It is important that clinical drug candidates not only have appropriate affinity and target specificity, but also have optimal biophysical properties. Using nuclease-directed integration, we have constructed large mammalian display libraries integrating tens of millions of antibody genes at a single genomic locus. The system not only allows selection for binding properties, but is also sensitive to biophysical characteristics, enabling detection and avoidance of problematic antibodies during the initial discovery phase.

• NEW DATA - This Presentation Contains New Data​

Over the past 4 years, DistributedBio's discovery platforms have delivered truly CDRH3 unique binders in over 80 campaigns. Our libraries display unparalleled paratope diversity on fully human germline scaffolds reliably yielding diverse sets of 50+ unique, drug-ready candidates even against difficult targets like ion channels, ultra-specific pMHC complexes, and GPCRs. Here we present findings from our past programs and how they sparked our latest invention: The Cosmic Antibody Library – 100 billion computationally optimized, fully human antibodies now offered with guaranteed molecular exclusivity.

Here I will describe our efforts to isolate antibody fragments from recombinant libraries using phage display combined with next-generation sequencing for screening output clones.

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Screening and deep sequencing of large mutagenesis libraries of antibodies and proteins provides training data that can be used to construct machine learning models. Here I will present our work in this field and how we apply it for the in silico screening and engineering of proteins with improved properties.

During this talk I will highlight the potential of Icosagen's proprietary technology platforms in developing highly potent SARS-CoV-2 neutralizing antibodies. Although neutralizing antibodies against SARS-CoV-2 demonstrate efficacy in reducing the development of severe Covid-19, the cumbersome intravenous administration of antibodies limits the effective use of such therapies. Here we demonstrate the potential use of inhalation based delivery of SARS-CoV-2 neutralizing antibodies for generating rapid passive immunity.

Utilizing its proprietary DNA technology to write synthetic libraries, Twist Biopharma provides end-to-end antibody discovery libraries including both (1) highly diverse synthetic naïve antibody phage display libraries and (2) target class-specific antibody phage display libraries against difficult-to-drug targets.  In this talk, Aaron Sato, CSO, will present several POC data on each member of their Library of Libraries. 

This presentation will outline our in vivo phage display selections and rabbit-derived single-domain antibody platform as a promising strategy to develop highly specific and potent therapeutic antibodies against challenging targets and unmet diseases.

Identifying the epitope of an antibody is a key step in understanding its function and its potential as a therapeutic. It is well-established in the literature that sequence-based clonal clustering can identify antibodies with similar epitope complementarity. There is growing evidence that antibodies from markedly different lineages but with similar structures can engage the same epitope with near-identical binding modes. I will describe a novel computational method for epitope profiling based on structural modelling and clustering, and show how it can identify sequence-dissimilar antibodies that engage the same epitope. Our approach functionally links antibodies with distinct genetic lineages, species origins, and coronavirus specificities. This indicates greater convergence exists in the immune responses to coronaviruses than would be suggested by sequence-based approaches.

• NEW TALK - This Presentation Will be Given for the First Time

We will show that machine learning can improve target specificity by the modular composition of models from different experimental campaigns, enabling a new integrative approach to improving target specificity. Our results suggest a new path for the discovery of therapeutic molecules by demonstrating that predictive and differentiable models of antibody binding can be learned from high-throughput experimental data without the need for target structural data.

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Agonist antibodies targeting CD137 are not clinically successful due to severe systemic toxicity. We generated and optimized STA551, a novel ATP-dependent anti-CD137 antibody using a phage-displayed synthetic human Fab library with a built-in ATP-binding motif. STA551 is agonistic only around extracellular ATP, which is elevated in tumor microenvironment. STA551 demonstrated potent anti-tumor efficacy without activating T cells in normal tissues in mice. STA551 is in a Phase 1 clinical trial.

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Activating NK cell receptors represent promising target structures to elicit potent anti-tumor immune responses. We have generated efficient NK cell engagers that bridge activating receptor NKp30 on NK cells with EGFR on tumor cells in several multifunctional IgG-like bispecific formats. In this talk I will present different strategies for the generation of NKp30 targeting molecules either by optimizing the natural ligand or by isolating NKp30-specific antibody derivatives.

•    NEW DATA - This Presentation Contains New Data