Summary of Generative Humanization For Therapeutic Antibodies, by Cade Gordon et al.
Generative Humanization for Therapeutic Antibodies
by Cade Gordon, Aniruddh Raghu, Peyton Greenside, Hunter Elliott
First submitted to arxiv on: 6 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Quantitative Methods (q-bio.QM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel conditional generative modeling approach is proposed to reframe the humanization process in antibody therapy development. The method leverages a language model trained on human antibody data to sample humanizing mutations that reduce immunogenicity risk while maintaining or improving therapeutic properties. This algorithm can be seamlessly integrated into an iterative optimization campaign. In silico and laboratory validations demonstrate the efficacy of this generative humanization method, yielding diverse sets of antibodies that are both highly human-like and exhibit favorable therapeutic attributes, such as improved binding to target antigens. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Antibodies are being used to treat many diseases, but making sure they’re safe for patients is a challenge. One way to make them safer is by “humanizing” them – making them more like the antibodies our bodies naturally produce. This can be done using a computer algorithm that predicts which parts of the antibody need to change. However, this process has limitations and often results in few humanized candidates with compromised properties. A new approach uses machine learning to generate human-like antibodies while maintaining their therapeutic benefits. This method produces diverse sets of antibodies that are both safe for patients and effective at targeting disease-causing antigens. |
Keywords
* Artificial intelligence * Language model * Machine learning * Optimization
