A machine learning strategy for the identification of key in silico descriptors and prediction models for IgG monoclonal antibody developability properties

• Hauptverfasser: Andrew B. Waight (Verfasst von), David Prihoda (Verfasst von), Rojan Shrestha (Verfasst von), Kevin Metcalf (Verfasst von), Marc Bailly (Verfasst von), Marco Ancona (Verfasst von), Talal Widatalla (Verfasst von), Zachary Rollins (Verfasst von), Alan C Cheng (Verfasst von), Danny A. Bitton (Verfasst von), Laurence Fayadat-Dilman (Verfasst von)
• Format: Buch
• Veröffentlicht: Taylor & Francis Group, 2023-12-01T00:00:00Z.
• Schlagworte: article
• Online-Zugang: Connect to this object online.

ABSTRACTIdentification of favorable biophysical properties for protein therapeutics as part of developability assessment is a crucial part of the preclinical development process. Successful prediction of such properties and bioassay results from calculated in silico features has potential to reduce...