PEGS Europe 2024 Poster A070

In collaboration with JSR Life Sciences and the University of Lausanne

High-throughput sequencing has revolutionized antibody discovery methods like phage display, hybridoma, and single B cell sequencing. By integrating next generation nequencing (NGS) and bioinformatics, antibody candidate identification has become faster and more efficient. The application of artificial intelligence (AI) now plays a key role, enabling the analysis of larger sequence and structure spaces with deeper insights in less time.

In this poster, we apply in silico methods to phage display libraries, from discovery to optimization, using both public and internal single-chain variable fragment (scFv) libraries generated through multiple rounds of biopanning.

Download this poster to learn how:

• Leveraging sequence data allows for comprehensive characterization of phage libraries in an scFv format, while PLMs extract key features to identify potential binders or suggest modifications for antibody humanization.
  
  
• Structural information further enhances this process by enriching the diversity landscape and enabling clustering of antibodies into functional groups.
  
  
• Together, these in silico approaches work in powerful synergy to accelerate and enhance antibody discovery and development.

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