The development of new therapeutic proteins and biosimilars, including antibodies, requires a clear understanding of the relationship between their structure and function. In IgG molecules, glycosylation at Asn297 plays a key role in modulating effector functions, a fact increasingly emphasized in guidelines issued by the World Health Organization and regulatory agencies. Correlated glycan patterns, low variability, and the lack of well‑defined glycan profiles in process development and manufacturing samples significantly hinder the evaluation of individual glycan groups. Experimental approaches reported in the literature often rely on suboptimal strategies, where researchers vary one factor at a time and apply univariate data analysis. In this work, we present a systematic approach to understanding and predicting the impact of Fc glycan structures on the effector functions of IgG. We first optimized the preparation of orthogonal IgG samples using in‑vitro glycoengineering. We then characterized their glycan structures, binding affinities, and biological activity using various analytical techniques. Based on these data, we developed multiple linear regression models that provide quantitative evaluation and prediction of how specific glycan groups affect the binding of therapeutic IgG1 and IgG4 to Fcγ receptors and their biological activity. Our results also show that individual glycan isoforms can, in some cases, exert specific effects that differ from those of the overall glycan group, and should therefore be considered when assessing IgG functionality. With this work, we establish a systematic quantitative approach to understanding the multivariate impact of glycosylation on the effector functions of therapeutic monoclonal antibodies and offer a useful tool for more efficient and accelerated development of therapeutic proteins.
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