Similarity assessment by multivariate statistics method based on the distance between biosimilar and originator

Area of Science:

• Biopharmaceutical Development
• Analytical Chemistry
• Biotechnology

Background:

• Biosimilar products, or follow-on biologics, offer lower-cost alternatives to originator biologics.
• Assessing the similarity of critical quality attributes, such as glycosylation patterns, is crucial for biosimilarity.
• Optimization of cell culture conditions is essential for producing biosimilar candidates with comparable characteristics.

Purpose of the Study:

• To propose a multivariate data analysis method for evaluating glycosylation pattern similarity between antibody candidates and a reference.
• To demonstrate the application of this method in optimizing cell culture conditions for biosimilar development.
• To identify specific media components that influence glycan similarity.

Main Methods:

• Utilized JMP software for multivariate data analysis.
• Developed a specific distance metric to quantify glycoform similarity.
• Conducted optimization experiments varying cell culture media components, including N-acetylglucosamine (GlcNAc).

Main Results:

• The proposed data analysis method successfully generated a distance metric indicating glycoform similarity.
• Increased concentration of GlcNAc in the basal media resulted in antibody glycans more similar to the reference.
• The method is applicable to assessing other physicochemical and functional similarities of follow-on biologics.

Conclusions:

• A robust data analysis approach can effectively assess biosimilar glycosylation similarity.
• N-acetylglucosamine (GlcNAc) supplementation is a viable strategy to enhance glycan similarity in antibody candidates.
• This methodology supports the design of experiments for optimizing cell culture and developing comparable biosimilars.