End-to-End Antibody Discovery: Yeast Display, Automation, AI, and Multispecifics
Our High-Affinity Talks features Andre Texeira from the Institute for Protein Innovation. Most of the human surfaceome and secretome still lack monoclonals validated for anything beyond western blot, and therapeutic pipelines remain crowded around a handful of targets. The team built an integrated platform that pushes antibody and nanobody discovery past 200 targets per year, combining yeast surface display, laboratory automation, and AI-guided clone triage. They walk through the architecture of the platform, including antigen production, library sorting, single-clone characterization and validation, and also the design choices that make this throughput sustainable rather than heroic. They also show 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 to give the audience a concrete blueprint for running discovery at this scale, and an honest view of where automation and AI actually move the needle. This discussion is hosted and moderated by MiLaboratories, the creators of the leading biologics discovery software.
Structural plausibility without binding specificity: limits of AI antibody-antigen prediction
Accelerating In-Vivo Antibody Discovery: Unlocking Immunization Data & Maturation Pathways
Computational predictions of BCR properties and relations to B cell development and maturation
In-Vitro Antibody Discovery Masterclass: Mining Display Libraries for Top Leads
RNA-seq: Run Cell Ranger for 10x scRNA-seq data
Streamlining TCR α/β Discovery: Miltenyi’s TCR-Profiling Chemistry and Platforma’s Advanced Analysis
scRNA-seq: Compositional analysis
Antibody Discovery: Lead Selection
RNA-seq: Dimensionality reduction and batch correction
Miltenyi TCR Clonotyping
RNA-seq: import raw FASTQ files
RNA-seq: Differential Gene Expression
Antibody Discovery: Sequence Liabilities
scRNA-seq: Leiden clustering
