GenovacAI Humanization Powered by ENPICOM

GenovacAITM uses a next-generation generative deep learning algorithms to humanize antibodies with very high success rates. Combined with our high-throughput antibody production and characterization platforms, GenovacAI enables humanization of one-to-many candidate antibodies with significant savings in cost and time.

GenovacAI Powered By ENPICOM

GenovacAI is a cutting-edge, species agnostic generative deep learning algorithm for the next-generation humanization of antibodies. The algorithm generates humanized variants of parental antibodies with significantly greater success – defined by the variants’ humanness score and retention of binding affinity – than traditional methods, such as CDR grafting, and publicly available algorithms, such as BioPhi. While GenovacAI can be used to humanize a lead candidate antibody, the algorithm’s high success rate enables ‘humanization-forward’ engineering of many candidate antibodies immediately following a discovery campaign. Humanization-forward antibody engineering eliminates the need to repeat time-intensive and costly characterization and functional studies – a requirement if humanization is done post-selection of the lead candidate.

GenovacAI Humanization Project Scope and Deliverables

GenovacAI is a highly flexible tool that can be used to humanize one to many candidate antibodies. Additionally, the tool can be configured to generate any number of humanized variants per parental antibody and to define the desired level of humanness for each variant.

Deliverables for an GenovacAI humanization are customized for each project and include:

  • Electronic sequence
  • Small-scale, highly parallel production
  • Binding kinetics and epitope binning
  • Functional testing
  • Intermediate to large-scale production

Poster: Anti-RAGE Antibody Discovery and GenovacAI Humanization Case Study

Abstract: In this poster, we introduce GenovacAI, a cutting-edge, species agnostic service for next-generation humanization of antibodies, based on the novel AIGX generative deep learning model. Through a commercial project focused on the discovery and development of anti-RAGE antibodies, we show that GenovacAI generates humanized mouse and rat sequences with significantly greater success than using traditional methods, such as CDR grafting, and publicly available algorithms, such as BioPhi. GenovacAI’s capability to achieve superior results across species and to humanize of large numbers of candidate antibodies represents a significant advancement in antibody humanization, leading to lowered costs and a shortened timeline to IND filing.