Reduction of monoclonal antibody viscosity using interpretable machine learning

Reduction of monoclonal antibody viscosity using interpretable machine learning

Early identification of antibody candidates with drug-like properties is essential for simplifying the development of safe and effective antibody therapeutics. For subcutaneous administration, it is important to identify candidates with low self-association to enable their formulation at high concen...

Full description

Saved in:
Bibliographic Details
Main Authors: Emily K. Makowski, Hsin-Ting Chen, Tiexin Wang, Lina Wu, Jie Huang, Marissa Mock, Patrick Underhill, Emma Pelegri-O’Day, Erick Maglalang, Dwight Winters, Peter M. Tessier
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:mAbs
Subjects:
Antibody engineering
charge
computation
developability
formulation
Fv
Online Access:https://www.tandfonline.com/doi/10.1080/19420862.2024.2303781
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items