Characterization and quantitation of bevacizumab in human blood serum through hyperspectral micro-Raman spectroscopy...

HPLC/MS and ELISA immunoassay are established techniques for identifying and quantifying monoclonal antibodies in biological fluids, offering high accuracy, precision, and low limits of detection (DL) and quantitation (QL). However, these methods are complex, destructive, costly and solvent-intensive. In contrast, vibrational techniques, such as Raman spectroscopy, provide non-destructive, environmentally friendly, and cost-effective analysis while maintaining analytical reliability. This study aimed to develop a hyperspectral micro-Raman approach for identifying and quantifying monoclonal antibodies in human blood serum with minimal achievable DL and QL.

Bevacizumab was selected as a model monoclonal antibody to evaluate the capability of micro-Raman mapping for discrimination from the blood serum matrix. Spectral acquisition conditions and imaging parameters, including mapping step size and number of spectra per map, were optimized to ensure robust identification. Quantification was achieved using classical least squares (CLS) fitting, exploiting both CLS scores and the surface area covered by the analyte within each map to construct calibration curves. The resulting models exhibited excellent linearity, with coefficients of determination (R²) between 0.98 and 0.99 over a concentration range of 0.01-1.25 ppm. The method achieved a DL of 0.17 ppm and a QL of 0.53 ppm for bevacizumab in human blood serum.

This work demonstrates that hyperspectral micro-Raman spectroscopy combined with chemometric analysis enables automated, and environmentally friendly quantification of monoclonal antibodies in complex biological matrices, achieving adequately low DL and QL.