity data at scale.

Protein design is essential in the early stages of a drug discovery campaign. Anthropic generates functional binders with hit rates exceeding prior methods in a matter of days, compared to the weeks or months it would take a human specialist. This creates an opportunity for drug developers and shifts the bottleneck from protein design to wet-lab experimental analysis. Carterra's HT-SPR technologies overcome this bottleneck, enabling large-scale affinity and kinetics binding data to be generated in days.

Josh Eckman, CEO and co-founder of Carterra, said, "This study shows the enormous potential of AI and Lab-in-a-Loop automation to accelerate drug discovery, when paired with high-throughput analysis platforms. An AI system generated thousands of novel binders in a matter of days. Two independent labs experimentally validated the protein designs in a few weeks. Carterra was built for this moment, when measurement has to keep up with design."

The ability to measure tens of thousands of binding interactions in a short period of time has changed the landscape of drug development. If done a few at a time on legacy SPR platforms, a campaign this size would consume months of instrument time and far more purified antigen than a design program would typically have on hand. Carterra's array-based approach compresses these complex experiments into a small number of unattended runs which consume around 1% of the small sample required by traditional systems.

Collecting data on several targets and designs on a single Carterra array unlocks scale that was previously impossible. When Anthropic wanted to compare Claude's best RBX1 binder with the winner of an earlier open design competition, the investigators put both on the same array. Claude's design measured 3.9nM versus 45nM for the previous winner, head-to-head, under identical conditions. As human, mouse, and cynomolgus versions of a target were run in parallel, Anthropic got species cross-reactivity, a preclinical-relevance question it had treated as a secondary objective, as part of the primary dataset instead of requiring a follow-up study.

Julian Englert, CEO and co-founder of Adaptyv Bio, said, "The bottleneck in AI drug discovery is the experimental validation of all those molecules that the AI models come up with. For large campaigns like this one, high-throughput SPR is the best method to get real binding kinetics data, which is why we're using Carterra SPR in our automated lab. That's what generates the data to train the AI models and improve the next round of designs."

The study follows Leerink Partners report from July 2026 that named Carterra a core enabling technology in the roughly $7 billion 'Lab-in-the-Loop' market for AI-driven antibody discovery, and identified binding affinity measurement as a central piece of the workflow.

Carterra's platforms combine flow-printing microfluidics with real-time array HT-SPR, delivering up to 100 times the throughput of traditional label-free platforms while using a fraction of the sample. The company has spent over two decades developing label-free biosensor technology, and its platforms are used by pharmaceutical companies for biologics and small-molecule characterisation.