De-risking antibody development by predicting exposed liabilities using
high-throughput structural modeling

NGS technologies provide an unparalleled level of sequencing depth that allows for the identification of millions of receptor sequences in a single experiment. Discover how high-throughput structural modeling can save valuable discovery time and help de-risk the path to diverse, developable antibodies.

What will you learn?

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, we will break down how you can:

  • Easily perform clustering, phylogeny, and exposed liability analyses in a secure, scalable environment
  • Accelerate antibody selection by exploring multiple characteristics from sequence, assay, and in silico predicted data
  • Leverage exposed liability predictions and developability profiles to de-risk candidate selection

Speaker: Piotr van Rijssel

Application Scientist

Piotr van Rijssel is an Application Scientist at ENPICOM where 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.