Summary

This article outlines Byos' role in biosimilar development, with a focus on its reporting tool's visualization features. Key points include:

• Reporting Capabilities: The software offers charts and tables that facilitate biosimilar comparability studies, helping to identify which candidate closely resembles the originator.
• Integration with External Tools: While Byos allows detailed analysis of individual attributes, tools like GraphPad Prism can enhance the visualization by creating dendrograms that integrate multiple critical attributes.
  
  
• GraphPad Prism Integration: GraphPad Prism supports hierarchical clustering, enabling the consolidation of critical attributes—such as glycosylation profiles, afucosylation levels, and PTMs—into a single, clear plot that distinguishes between originator and biosimilar batches.

 

 

 

Introduction

Biosimilars are biologic products that are highly similar to approved reference biologics, with no clinically meaningful differences in safety, purity, or efficacy. These complex molecules are produced in living systems, leading to inherent variability that distinguishes them from generic small-molecule drugs. Developing biosimilars involves extensive structural and functional characterization, followed by comparative clinical studies to confirm biosimilarity. Regulatory agencies like the FDA and EMA have established rigorous approval processes, focusing on demonstrating high similarity to the reference product rather than conducting independent efficacy and safety studies. Biosimilars offer potential benefits such as increased treatment options, improved patient access, and reduced healthcare costs[1].

Role of Mass Spectrometry in Biosimilar Analysis

Mass spectrometry (MS) is pivotal in the development, characterization, and quality control of biosimilars. Below are key MS applications:

1. Characterization of Primary Structure
   • Protein Sequence: MS confirms the amino acid sequence of the biosimilar, ensuring it matches the reference product. This involves peptide mapping, where the protein is enzymatically digested, and the resulting peptides are analyzed. Sequence variants, even in low abundance, can be detected.
   • Post-Translational Modifications (PTMs): MS is essential for identifying and quantifying PTMs, such as glycosylation, phosphorylation, methylation, and oxidation. PTMs can significantly impact the biosimilar's function and immunogenicity, and therefore must closely resemble those of the reference product.
2. Assessment of Higher-Order Structure
   • Though primarily used for primary structure, MS also aids in analyzing higher-order structures through techniques like hydrogen-deuterium exchange (HDX-MS) and cross-linking studies. These approaches help assess the biosimilar’s folding and conformation to ensure biological activity comparable to the reference product. Disulphide mapping, involving non-reduced peptide mapping, is also commonly used to identify expected and shuffled disulphide species.
3. Peak Identification
   • While biophysical methods like size-exclusion chromatography and capillary electrophoresis quantify molecular weight variants and fragments, they don’t identify these species. MS is preferred for identifying new peaks or variations in amplitude when compared to the originator’s profile.
4. Comparability Studies
   • Extensive comparability studies are conducted to demonstrate that the biosimilar closely resembles the reference product. MS provides molecular-level data to support these claims by comparing critical quality attributes, such as intact mass, peptide mapping, and glycosylation patterns.

Analysis of Biosimilars with Byos

Byos provides a comprehensive solution for all the above MS applications, streamlining the analysis and comparison of biosimilars across various structural and functional attributes. Some workflows include:

 

 

In this article, we focus on a subset of these applications, particularly glycosylation profiling and PTM analysis. The data presented below is based on a study published by Pisupati et al., 2017 [2]. In this study, four different batches of Remicade (Originator) and Remsima (Biosimilar) were analyzed. Detailed descriptions of sample preparation and data acquisition can be found in the original publication. In brief, all samples were digested with trypsin and analyzed with nano-LC-MSMS.

N-Glycan Profile

Glycosylation analysis can be performed in Byos either via glycopeptides generated from peptide mapping or with released glycan analysis. The data shown here originates from peptide mapping experiments. For detailed instructions on creating projects and inspecting data in Byos, refer to the following resources (Peptide Validation, Tutorial Video). Byos offers multiple visualization options, allowing direct comparison of differences between the originator and biosimilar. The data tables are enhanced with glycan cartoons and heat maps (Figure 1).

Figure 1. N-Glycan profile in table view.

Visualizations in Byos range from simple bar charts to more advanced PCA plot (Figure 2). PCA plots aggregate data, enabling direct comparison of multiple samples to determine which candidates most closely resemble the Originator.

 

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B

Figure 2. (A) Bar chart of the glycan profile. (B) PCA chart based on the glycan profile to detect clusters.

 

Fucosylation

Variations in afucosylated glycans have been shown to have a direct impact on bioactivity [2]. By grouping glycans containing fucose in a custom column, users can quickly assess differences in the data table or the bar chart (Figure 3).

The categorization of glycans whether being fucosylated or afucosylated is achieved by using the dynamic column function in the report. These dynamic custom column are created with JavaScript. To learn how you can create your own dynamic columns, please contact us.

 

A

B

Figure 3. Visualization of fucosylation levels with a table view (A) and a grouped bar chart (B).

 

Oxidation and Deamidation

Critical quality attributes such as oxidation and deamidation are also important. For a detailed guide on analyzing deamidation, refer to this resource. Pisupati et al [2] showed, oxidation and deamidation levels are remarkably similar (Figure 4).

Figure 4. Oxidation and Deamidation levels.

 

Hierarchical Clustering with GraphPad Prism

Ideally, all critical attributes should be consolidated into a single plot, providing a clear visualization of which candidate is closest to the originator. Since Version 10.3, GraphPad Prism supports hierarchical clustering, allowing users to visualize concatenated data from glycosylation profiles, afucosylation levels, and PTMs (such as oxidation and deamidation in the CDR region). The resulting dendrogram shows two main clusters: one for the originator batches and another for the biosimilar batches (Figure 5).

 

Figure 5. Dendogram used to cluster the analyzed samples based on their glycan profile, afucosylation levels, and oxidation and deamidation levels.

Conclusion

• This article provides a snapshot of Byos' capabilities in supporting biosimilar development, with a focus on its visualization features and reporting tools.
• The Byos report includes a variety of charts and tables that aid biosimilar comparability studies, helping to identify candidates most similar to the originator.
• While Byos enables detailed analysis of individual attributes, external tools like GraphPad Prism can enhance the analysis by creating dendrograms that aggregate multiple attributes, streamlining the assessment of large numbers of candidates to identify those closest to the originator.

References

[1] Castel, J.; Delaux, S.; Hernandez-Alba, O.; Cianférani, S. Recent Advances in Structural Mass Spectrometry Methods in the Context of Biosimilarity Assessment: From Sequence Heterogeneities to Higher Order Structures. Journal of Pharmaceutical and Biomedical Analysis 2023, 236, 115696. https://doi.org/10.1016/j.jpba.2023.115696.

[2] Pisupati, K.; Tian, Y.; Okbazghi, S.; Benet, A.; Ackermann, R.; Ford, M.; Saveliev, S.; Hosfield, C. M.; Urh, M.; Carlson, E.; Becker, C.; Tolbert, T. J.; Schwendeman, S. P.; Ruotolo, B. T.; Schwendeman, A. A Multidimensional Analytical Comparison of Remicade and the Biosimilar Remsima. Anal. Chem. 2017, 89 (9), 4838–4846. https://doi.org/10.1021/acs.analchem.6b04436.