Utilizing its proprietary DNA technology to write synthetic libraries, Twist Biopharma provides end-to-end antibody discovery and optimization solutions for the biotechnology industry. This solution includes:

1. a panel of highly diverse synthetic naïve antibody phage display libraries
2. several target class specific antibody phage display libraries against difficult-to-drug targets
3. a Twist Antibody Optimization (TAO) platform for antibody affinity and developability optimization
4. and a high-throughput antibody expression service. To highlight the power of this platform, our anti-SARS-CoV-2 antibody discovery and optimization efforts will be presented.

Educational Value of Attending:
With our unique DNA writing technology, Twist Biopharma is accelerating the way our partners discover and optimize antibody therapeutics. We have decades of synthetic antibody library design and selection expertise and have the ability to write any DNA sequence to enable faster, better discovery and development. Using our precise, rational, expertise in library fabrication, we can create libraries in a fundamentally different way that allow us to address tough targets, e.g. GPCRs. Since we are a DNA product company, we have considerable automation expertise that is utilized to drive the biopharma discovery workflow. This seminar will highlight how Twist Biopharma is fundamentally different from our competitors and how we can help you in your antibody discovery and optimization projects

Speakers:

Aaron K. Sato, Ph.D.,
Chief Scientific Officer, Biopharma
Twist Bioscience

Therapeutic antibodies do more than just recognize targets. In addition to biological activity, inherent biophysical properties are crucial to in vivo utility. The Specifica generation 3 platform is based on five sub-libraries created using well behaved clinical human antibodies as scaffolds. All CDRs, except HCDR3, are replaced by replicated natural CDRs found in the human repertoire, but purged of known sequence liabilities (e.g. aggregation-prone motifs, glycosylation motifs, etc.). The HCDR3s are generated by PCR from at least 1 billion B cells from 10 healthy donors. This platform generates diverse pools of high-affinity antibodies (pM and low nM) against clinically relevant targets with biophysical properties as good as, or better, than the original clinical antibodies used as scaffolds

Speakers:

Andrew Bradbury, M.D., Ph.D.
Chief Scientific Officer
Specifica

Traditional antibody discovery technologies have been used to develop all FDA approved antibody therapeutics currently in the clinic for diseases including autoimmune, inflammatory, infectious diseases and cancer. However, the next-generation of antibody therapies against more challenging targets, such as membrane-bound receptors, will require new technologies that can screen the broad B cell repertoire in depth.

Dr. Shireen Khan will present a case study of how ChemPartner has leveraged the Beacon system to rapidly discover cross-reactive antibodies against the GPI-anchored urokinase plasminogen activator (uPA) receptor. uPA and its receptor uPAR are associated with aggressive forms of cancer including metastatic breast cancer and pancreatic ductal adenocarcinomas. The upregulation of uPA in cancer was shown to correlate with poor clinical prognosis and supports targeting this pathway as a therapeutic approach for tumors in which uPA/uPAR are tumorigenic drivers. Identification of crossreactive antibodies to human, cyno and mouse uPAR proved to be challenging by panning a Fab phage display library against human uPAR. In collaboration with UCSF and SPII, ChemPartner leveraged the Berkeley Lights’ Beacon optofluidic system to screen deeper into the immune B cell repertoire. Single B cells were screened on the Beacon system using a novel multiplexed assay for human, mouse and cyno uPAR binders. Antibodies were identified that bound both human and cyno uPAR proteins and represented broad sequence diversity. After generating the antibodies through recombinant antibody expression and purification, several candidates were strong binders to human uPAR on endogenously expressing MDA-MB-231 breast cancer cells. Functional characterization of these antibodies in uPA/uPAR blocking, pERK signaling and invasion assays is underway.

Dina Sirypangno will share new capabilities developed at Berkeley Lights to enable better antibody lead candidate selection in under 1 week.

