FREE WEBINARS

 
Addressing LC Method Optimization - Scaling For Efficiency, Throughput And Reproducibility
Namrata Saxena
Speakers:

Namrata Saxena 
Technical Manager, Phenomenex

Namrata Saxena is the Technical Manager for the Asia-Pacific region at Phenomenex and is part of the global technical team, she provides expert support for a wide range of chromatographic challenges particularly in the characterization of biotherapeutics and emerging cell and gene therapy modalities. Her role includes delivering technical training, hosting seminars and webinars, and contributing to scientific content development. Prior to joining Phenomenex, Namrata worked as a Product Specialist at Bischoff Chromatography GmbH in Germany where she gained extensive experience in stationary phase chemistry, column manufacturing and method development domains.

One webinar, two viewing options
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Viewing Options
Session 1
Tuesday, September 1, 2026
Los Angeles: 10:00 AM PT | New York: 1:00 PM EST
Mexico City: 12:00 PM CDT

Session 2
Wednesday, September 2, 2026
London: 9:00 AM BST | Berlin: 10:00 AM CEST 
Mumbai: 1:30 PM IST
Overview
This webinar provides a foundational overview of LC method optimization. The session will focus on parameters that are significant for method optimization, including column dimensions, sample loading, particle morphologies, silica specifications, and stationary phase selectivities. Attendees will gain insight into how to use method development tools for scalability, throughput, and reproducibility for their LC methods.
Key Learning Points
  • Understand your column, from hardware design through stationary phase.
  • Learn how to choose the right particle morphology to match your analytical objectives.
  • Master sample load scaling for consistent, reliable results.
  • Apply LC method scaling parameters to maximize throughput while maintaining reproducibility.
Who Should Attend
Any scientists and professionals working with liquid chromatography who want to learn about LC method optimisation during scaling for high throughput and preparative applications.
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