Predicting purification process fit of monoclonal antibodies using machine learning

Predicting purification process fit of monoclonal antibodies using machine learning

In early-stage development of therapeutic monoclonal antibodies, assessment of the viability and ease of their purification typically requires extensive experimentation. However, the work required for upstream protein expression and downstream purification development often conflicts with timeline p...

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Bibliographic Details
Main Authors: Andrew Maier, Minjeong Cha, Sean Burgess, Amy Wang, Carlos Cuellar, Soo Kim, Neeraja Sundar Rajan, Josephine Neyyan, Rituparna Sengupta, Kelly O’Connor, Nicole Ott, Ambrose Williams
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:mAbs
Subjects:
Antibody
biophysical
chromatography
computational
developability
machine learning
Online Access:https://www.tandfonline.com/doi/10.1080/19420862.2024.2439988
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https://www.tandfonline.com/doi/10.1080/19420862.2024.2439988

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