BOSTON — Nuclera has launched an antibody screening service designed to help researchers move more efficiently from AI-generated antibody candidates to lead selection.
The company, which is based in Cambridge, England, and Boston, said the service is intended to address a key bottleneck in AI-driven antibody discovery by helping researchers identify the most promising antibody candidates before moving into more costly mammalian expression and functional testing.
Nuclera said the service uses cell-free technology to convert AI-generated candidates into experimental binding data, allowing researchers to eliminate non-binders earlier in the process.
The launch follows Nuclera’s Series C extension and supports the company’s broader effort to integrate antibody expression and binding validation into antibody discovery workflows.
Nuclera’s antibody service provides an upstream triage workflow between in silico hit generation and mammalian scale-up. The company said it uses 96-plex binary cell-free expression and binding assays to screen full-length antibody libraries in parallel, narrowing large candidate sets into a smaller group of confirmed binders. Surface plasmon resonance is then performed on prioritized hits to assess binding kinetics.
Despite advances in bioinformatics and in silico antibody design, Nuclera said researchers still face challenges in experimentally validating large numbers of antibody candidates. Traditional secondary screening methods can be slow and fragmented, leading companies to spend significant resources on candidates that ultimately do not bind.
As AI-driven approaches generate larger antibody libraries, Nuclera said rapid and cost-effective triage tools are becoming more important. The company said its service is designed to convert large AI-generated libraries into experimental binding data and reserve expensive downstream testing for candidates that have already shown binding activity.
“Antibodies are one of the most important classes of therapeutic molecules, yet antibody discovery remains inefficient, with many initially promising candidates failing during downstream validation,” said Dr. Michael Chen, CEO and co-founder, Nuclera. “A key bottleneck is the cost of recombinant antibody expression and binding validation, which limits the generation of high-quality data, and is holding back the full potential of AI/ML discovery. The launch of our antibody service addresses this challenge by enabling rapid triage of large candidate sets and delivering decision-grade binding data early in the discovery process at a competitive cost. By helping teams focus on the most promising candidates before scale-up, we are taking an important step toward enabling more effective use of AI in antibody discovery.”
