Multi-attribute quality screening of immunoglobulin G using polarized Excitation Emission Matrix spectroscopy.

Anal Chim Acta

Nanoscale BioPhotonics Laboratory, School of Chemistry, National University of Ireland, Galway, Galway, H91 CF50, Ireland. Electronic address:

Published: March 2020

Immunoglobulin G (IgG) is often used as a starting material for the production of functionalised antibodies, like Antibody Drug Conjugates (ADCs), PEGlyated-conjugates, or radioimmunoconjugates. The gross structural quality of the protein starting material is, therefore, an important factor in determining final product composition, purity, and quality. In terms of structural quality, one needs to know both the aggregation content and the tertiary structure of the protein. The measurement of structural quality in solution can thus be difficult, but the use of intrinsic fluorescence measurements might offer a solution because of its high sensitivity, ease of use, and when implemented in via multi-dimensional techniques like polarized Excitation Emission Matrix (pEEM) spectroscopy, its high information content. Here we demonstrate how pEEM measurements can be used as a multi-attribute screening method for protein quality using a polyclonal rabbit immunoglobulin (rIgG) model system. By using both Rayleigh scatter and fluorescence emission in combination with simple chemometric data analysis methods like Principal Component analysis (PCA) and unfolded partial least squares (U-PLS) one can simultaneously measure protein concentration, structural variance, and particle/aggregate composition. Furthermore, one can generate quantitative prediction models for non-reversible aggregation content as described by size exclusion chromatography (SEC) and obtain qualitative information about reversible aggregate content, which cannot be obtained from SEC measurements. In conclusion, the pEEM measurement approach is a potentially useful Process Analytical Technology (PAT) method for downstream processing operations in biopharmaceutical manufacturing.

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http://dx.doi.org/10.1016/j.aca.2019.12.020DOI Listing

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