End-to-End Antibody Discovery: Yeast Display, Automation, AI, and Multispecifics

In this High-Affinity Talks session, Andre Teixeira from the Institute for Protein Innovation walks through an integrated platform that pushes antibody and nanobody discovery past 200 targets per year by combining yeast surface display, laboratory automation, and AI-guided clone triage. Most of the human surfaceome and secretome still lacks monoclonal antibodies validated for anything beyond western blot, and therapeutic pipelines remain crowded around a handful of targets. This talk lays out how the IPI team built a discovery pipeline to close that gap at scale. Teixeira covers the full architecture — antigen production, library sorting, single-clone characterization, and validation — and the design choices that make this throughput sustainable rather than heroic. The session also shows how the same pipeline supports rational engineering of new functions, including biparatopic antibodies that crosslink cell-surface receptors to drive axon growth. The goal is a concrete blueprint for running discovery at this scale, and an honest view of where automation and AI actually move the needle and where they don't. Methods and concepts covered: high-throughput antibody and nanobody discovery, yeast surface display, laboratory automation for discovery, AI-guided clone triage, antigen production, library sorting, single-clone characterization and validation, and biparatopic antibody engineering. Questions this session answers: How do you scale antibody discovery to hundreds of targets per year? How is laboratory automation used in antibody discovery? Where do AI and automation actually help in antibody discovery, and where don't they? What is yeast surface display and how is it used for antibody and nanobody discovery? How are biparatopic antibodies engineered to drive new functions? Hosted and moderated by MiLaboratories, the creator of Platforma — an end-to-end antibody discovery platform that takes teams from NGS data to developable, diverse lead candidates, built on the open-source MiXCR toolkit. Learn more: https://platforma.bio Part of the High-Affinity Talks series by MiLaboratories.