Getting More from Chromatography Data: From Summary Metrics to the Full Chromatogram

Tuesday, November 3, 2026
6am PST | 9am EST | 2pm GMT | 3pm CET

Method development can generate a large amount of data, from full chromatograms and calculated responses such as tailing factor, capacity factor, and resolution to the experimental settings behind them. Understanding how these factors interact and influence chromatographic performance can quickly become complex, particularly when modelling adds further formulas, tables, and statistical measures.

In this webinar, we explore practical ways to use modelling to better understand chromatography development experiments. We begin with familiar response-based approaches and progress to methods that use the complete chromatographic profile. We also look at how operating regions can be defined, as outlined by regulatory guidelines, to assess method robustness and support Quality by Design (QbD) approaches.

Topics include:

• Modelling familiar chromatographic responses such as resolution, tailing factor, and capacity factor, as well as determining which experimental factors have the greatest effect on performance
• Balancing experimental settings to achieve the desired combination of response characteristics and assessing method robustness in line with Quality by Design and regulatory guidelines
• Analyzing the complete chromatogram as a functional response and examining how experimental factors affect the shape and features of the chromatographic profile
• Using chromatographic or spectral profiles as predictors and identifying the regions of the signal associated with an outcome.

Speakers