reviewTrends in Pharmacological SciencesJan 18, 2023HYBRID OA

Computational and artificial intelligence-based methods for antibody development

University of Toronto

PubMed
Indexed incrossrefpubmed

Abstract

Due to their high target specificity and binding affinity, therapeutic antibodies are currently the largest class of biotherapeutics. The traditional largely empirical antibody development process is, while mature and robust, cumbersome and has significant limitations. Substantial recent advances in computational and artificial intelligence (AI) technologies are now starting to overcome many of these limitations and are increasingly integrated into development pipelines. Here, we provide an overview of AI methods relevant for antibody development, including databases, computational predictors of antibody properties and structure, and computational antibody design methods with an emphasis on machine learning…

Citation impact

174
total citations
FWCI
38.57
Percentile
100%
References
118
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Artificial intelligence
  • Complementarity (molecular biology)
  • Bispecific antibody
  • Antibody
  • Computational biology
  • Machine learning
  • Biology
No related works found for this paper.