Imaged capillary isoelectric focusing associated with multivariate analysis: A powerful tool for quality control of therapeutic monoclonal antibodies

Monoclonal antibodies are increasingly used in cancer therapy. To guarantee the quality of these mAbs from compounding to patient administration, characterization methods are required (e.g. identity). In a clinical setting, these methods must be fast and straightforward. For this reason, we investigated the potential of image capillary isoelectric focusing (icIEF) combined with Principal Component Analysis (PCA) and Partial least squares-discriminant analysis (PLS-DA). icIEF profiles obtained from monoclonals antibodies (mAbs) analysis have been pre-processed and the data submitted to principal component analysis (PCA). This pre-processing method has been designed to avoid the impact of concentration and formulation. Analysis of four commercialized mAbs (Infliximab, Nivolumab, Pertuzumab, and Adalimumab) by icIEF-PCA led to the formation of four clusters corresponding to each mAb. Partial least squares-discriminant analysis (PLS-DA) applied to these data allowed us to build models to predict which monoclonal antibody is analyzed. The validation of this model was obtained from k-fold cross-validation and prediction tests. The selectivity and the specificity of the model performance parameters were assessed by the excellent classification obtained. In conclusion, we established that the combination of icIEF and chemometric approaches is a reliable approach for unambiguously identifying compounded therapeutic monoclonal antibodies (mAbs) before patient administration.