Conference dates: MAY 2-6, 2022
Location: Hynes Convention Center (Boston, MA)
Carterra Booth #1323
Title: Drug-like Antibodies and Other Binders Directly from Semi-synthetic Naive Libraries
Speaker: Andrew Bradbury, Chief Scientific Officer, Specifica, Inc.
Date: Tuesday, May 3, 2022
Time: 12:40 pm EST
Abstract: The Specifica Generation3 Library Platform is based on highly developable clinical scaffolds, into which natural CDRs purged of sequence liabilities have been embedded. The platform directly yields highly diverse, high affinity (20% subnanomolar), developable (>80% lack biophysical liabilities), drug-like antibodies as potent as those from immune sources. This talk will discuss the Generation3 concept and its application to antibodies and VHH scaffolds of clinical interest.
Title: A Cloud-Based Platform that Uses Unsupervised Machine Learning to Identify Hundreds of SARS-CoV-2 Antibodies with Optimal Properties
Speaker: M. Frank Erasmus, PhD, Head, Bioinformatics, Specifica, Inc.
Date: Thursday, May 5, 2022
Time: 3:50 pm EST
Abstract: Efficient exploration of sequence outputs from discovery campaigns is often hindered by inefficient sampling of the CDR diversity and technical hurdles involved with the handling of big data, particularly from multiplexed experiments. To overcome these limitations, we developed a cloud-based bioinformatics platform, AbXtract™, which utilizes population-based statistics and unsupervised clustering of next-generation sequencing (NGS) data to rapidly identify leads from distinct and/or overlapping populations. To validate the platform, we carried out a discovery campaign using our in vitro Generation 3 Antibody Library Platform to select antibodies against the SARS-CoV-2 Spike protein trimer and its RBD and S1 subunits. After demultiplexing the NGS datasets from antibody selections against different antigen populations at decreasing concentrations, we were able to effectively sort through the maze of sequencing data to identify and test many of these top candidates for kinetics, binning, and in vitro neutralization experiments. The correlation of these data with NGS metrics strengthened our ability to identify high quality leads directly from NGS datasets, with many predicted leads displaying favorable properties such as sub-nanomolar affinities (≥13pM), distinct binding profiles and potent neutralization (IC50’s <1ng/ml) of many SARS-CoV-2 variants of concern.
Title: Improving the screening, selection and deep characterization of biotherapeutic molecules using high-throughput SPR
Abstract: Throughput, speed, resolution, and sample consumption are inevitable challenges scientists face when screening biomolecule libraries and working to the goals of discovering and identifying the best lead candidates. Educated selection will often require multiple tests and orthogonal testing confirmation to determine the top candidate. Here we demonstrate how the Carterra LSA, which performs high-throughput surface plasmon resonance (HT-SPRTM) can rapidly generate high quality kinetic data from 384 candidates in parallel using a minimal amount of sample material. In addition, the LSA can perform epitope binning on up to 384 candidates per array to obtain unique epitope discrimination and characterization. The LSA is a high-throughput biology solution that enables scientists to characterize binding kinetics, affinity, and epitope specificity on large protein panels with minimal sample consumption, accelerating library-to-lead candidate selection and discovery.