Bringing In Silico Immunogenicity Prediction into the 21st Century with augmented intelligence


Many of the in-silico platforms used for immunogenicity risk assessment use algorithms and data which is over two decades old. Abzena have employed the latest technology in machine learning to develop a new in silico immunogenicity intelligence platform “iTope-AI” to help improve lead selection and safety assessment.

  • Reduce false negative / false positive rates using state-of-the-art Machine Learning risk assessment algorithms
  • Predicting peptide binding specificities across 46 major HLA-DR, DP and DQ isotypes
  • Filter out high risk clones or variants from a panel of biologics with higher confidence
  • Rank clones or variants with high sequence homology based on immunogenicity risk

Design deimmunised or humanised proteins with reduced risk of antigen presentation

Presenter
Anais Manin
Senior Director Bioassays
Abzena

Registration details:

Our registration process uses cookies, by submitting this registration form you agree to our cookie policy.

(*) denotes required form field(s)

Submit