Omniab, Inc. · NASDAQ:OABI
Omniab — Technical Presentation (December 2023)
31 slides from Omniab's technical presentation, Dec 15, 2023
Slide 1: Wrangling Diverse OmniAb Antibody Repertoires with OmniDeep
1 Wrangling Diverse OmniAb Antibody Repertoires with OmniDeep Bob Chen, PhD Antibody Engineering & Therapeutics US December 15, 2023
Slide 2: The OmniAb Technology Offering is Expanding
2 The OmniAb Technology Offering is Expanding TECHNOLOGY OFFERING ADDRESSES THE MOST CRITICAL CHALLENGES OF ANTIBODY DISCOVERY Create Screen Deliver Create Diverse Repertoires of Screen Millions of Cells to Find Further Characterize, Select and High-Quality Antibodies Potential Therapeutic Candidate
Slide 3: Deep Repertoires, Deep Sequencing, Deep Screening, Deep Learning
3 Deep Repertoires Deep Sequencing Deep Screening Deep Learning
Slide 4: Custom Antibody Repertoires for Every Target
4 Custom Antibody Repertoires for Every Target Biological Intelligence : Interplay between rational genetic design and powerful in vivo processes Animal 1: Animal 2: Animal 3: Protein Protein Genetic immunization immunization immunization Biological Intelligence can create a vast and diverse antibod
Slide 5: OmniAb Antibody Repertoires
5 OmniAb Antibody Repertoires BROAD PLATFORM AVAILABLE TO ADDRESS DIVERSE PARTNER OBJECTIVES Structural and Benefits for therapeutics Host V genes immunological features discovery and development • Full human V gene diversity • Diverse V gene usage and mixed • Widely accessible and flexible workflow
Slide 6: Common Light Chain Platforms
6 Common Light Chain Platforms STANDARD IGG FORMAT TO DE-RISK DOWNSTREAM DEVELOPMENT1 OF BISPECIFIC MABS Rearranged IgVK3-15/JK1 IgKC JK2-5 IgVK3-15/JK1 // Rearranged human VK3-15 light chain “Germlining” human VK3-15 light chain combined with diversifying heavy chain combined with diversifying heav
Slide 7: Deep Screening Platforms
7 Deep Screening Platforms AT TA A T Immunization Isolate B-cells Expression Validation Sequence Bioinformatics Hybridoma Workflow Fusion Screen B-cell Enrichment Single-cell optional NGS Workflow Our powerful single B-cell screening technologies, xPloration ® and GEM assay, bypass bottlenecks of hy
Slide 8: xPloration®: AI-Driven Deep Functional Screening
8 xPloration®: AI-Driven Deep Functional Screening 1 | Loading 2 | Assay + Machine Vision 3 | Recovery & Single-Cell NGS Fluorescent Bright Field Antibodies Cell Surface Binding Label-free GFP Immune Reporter Activation cAMP Signaling 20 hr Primary Cells 24-72 hr Input Prediction Input Prediction 1.
Slide 9: Assay
9 Assay
Slide 10: Assay
10 Assay Target cell Antibody secreting cell Confidential 10
Slide 11: Assay
11 Assay
Slide 12: Multi-Parameter Screening: Multiplex Phenotypic Data
12 Multi-Parameter Screening: Multiplex Phenotypic Data Selective binding of target on beads Selective binding of target cell Target Target B cell B cell Control Control BF Binding BF Binding Binding BF Binding Binding to Target Binding to Control Control
Slide 13: Laser Recovery
13 Laser Recovery 13
Slide 14: Rapid Laser Recovery of Hits
14 Rapid Laser Recovery of Hits Example target cell specific hits Binding BF Binding BF 1x speed video of laser recovery
Slide 15: Integrating Biological Intelligence with AI
15 Integrating Biological Intelligence with AI IN SILICO TOOLS TO BETTER MINE DIVERSE IMMUNE REPERTOIRES Deep Screening + Deep Sequencing Biological Intelligence Large-scale data collection Structure-Based Design Tools Proprietary Databases Deep Learning Models Multi-species databases
Slide 16: NKp46 Case Study
16 NKp46 Case Study: Discovering NK cell engager arm for bispecific antibody
Slide 17: Project Background
