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Observation of Small Cluster Formation in Concentrated Monoclonal Antibody Solutions and Its Implications to Solution Viscosity

Published

Author(s)

Eric J. Yearley, Paul D. Godfrin, Tatiana NMN Perevozchikova, Hailiang Zhang, Peter Falus, Lionel Porcar, Michihiro Nagao, Joseph E. Curtis, Pradad Gawande, Rosalynn Taing, Isidro E. Zarraga, Norman J. Wagner, Yun Liu

Abstract

Monoclonal antibodies (mAbs) are a major class of biopharmaceuticals. Some concentrated mAb solutions are hypothesized to exhibit the formation of a solution phase consisting of reversibly self-associated aggregates (or reversible clusters), which is speculated to be responsible for their distinct solution properties. Here we report the observation of reversible clusters in concentrated solutions of mAbs directly using neutron spin echo (NSE). Using two different mAbs, we show how seemingly minor changes in the primary protein sequence can manifest as a significant increase in the clustering behavior at high concentrations. The mAb cluster size and solution morphology are determined by combining NSE, small angle neutron/x-ray scattering and computer simulations. The cluster formation and the associated solution viscosity are shown to be controllable by adding electrolyte. These results conclusively connect the undesirable high viscosity of some mAb solutions with the formation of reversible clusters having extended open structures. These studies can aid in the development of mAbs with desired solution properties.
Citation
Biophysical Journal
Volume
106

Keywords

cluster, viscosity, neutron spin echo, small angle scattering, protein, monoclonal antibody

Citation

Yearley, E. , Godfrin, P. , Perevozchikova, T. , Zhang, H. , Falus, P. , Porcar, L. , Nagao, M. , Curtis, J. , Gawande, P. , Taing, R. , Zarraga, I. , Wagner, N. and Liu, Y. (2014), Observation of Small Cluster Formation in Concentrated Monoclonal Antibody Solutions and Its Implications to Solution Viscosity, Biophysical Journal, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=914769 (Accessed March 3, 2024)
Created April 14, 2014, Updated October 12, 2021