Biologics developability data analysis using hierarchical clustering accelerates candidate lead selection, optimization, and preformulation screening

Biologics developability data analysis using hierarchical clustering accelerates candidate lead selection, optimization, and preformulation screening

Identification of an optimal single protein sequence at the discovery stage for preclinical and clinical development is critical to the rapid development and overall success of a biologic drug. High throughput developability assessments at the discovery stage are used to rank potent molecules by the...

Full description

Saved in:
Bibliographic Details
Main Authors: Kevin James Metcalf, Galen Wo, Jan Paulo Zaragoza, Fahimeh Raoufi, Jeanne Baker, Daoyang Chen, Mehabaw Derebe, Jason Hogan, Amy Hsu, Esther Kofman, David Leigh, Mandy Li, Dan Malashock, Cate Mann, Soha Motlagh, Jihea Park, Karthik Sathiyamoorthy, Madhura Shidhore, Yinyan Tang, Kevin Teng, Katharine Williams, Andrew Waight, Sultan Yilmaz, Fan Zhang, Huimin Zhong, Laurence Fayadat-Dilman, Marc Bailly
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:mAbs
Subjects:
Antibody discovery
antibody screening
biologics
biophysical properties
CMC
data-driven decision making
Online Access:https://www.tandfonline.com/doi/10.1080/19420862.2025.2502127
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items