PEGS Boston

Date: 01 - 05 May 2017 Location: Seaport World Trade Center City: Boston, MA Country: USA Visit the event website for more information Booth 317

 We have a speaker and a poster presentation at PEGS 2017.

 

 

 

Luncheon Presentation:

Yvette Stallwood 

Yvette Stallwood, Ph.D.

Head Applied Protein Services

 

Monday, May 1, 12:50 pm

 

Title:  Predicting, Avoiding and Mitigating Risk of Failure when Developing Biotherapeutics

 

Abstract:  In silico methods can be used to evaluate protein sequence and structure to assess the likelihood of immunogenic responses and potential critical quality attributes.  Ex vivo T- and B-cell responses enable the assessment of overall immunogenicity risks and to identify processed and presented epitopes.  This presentation will discuss how such methodologies are employed to perform a manufacturability and immunogenicity risk assessment in order to highlight potential risks of failure early in the development of biotherapeutics.

 

Poster Presentation:

 

Title:  Computational Approaches for Prediction of Developability Properties of Biotherapeutics and Risk Mitigation

 

Authors:  Olga Obrezanova, Andreas Arnell, Ramon Gomez de la Cuesta, James Herron, Noel Smith, and Yvette Stallwood

 

Abstract:  The ability to assess and de-risk the developability of a therapeutic candidate as early as possible in the development can be a very powerful tool to enhance the probability of success during manufacturing and clinical trials. 

    Here we demonstrate how a number of in silico and in vitro methodologies can be employed in an early developability assessment to aid selection of leads with improved manufacturability and safety profiles and to highlight potential risks of failure including aggregation, immunogenicity, lack of chemical stability and low productivity.

    Computational algorithms for the prediction and re-engineering of aggregation and immunogenicity will be described.  Sentinel APART™, a platform for antibody prediction and re-engineering, provides high-throughput, fully automated screening for aggregation risk combined with identification of aggregation hotspots and re-engineering.  The Epibase™ immunogenicity prediction platform combines the prediction of HLA-peptide binding with criteria such as similarity of peptides to "self" proteins on the level of exact matching and T-cell receptor (TCR) facing residues and population frequencies of global HLA types.  In silico predictions can be combined with in vitro risk assessments.

Bg