Controlling False Positives in Sequence Variant Analysis

Reduce false positives in sequence variant analysis with a simple, time-saving approach. Join Zachary Lee to learn how time-course digestion can streamline data analysis and improve accuracy. Register now to gain actionable insights.

Register Free: https://www.pharmtech.com/pt_w/false-positives

Event Overview:

• Sequence variant analysis is essential for characterizing biotherapeutic proteins, but high rates of false positives can slow development. In this webinar, Zachary Lee will reveal how low-level post-translational modifications introduced during protein digestion can be misidentified as sequence variants. You'll learn how implementing time-course digestion during method development can effectively distinguish true variants from artifacts, significantly reducing data analysis time. Key takeaways include understanding the role of sequence variant analysis, strategies for identifying and eliminating false positives, and practical guidance on integrating time-course digestion into your workflow.
  
  Key Learning Objectives:
• Understand the importance of sequence variant analysis during protein biotherapeutic development.
• Learn how true sequence variants are identified and distinguished from false positives.
• Demonstrate how time-course digestion enables rapid identification of false positives during method development.

Who Should Attend:

• Any individual involved in biopharmaceutical product analysis, development, manufacturing, and quality control.

Speaker:

Zachary Lee, PhD, has over 12 years of experience in protein analytics using liquid chromatography mass spectrometry. His focus is on protein characterization methodologies such as peptide mapping, intact mass, sequence variant, and host-cell protein analysis. His team has extensive experience in analyzing monoclonal antibodies and antibody-drug conjugates . Lee holds a PhD in biology from the Stowers Institute for Medical Research.

Register Free: https://www.pharmtech.com/pt_w/false-positives