17 Project Background Target • NKp46 (NCR1, CD335) is a 46-kDa glycoprotein • No statistically significant downregulation of NKp46 on both NK and T cells has been observed in many cancers From PDB 6IAP Discover anti-NKp46 antibodies from OmniClic for bispecific antibody (NKCE)
Slide 18: OmniDeep Empowers Large-Scale Antibody Discovery
18 OmniDeep Empowers Large-Scale Antibody Discovery Biological Intelligence +
Slide 19: OmniClic® Screening Summary
19 OmniClic® Screening Summary Bird Screen Type # Cells Screened # Hits Antigen on beads 1.4 M 1200 1 Cells 3.2 M 203 Antigen on beads 1.4 M 1199 2 Cells 3.1 M 602 Antigen on beads 2.6 M 1326 3 Cells 1.3 M 699 Total 13 M 5229 • Processed with pooled NGS sequencing for 2130 unique sequences Synergy b
Slide 20: OmniClic® Repertoire Space
20 OmniClic® Repertoire Space Bead screen Cell screen
Slide 21: Bioinformatics-Aided Antibody Selection
21 Bioinformatics-Aided Antibody Selection Activity profile Diversity In Silico Developability Filter Profile 1: All clones Sequences Cell + Protein binder Method A Method B Count Profile 2: 3D homology All Cell binders models Hydrophobic patches near CDRs Profile 3: Lineages Cell binder only Struct
Slide 22: OmniClic® Repertoire Space
22 OmniClic® Repertoire Space Selected Bead screen Cell screen
Slide 23: Discovery of NKp46 Binders
23 Discovery of NKp46 Binders # Selected Clones Binding (%) <10 nM (%) 178 49 6% • Expressed clones with common light chain • 88 confirmed binders ‒ Average affinity ~100 nM Can we employ deep learning to increase yield and affinity?
Slide 24: Encoding Sequence Space with Deep Learning
24 Encoding Sequence Space with Deep Learning Variational Autoencoder (VAE) Model Encoded Antibody Space Antibody Sequence Principal Component 2 Encoder Affinity Prediction 8.3 Predicted Affinity Latent Space 7.9 7.4 7.0 unlabeled data 6.6 6.1 Principal Component 1 5.7 5.7 6.1 6.6 7.0 7.4 7.9 8.3 Af
Slide 25: Identifying Higher Affinity Antibody Sequences
25 Identifying Higher Affinity Antibody Sequences SELECTION FROM UNLABELED POOL OF DATA • Expected Improvement (EI) of the entire unlabeled data set can be calculated and sequences with highest values are selected Selection of Unlabeled Samples by Ab-VAE Encoding of Antibody Space Expected Improveme
Slide 26: VAE Highlight New Clusters to Prioritize
26 VAE Highlight New Clusters to Prioritize VAE Selected Seed Bead screen Cell screen
Slide 27: OmniDeep Successfully Selected High Affinity Clones
27 OmniDeep Successfully Selected High Affinity Clones Initial selection AI selection Re-run for direct comparison Bulk NGS Sorted Seed Seed clones used to select new sequences from bulk NGS and Initial xPloration sorts Seed Successfully found additional unique clones at 91% rate with ~10x improveme
Slide 28: New Insights from OmniDeep
28 New Insights from OmniDeep • Prioritize clones within standard lineage definitions • Found 70 pM clone (10x seed affinity) • Identifies new non-obvious clones in other lineages Deep learning provides new non-obvious insights for partners
Slide 29: OmniDeep Leverages Deep Learning
29 OmniDeep Leverages Deep Learning High-Quality in Silico Deep Learning Model New Suggested Hits Input Data Developability Filter Encoder Affinity xPloration hits Latent Space Assay data Decoder Variational Autoencoder (VAE) : Structure-based method: • Extends insights from Suggested antibodies • P
Slide 30: The OmniAb Technology Offering is Expanding
30 The OmniAb Technology Offering is Expanding TECHNOLOGY OFFERING ADDRESSES THE MOST CRITICAL CHALLENGES OF ANTIBODY DISCOVERY Create Screen Deliver Create Diverse Repertoires of Screen Millions of Cells to Find Further Characterize, Select and High-Quality Antibodies Potential Therapeutic Candidat
Slide 31: THANK YOU! Visit us at Booth #300
31 THANK YOU! Visit us at Booth #300 www.OmniAb.com