Modeling of the Biological Activity of Monoclonal Antibodies Based on the Glycosylation Profile

Abstract

The influence of the glycosylation profile of IgG on biological activity is known, but it is not clear which glycoforms have the highest impact on the main mechanism of action. The aim of this study was to design a mathematical model for predicting the antibody-dependent cellular cytotoxicity (ADCC) activity and the Fc gamma IIIa receptors' (FcɣRIIIa) relative binding of rituximab drug products based on their glycosylation profile. An additional goal was to identify the glycoforms that have the greatest impact on these mechanisms of action. For these purposes, the glycosylation profile was examined by hydrophilic interaction ultra-performance liquid chromatography (HILIC-UPLC), ADCC was assessed using a Promega kit, and FcɣRIIIa's binding affinity was assessed by surface plasmon resonance (SPR) analysis of a group of >50 rituximab drug products. Based on the results, mathematical models for the ADCC and FcɣRIIIa binding affinity prediction were designed using JMP 13.2.0. The quality of the model and the influence of sample size and heterogeneity on the reliability were verified. The results allow for the evaluation of rituximab drug products' activity based on their glycosylation profile and show that with a sufficiently large and differentiated dataset, it is possible to generate models for different monoclonal antibodies.

Keywords: Antibody(s); Bioanalysis; Biosimilar(s); Biotechnology; Glycoprotein(s); Glycosylation; HPLC; IgG antibody(s); Mathematical model(s); Surface plasmon resonance (SPR) spectroscopy.