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Optimal Affinity of a Monoclonal Antibody: Guiding Principles Using Mechanistic Modeling

Authors :
Anup Zutshi
Pratap Singh
Anson K. Abraham
Abhinav Tiwari
John M. Harrold
Source :
The AAPS Journal. 19:510-519
Publication Year :
2016
Publisher :
Springer Science and Business Media LLC, 2016.

Abstract

Affinity optimization of monoclonal antibodies (mAbs) is essential for developing drug candidates with the highest likelihood of clinical success; however, a quantitative approach for setting affinity requirements is often lacking. In this study, we computationally analyzed the in vivo mAb-target binding kinetics to delineate general principles for defining optimal equilibrium dissociation constant (\( {K}_D^{opt} \)) of mAbs against soluble and membrane-bound targets. Our analysis shows that in general \( {K}_D^{opt} \) to achieve 90% coverage for a soluble target is one tenth of its baseline concentration (\( {K}_D^{opt}=0.1\times {S}_0 \)), and is independent of the dosing interval, target turnover rate or the presence of competing ligands. For membrane-bound internalizing targets, it is equal to the ratio of internalization rate of mAb-target complex and association rate constant (\( {K}_D^{opt}=\raisebox{1ex}{${k}_{elDM}$}\!\left/ \!\raisebox{-1ex}{${k}_{on}$}\right. \)). In cases where soluble and membrane-bound forms of the target co-exist, \( {K}_D^{opt} \) lies within a range determined by the internalization rate (\( {k}_{elDM} \)) of the mAb-membrane target complex and the ratio of baseline concentrations of soluble and membrane-bound forms (\( \raisebox{1ex}{${S}_0$}\!\left/ \!\raisebox{-1ex}{${M}_0$}\right. \)). Finally, to demonstrate practical application of these general rules, we collected target expression and turnover data to project \( {K}_D^{opt} \) for a number of marketed mAbs against soluble (TNFα, RANKL, and VEGF) and membrane-bound targets (CD20, EGFR, and HER2).

Details

ISSN :
15507416
Volume :
19
Database :
OpenAIRE
Journal :
The AAPS Journal
Accession number :
edsair.doi.dedup.....c61b2d466121ee6fae2deed7d6430b13