Analyzing Proteins with Mass Photometry and Size Exclusion Chromatography
App Note

Analyzing Proteins with Mass Photometry and Size Exclusion Chromatography

Considerations when comparing mass photometry and size exclusion chromatography data for protein quantification and antibody aggregation

Characterizing antibody aggregation and quantifying protein abundance is critical for ensuring the safety and efficacy of protein-based biopharmaceuticals, such as monoclonal antibodies. Given the complexity of these proteins, a combination of advanced analytical technologies is often required for a thorough analysis.  

Analyzing Proteins with Mass Photometry and Size Exclusion Chromatography

Mass photometry is a novel method that measures the true molecular mass of individual biomolecules by quantifying scattered light. This technique can rapidly analyze small sample volumes—as little as 10µL—at physiologically relevant concentrations under native conditions, making it an invaluable analysis tool for complex proteins. 

Size exclusion chromatography (SEC) is the gold standard for assessing nanometer-sized aggregates. However, SEC can be complicated by several factors, including column and mobile phase optimization. Integrating mass photometry with SEC offers a more comprehensive approach to sample characterization, combining the strengths of both techniques. 

Despite their complementary nature, the underlying detection principles of these two techniques are fundamentally different. Therefore, careful consideration is required when comparing data between them. The following technical note explores these considerations through two case studies, demonstrating the validity and utility of mass photometry as an orthogonal analytical technique. 

Elevate your protein analysis capabilities with our comprehensive technical note on mass photometry and size exclusion chromatography. Download now to discover: 

  • The fundamental principles behind mass photometry and SEC
  • How to accurately assess protein abundance and aggregation
  • Best practices for integrating mass photometry and SEC data 

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