High throughput cross-interaction measures for human IgG1 antibodies correlate with clearance rates in mice
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Wittrup_High throughput.pdf
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Author(s)
Sun, Tingwan
Jain, Tushar
Caffry, Isabelle
Yu, Yao
Lynaugh, Heather
Brown, Michael
Xu, Yingda
Kelly, Ryan Lewis
Vasquez, Maximiliano
Wittrup, Karl Dane
Date Issued
June 2015
Journal
mAbs
Publisher
Landes Bioscience
Citation
Kelly, Ryan L, Tingwan Sun, Tushar Jain, Isabelle Caffry, Yao Yu, Yuan Cao, Heather Lynaugh, et al. “High Throughput Cross-Interaction Measures for Human IgG1 Antibodies Correlate with Clearance Rates in Mice.” mAbs 7, no. 4 (May 27, 2015): 770–777.
Version
Final published version
Abstract
Although improvements in technology for the isolation of potential therapeutic antibodies have made the process increasingly predictable, the development of biologically active monoclonal antibodies (mAbs) into drugs can often be impeded by developability issues such as poor expression, solubility, and promiscuous cross-reactivity. Establishing early stage developability screening assays capable of predicting late stage behavior is therefore of high value to minimize development risks. Toward this goal, we selected a panel of 16 monoclonal antibodies (mAbs) representing different developability profiles, in terms of self- and cross-interaction propensity, and examined their downstream behavior from expression titer to accelerated stability and pharmacokinetics in mice. Clearance rates showed significant rank-order correlations to 2 cross-interaction related assays, with the closest correlation to a non-specificity assay on the surface of yeast. Additionally, 2 self-association assays correlated with each other but not to mouse clearance rate. This case study suggests that combining assays capable of high throughput screening of self- and cross-interaction early in the discovery stage could significantly lower downstream development risks.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Chemical Engineering
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1080/19420862.2015.1043503
