Computational and artificial intelligence-based methods for antibody development
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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
5Topics & keywords
Topics
Keywords
- Computer science
- Artificial intelligence
- Complementarity (molecular biology)
- Bispecific antibody
- Antibody
- Computational biology
- Machine learning
- Biology
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