Discovery and prioritization of novel antibodies with advanced repertoire analysis and exposed liability predictions

In this session, we discuss how you can quickly identify developable and diverse antibody candidates using integrated Rep-Seq data analysis and high-throughput exposed liability predictions.

What will you learn?

The integration of high-throughput sequencing data in antibody screening accelerates and improves discovery of novel therapeutic antibodies. However, getting from millions of sequences to a diverse set of developable antibodies with the right therapeutic properties can be incredibly challenging, time-consuming, and requires significant software and computational resources. In this session, you will learn how to:

  • Perform advanced clustering and phylogenetic analysis through an intuitive user interface
  • De-risk antibody development by annotating structural liabilities for thousands of sequences at once
  • Speed up candidate selection by exploring multiple antibody characteristics in a single visualization

Speaker: Piotr van Rijssel 

Application Scientist at ENPICOM

As an Application Scientist he helps develop tailored workflows to help life scientists maximize their insights and accelerate the development of new immunotherapeutics and vaccines. Piotr focuses on providing technical consultations and ensuring the successful application of ENPICOM’s solutions to customers’ research.