In-Vitro Antibody Discovery Masterclass: Mining Display Libraries for Top Leads

How do you select the best antibody leads from a phage or yeast display panning campaign — without building custom bioinformatics pipelines? This masterclass walks through practical, end-to-end lead-selection workflows in Platforma, showing how teams move from raw selection-output sequencing to a diversified, developable panel of candidates. Antibody discovery teams increasingly need to make lead decisions earlier, without being slowed by fragmented tools or complex custom pipelines. This session is for scientists and discovery leaders who want to go beyond theory and see how teams turn display panning data into confident lead-selection decisions, using real-world examples in Platforma — a no-code antibody discovery platform built on the open-source MiXCR toolkit. What you'll learn: Repertoire characterization for panning campaigns: use rarefaction and clonal-dominance (Gini index) checks to confirm your campaign captured high-quality, reproducible data before you trust any hit. Clustering and motif-level analysis: group binders into lineage and paratope clusters to collapse redundant sequences, reveal shared binding motifs, and diversify your lead panel. Enrichment tracking across selection rounds: follow log-fold-change enrichment trajectories to classify binders as stable, rescuer, weak, or parasite, and separate true binders from noise. Specificity filtering with negative controls: use target-versus-control enrichment to reject sticky, non-specific binders before they reach synthesis. Developability-based prioritization: rank candidates by developability and sequence liabilities to surface risk early, not after synthesis. Methods and concepts covered: phage and yeast display panning analysis, selection-output NGS, rarefaction and Gini-index quality control, enrichment analysis and log-fold-change trajectories, enrichment-quality classification (stable, rescuer, weak, parasite), negative-control specificity filtering, sequence and paratope clustering, developability and liability assessment, and no-code lead selection. Questions this masterclass answers: What's the best software for phage display NGS analysis? How do you select antibody leads from a panning campaign? How do you track enrichment across selection rounds to identify true binders? How do you combine enrichment and developability when selecting antibody leads? How do you filter out non-specific binders from display data? Why Platforma: End-to-end, no-code workflow: run the full discovery pipeline — from raw sequencing to lead selection — in one interactive interface, without writing code or stitching together separate tools. Billion-scale processing: analyze billions of sequences without hitting computational bottlenecks or moving data between systems. Intelligent lead selection: rather than a naive Top-N sort that returns redundant clones, Platforma filters, scores, and diversifies — selecting the best representative from each clonal family to deliver a structurally diverse, developable lead panel in one step. Built around your biology: configure non-standard formats (VHH, bispecifics such as knob-in-hole, tri-specifics, custom scaffolds) and unconventional experimental designs (deep mutational scanning, pH-switch selection, multi-arm panning, Tite-Seq) to match your protocol Transparent, not a black box: every filter, weight, and ranking rule is visible and editable, with open-source, auditable block logic built on published, gold-standard engines like MiXCR. Deploy where your data lives: run in your own cloud or fully on-premise, with data sovereignty as a foundational feature — not an add-on.