Nuclera launched an antibody triage service to streamline the transition from AI-driven antibody hit generation to lead selection, targeting a bottleneck in experimental validation. The service uses 96-plex binary cell-free expression and binding assays to narrow large candidate sets to confirmed binders before costly mammalian scale-up. Nuclera said it then performs surface plasmon resonance on prioritized hits to assess binding kinetics, aiming to reserve downstream functional testing for candidates with early evidence of binding activity. The launch follows a Series C extension enabling integration of antibody expression and binding validation into its workflows. For the biotech industry, the practical value is throughput and cost control: AI models can generate large libraries, but experimental screening capacity often becomes the constraining step. An early-exclusion triage layer can compress cycle times and improve portfolio decision-making. The company positioned the service as a bridge between computational discovery and recombinant antibody validation, where failures and wasted expression resources are expensive.