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Automating MS-Based Biotherapeutic Characterization Workflows for Developability Assessment

Gaining a comprehensive overview of biopharmaceutical candidates’ molecular characteristics for developability assessments typically requires collation of data obtained using multiple instruments and software platforms across several labs. Processing these large and often disparate data sets can create data processing bottlenecks due to the laborious, time-intensive, and error-prone nature of manual data management.

Discover how scientists at Novartis are leveraging automated MS data workflows to:

  • Improve productivity by reducing analysis time from days to hours
  • Harmonize data analysis to enable meaningful comparison of results
  • Eliminate error-prone manual data management
  • Facilitate collaboration through an integrated MS data processing platform

Learning Objectives

  • Gain insights into the logistical and analytical challenges presented by emerging biotherapeutic modalities
  • Learn how mass spectrometry and automation can address these and other key biopharma industry challenges
  • Explore how fully automated MS-based protein analysis supports next-generation biotherapeutic development

Who Should Watch

Biopharma analytical scientists and managers who are looking to automate mass spectrometry-based analytical workflows for characterization and quality monitoring of biotherapeutics.


  • Christian Hug, M.Sc., Senior Scientist, Novartis AG
  • Jonathan Jones, Ph.D., Business Development, Genedata

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