Taking the individual bias out of examining comparability of biosimilars: A case study on monoclonal antibody therapeutics

Biosimilar manufacturers need to perform analytical and functional similarity assessments against the reference product. Successful demonstration allows for an abbreviated clinical path, thereby translating to affordable biosimilars. Current practices for regulatory concurrence on analytical similarity data are based on chart visualization and open to individual (human) bias. Here, we present a novel, chemometric approach for assessing biosimilarity that aims to simplify assessment and eliminate individual bias from decision making through application of weighted principal component analysis. Through the proposed approach, chemical information across the analytical characterization platform and drug products can be collated into a single plot for quantitative biosimilarity assessment. The proposed one-plot analysis offers a holistic visualization of 1) inter-product variability (w.r.t reference product) in cases where multiple batches per product have been investigated and 2) intra-product variability for each critical quality attribute (CQA) wherein information from orthogonal tools can be incorporated within the same plot. This allows for numerical grading of similarity for biosimilars of any given reference product. Although the proposed statistical approach is novel, it builds on standardized measures of CQA, criticality, and analytical procedures, thus making this approach easy to incorporate within the existing regulatory framework.