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The multi-attribute method (MAM) streamlines biotherapeutic protein characterization using LC-MS peptide mapping. This advanced technique enhances quality control and accelerates development by providing site-specific analysis of protein attributes.

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Area of Science:

  • Biopharmaceutical Analysis
  • Analytical Chemistry
  • Biotechnology

Background:

  • The multi-attribute method (MAM) is a liquid chromatography-mass spectrometry (LC-MS) based peptide mapping approach.
  • It offers a streamlined strategy for parallel monitoring of multiple attributes in a single analysis with high sensitivity and confidence.
  • MAM supports robust Quality by Design (QbD) approaches and faster decision cycles for biotherapeutic development.

Purpose of the Study:

  • To detail the multi-attribute method (MAM) for biotherapeutic protein characterization.
  • To outline the MAM workflow from sample digestion to data processing.
  • To highlight MAM's advantages over conventional analytical methods.

Main Methods:

  • Proteolytic digestion of the biotherapeutic protein.
  • Reversed-phase liquid chromatography coupled with high-resolution accurate mass spectrometry (LC-HRAM MS) for peptide separation and detection.
  • Two-phase data acquisition: Phase I (discovery) using data-dependent acquisition (DDA) MS/MS for peak identification and peptide workbook development, and Phase II (monitoring) using full MS acquisition for predefined product quality attribute monitoring.

Main Results:

  • MAM enables direct assessment of protein sequence and product quality attributes with site specificity.
  • The method allows for confident identification of peaks and development of a peptide workbook in Phase I.
  • Phase II facilitates targeted monitoring of predefined product attributes and new peak detection (NPD) through comparative analysis with a reference standard.

Conclusions:

  • MAM provides a sensitive, confident, and streamlined approach for biotherapeutic protein characterization.
  • It replaces conventional analytical methods by enabling parallel monitoring of multiple attributes in a single LC-MS analysis.
  • MAM supports robust QbD strategies and accelerates biotherapeutic development timelines.