Understanding the effects of system differences for parameter estimation and scale-up of high throughput...

Area of Science:

• Chromatography
• Bioseparation
• Process Analytical Technology

Background:

• RoboColumns® systems on automated liquid handling devices differ from larger scale systems in elution profile determination.
• Multistep gradients are used in RoboColumns® to approximate linear gradients common in larger scale chromatography.

Purpose of the Study:

• To evaluate the impact of fraction collection and multistep gradients in RoboColumns® on experimental data and column simulation.
• To develop a method for correcting RoboColumn® data for improved comparison with benchtop chromatography.
• To assess the suitability of Linear Steric Mass-Action (SMA) parameters for modeling RoboColumn® data.

Main Methods:

• Column simulations were performed to assess the effects of fraction collection and multistep gradients.
• An empirical transformation was developed to correct elution data from RoboColumn® experiments.
• Linear SMA parameters were estimated using corrected data and used for performance prediction.

Main Results:

• Fraction collection was found to reduce the first moments of elution peaks.
• The effect of multistep gradients on retention volume was dependent on gradient step length.
• Corrected RoboColumn® data showed improved agreement with benchtop chromatography results.
• SMA parameters successfully predicted benchtop system performance and modeled RoboColumn® gradient data.

Conclusions:

• A methodology was proposed to account for operational differences in RoboColumns® for accurate scale-up.
• The developed correction method enhances the comparability of experimental data across different scales.
• Linear SMA parameters are effective for modeling RoboColumn® data when accounting for system-specific operational parameters.