Speakers:

Shireen Khan
Sr. Director, Biologics
ChemPartner

Dina Sirypangno
Sr. Technical Sales Specialist
Berkeley Lights

N-linked glycosylation is a common post-translational modification found on many antibody based biotherapeutics, and has been linked to safety, stability and activity of the drug substance. It is therefore important that the modification can be monitored and controlled as required. A commonly employed method for characterizing glycosylation utilizes enzymatic removal of the glycans followed by labelling with fluorescent groups. The labelled glycans are then separated by hydrophilic interaction chromatography (HILIC) and detected / quantified by detection of the fluorescent group. The glycan identity can be predicted based on the elution time and supporting mass spectral data. Although sensitive, as glycans are cleaved from the entire protein, site-based information is lost. Hence, if the biotherapeutic has more than one potential site of glycosylation, then any information on glycan sub populations linked to different sites is not ascertained. With the increasing numbers of bi-specifics in development the number of molecules with more than one site of glycosylation is increasing. Methods like peptide mapping and middle-up mass spectrometry can give site specific relative levels of glycosylation, through sub-division of the protein.

In this presentation we will discuss the use of these approaches to give relative levels of different glycoforms, at specific sites, and compare to the enzymatic stripping and fluorescent labelling approach. As well as being a powerful approach for monitoring glycosylation during product characterization, they are promising candidates for automation to provide rapid, high-throughput analytical screening to drive decision making during process development

Speakers:

Michael Walker
Technical Expert
Intertek Pharmaceutical Services

Antibodies for immune checkpoint blockade have revolutionized cancer therapy but their use is oftentimes limited by toxicity, particularly when used in combination. The next generation of immunotherapies must address these toxicities to enable more potent combination therapies. Here, we describe a bispecific SNIPER™ antibody that selectively targets intratumoral regulatory T-cells (Treg), diminishing the immunosuppressive tumor microenvironment without the toxicity associated with systemic Treg depletion. In vitro functional characterization of the engineered human SNIPERs™ identified a lead candidate that selectively binds Tregs localized in human tumors over those in systemic circulation. In vivo studies using a mouse surrogate SNIPERTM in CT26 tumor models revealed a dramatic reduction in Tregs in the tumors, with no change in the periphery. In an early CT26 model, a strong majority of mice receiving single agent therapy showed complete response and recovery. Combinations with immune stimulating agents against more advanced tumors led to similar efficacy

Speaker:

Jonathan Davis, Ph.D. Head of Discovery
Invenra, Inc

• The molecular mechanism of SARS-CoV-2 spike protein-mediated virus entry into host cell
• The important role of SARS-CoV-2 spike protein in serological testing, vaccine and antibody therapeutics development for COVID-19.
• The 3-D structural studies of SARS-CoV-2 spike protein alone or in complex with antibodies
• The characterization of SARS-CoV-2 spike protein glycosylation sites
• The discoveries of mutations in RBD of SARS-CoV-2 spike protein and the implications for drug and vaccine design

Speaker:

Yinan Jiang, Ph.D.
Product Development Manager
ACROBiosystems Inc.

We have used multistep genome editing with CRISPR-Cas9 to develop functional screening platforms for the engineering of T cell receptors (TCRs) and chimeric antigen receptors (CARs). These have been deployed to optimize and tune affinity and signaling of therapeutic TCRs and CARs to increase target specificity and reduce cross-reactivity.

Speaker:

Sai Reddy, PhD
Associate Professor
ETH Zurich

Deep Learning is a class of machine learning that uses large sets of data to uncover underlying relationships and rules of a given system. We use an unsupervised deep learning approach to extract key features of human antibody sequence and apply them to the generation of our Humanoid Antibody Library™ (HAL™) - a diverse library of novel human monoclonal antibodies. This approach permits us to bias the library towards a variety of developable properties

Speakers:

Tileli Amimeur
Senior Data Scientist
Just-Evotec Biologics, USA