Recent work has revealed critical vulnerable antibody targets that interrupt malaria and HIV-1 transmission. We performed efficient antibody engineering by screening all possible single amino acid substitutions throughout the antibody variable region, enabling exquisite anti-malarial protective potency. Using the same strategy, we engineered the most broadly-neutralizing antibody reported against the HIV-1 fusion peptide. This presentation will share these unpublished molecular studies and outline effective strategies for precision drug discovery.

Peptides are a highly promising class of therapeutics; however, their full potential has not yet been realized due to their poor cell permeability and limited oral bioavailability. mRNA-display is a powerful high-throughput in vitro screening technology in which peptide drug candidates are screened against a target of interest. The work described herein demonstrates the utility of in vitro approaches that interrogate peptide permeability, with the goal of integrating these tools into mRNA display. The integration of these approaches into mRNA-display has the potential to facilitate the development of peptides that exhibit activity against their target as well as membrane permeability.

Antibody repertoire sequencing has enabled us to access unprecedented amounts of antibody sequences. Here we will demonstrate our approach to comprehensive screening of antibody repertoires and in silico development of potent antibody leads.

The most clinically advanced COVID-19 vaccines use the full SARS-CoV-2 spike (S1 + S2) as immunogen. Molecular proteomics of plasma IgG (Ig-Seq) indicates that S2-targeting antibodies typically comprise the most abundant antibody lineages in circulation and that S2-targeting antibodies arise predominantly from pre-existing cross-ß-coronavirus lineages. These Ig-Seq observations, and others, are being harnessed in the development of a new pan-ß-coronavirus vaccine based on S2-only antigens.

GPCRs and ion channels are highly sought-after drug targets, but only two antibody drugs targeting them have been approved. AbCellera tackles the biggest challenges limiting antibody discovery for transmembrane proteins: producing antigens, driving antibody responses, and finding hits. Optimized immunization strategies, single-cell screening, and hyper-scale data science leads to hundreds of hits, and by integrating Tetrahymena — a natural membrane protein factory — we’re driving powerful solutions to unlock these targets.

This neoantigen recognition mechanism is one of the pillars of the immunological surveillance of tumor cells for cancer therapies. By leveraging the enriched immunopeptidomics dataset, we developed deep learning based models to characterize the peptide-MHC interaction and predict the antigen presentation and immunogenicity. The ranking of the neoantigens from patients could pave the way for the development of personalized cancer immunology therapies.

Epitope-specific binders can potentially be created by computational protein design strategies. By leveraging the unique properties of neural networks, we developed a generative model for immunoglobulin structures, with which diverse structures can be modeled with unprecedented speed. A design pipeline incorporating this neural network model can achieve flexible backbone protein-protein interface design. We will discuss this novel protein docking/design strategy and its potential application in creating epitope-specific novel immunoglobulin binders.

Poor brain delivery is a major hurdle in the development of biological therapeutics for neurologic diseases because of poor Blood-Brain Barrier penetration. Numerous BBB shuttles based on single-domain VNAR antibodies were developed by Ossianix. These include TXP1 which was demonstrated to penetrate the brain with high efficiency when inject at low therapeutic dose in non-human primates with an over 30-fold increase in comparison to the control.

We will describe Conformation Locking Antibodies for Molecular Probe discovery (CLAMPs) to distinguish and induce rare protein conformational states. We discover novel KRAS CLAMPs that recognize and induce a rare KRAS conformation. These CLAMPs enable new biology insights through visualization of inhibitor-bound KRAS in cells and tumors, a high-throughput screen to discover small molecule ligands, and structure-based characterization to provide a new framework for drug discovery against dynamic proteins.

The Specifica Generation 3 Library Platform is based on highly developable clinical scaffolds, into which natural CDRs purged of sequence liabilities have been embedded. The platform uses phage+yeast display to directly yield highly diverse (100-1000 clusters differing by Levenshtein distance 30-40), high affinity (20% subnanomolar), extremely developable (>80% lack biophysical liabilities), drug-like antibodies, which in a recent Covid campaign were as potent as antibodies from immune sources.

The COVID-19 pandemic has provided an unprecedented incentive for researchers to devise strategies for rapid target discovery and development of therapeutics and vaccines. The net effect has been breathtaking speed of discovery and product creation that may forever change how infectious diseases targets are identified and therapies developed. This presentation will provide an overview of discovery and product development platform approaches that could set the tone for the future development of infectious disease therapies. Case studies will be presented on viral and bacterial targets.

Near the start of the pandemic in 2020 caused by Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), AbCellera and Eli Lilly & Co. partnered to discover and develop antibodies capable of neutralizing infection by SARS-CoV-2. From this partnership, Ly-CoV555, also known as bamlanivimab, was rapidly identified from a blood sample of one of the first convalescent patients located in the US. Bamlanivimab became the first SARS-CoV-2 targeted antibody to enter US clinical trials, and receive Emergency Use Authorization, just three months after discovery. The rapid discovery and progression of bamlanivimab into clinical evaluation will be described.

In my talk, I will describe Autonomous Hypermutation yEast surfAce Display (AHEAD), a synthetic recombinant antibody generation technology that imitates somatic hypermutation inside engineered yeast. By encoding antibody fragments on an error-prone orthogonal DNA replication system, surface-displayed antibody repertoires continuously mutate through simple cycles of yeast culturing and enrichment for antigen binding to produce high-affinity clones in as little as 2 weeks. AHEAD was applied to generate a diverse set of potent nanobodies that target different epitopes on the surface of the SARS-CoV-2 S glycoprotein, a GPCR, and other targets, offering a template for streamlined antibody generation at large.

The NRC was mandated by the Government of Canada to establish the new Biologics Manufacturing Centre in Montréal to help support Canada’s biomanufacturing vaccine production capacity and pandemic readiness in response to the COVID-19 pandemic and in the future. A team of industry professionals and subject matter experts was assembled to design and build a facility within one year that would normally take 2 to 3 years in normal circumstances.

Specific requirements have to be met for the discovery of antibodies with challenging Target Product Profiles (TPPs). AbCheck has developed a technology to efficiently meet these requirements;  e.g., functional antibodies or antibodies against targets with high homology. Our novel, tailored microfluidics technology is based on high throughput functional sorting of immune plasma cell repertoires at single cell level.

The integration of high-throughput sequencing data in antibody screening accelerates and improves the discovery of novel therapeutic antibodies. However, getting from millions of sequences to a diverse set of developable antibodies with the right therapeutic properties can be incredibly challenging, time-consuming, and requires significant software and computational resources. In this session, we will discuss how you can predict exposed liability for thousands of antibodies to accelerate and de-risk your candidate selection.