Orion® Speeds Up Your Antibody Discovery with AbXtract™
Orion® Antibody Discovery Suite – AbXtract™ from Specifica
Next Generation Sequencing (NGS)-based antibody discovery is now available in the Orion® molecular-design platform. These capabilities are part of AbXtract™, which is the first module available in Orion's new Antibody Discovery Suite.** AbXtract was developed in partnership withSpecifica. Founded by Andrew Bradbury PhD, an innovator in novel antibody technologies, Specifica is a leader in antibody libraries design and discovery.
Compared to conventional colony screening methods, NGS screening with AbXtract helps teams:
Uncover more leads: Increase the number of clonotype leads five- to ten-fold compared to random colony screening
Increase sequence diversity and cluster representation: Explore the entire sequence diversity within selected populations, even rare clones that are typically missed by low-throughput methods that favor more abundant antibodies
Prioritize promising leads: Tie in known data, and even low-throughput assay data, to prioritize leads with the most favorable developability and biophysical profiles
Minimize costs: Achieve high throughput for a fraction of the cost of conventional assay runs
Equip the entire discovery team: Automated workflows for novice users, while allowing expert users to fully configure their settings
Use AbXtract™ in Orion® to identify antibodies within the same functional cluster that have reduced number of liabilities.
From Millions of Sequences to a Select Few
AbXtract has the cloud-based compute power to process tens of millions of sequences into meaningful information. Its sophisticated machine-learning algorithms and workflows help antibody engineers and bioinformaticians parse through this vast amount of data to characterize sequences and extract sequence- and functional-based features. Once promising leads are identified, visual models can further aid in decision-making.
Quickly subselect non-redundant antibody sequences belonging to the same cluster using the interactive plot.
User Friendly - Get Leads from Your Data in Three Guided Steps
Step 1: Upload and process sequence data (millions to 10s of millions of sequence files).
Upload sequence files into Orion
NGS: FASTQ, FASTA
Low-throughput: FASTA, FASTQ, EXCEL, TSV, CSV
Perform FASTQ quality filtering
Perform simple demultiplexing of highly multiplexed experiments
Annotate to identify CDRs and framework regions of interest (IMGT, Kabat, Chothia, or custom annotation)
Produce annotated records ideally suited for antibody discovery
Step 2: Consolidate sequences to group similar antibodies (1000s to 10,000s sequences).
Extract features
Avoid contaminants
Quantify population statistics
Maximize CDR diversity
Classify functionality
Obtain frequency of clones by population
Eliminate bad sequences (e.g., those seen before or with known biophysical liabilities)
Assess the scaffold distribution
Identify relationships between and within sequence clusters to avoid redundancy
Leverage known data for various sequence populations under different experimental conditions
Look at round-to-round enrichment to identify true binders and better-affinity binders
Couple in low-throughput screening-assay data for sequences with desired features
Identify overlap among different target populations
Step 3: Choose the most optimal candidates (10s to 1000s of sequences).
Identify best performers using NGS metrics derived from experimentally validated studies
Leverage prior knowledge to:
Maximize diversity
Reduce risk
Minimize redundancy
Optimize time to pre-clinical trials
Maximize the selection of leads with very distinct sequence-based properties
Perform unsupervised physicochemical clustering to identify clusters sharing similar binding modes
Easily select unexplored antibodies with likely distinct paratope space
Identify additional clones that share the same features as those characterized, such as:
Antibodies from the same cluster lacking specific sequence liabilities
Antibodies from the same cluster that span a broad affinity range
Quantify developmental liabilities from common and customized references
Perform region of interest (ROI)-based enrichment calculation across selection rounds / populations
Identify population overlap at deeper sequencing depth.
Identify the relative abundance of clones that bind distinct targets or variants
Identify NGS clones that map to already characterized populations
Additional Resources
Erasmus, MF, Fortunato, F., Leal-Lopes, C., D’Angelo, S., Teixeira, A., Spector, L., Perea, K., Soerensen, J., Dovner, M., A., Choudhary, A., Honnen, W., Calianese, D., Pinter, A., Bradbury, ARM. Diverse Panel of High Affinity SARS-CoV-2 Leads with Varying Specificity Derived from Long-Read Next-Generation Sequencing Pipeline. To Be Submitted (November, 2021).
Ferrara, F, Erasmus, M.F., D’Angelo, S., Leal-Lopes, C., Teixeira, A., Choudhary, A., Honnen, W., Calianese, D., Huang, D., Burton, D., Pinter, A., Bradbury, A.R.M. A pandemic-enabled comparison of antibody discovery platforms: a naïve library directly delivering antibodies as potent as immune sources. Nature Comm. In press (2021).
