Predicting sample injection profiles in liquid chromatography: A modelling approach based on residence time
Monica Tirapelle1, Maximilian O Besenhard1, Luca Mazzei1
1Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
Journal of Chromatography. A
|September 20, 2023
Summary
Accurate prediction of sample injection profiles in liquid chromatography is crucial for reliable simulations. This study introduces a novel model using residence time distribution theory to improve simulation accuracy, reducing experimental costs in pharmaceutical development.
Area of Science:
- Analytical Chemistry
- Chemical Engineering
- Computational Science
Background:
- Simulations of liquid chromatography are vital for method development and cost reduction in pharmaceutical and biopharmaceutical industries.
- Inaccurate injection profiles used as inlet boundary conditions can lead to significant errors in chromatographic simulations.
Purpose of the Study:
- To develop a novel modeling approach for accurate prediction of injection profiles in liquid chromatography.
- To improve the reliability of in-silico simulations for analytical chromatography.
Main Methods:
- Utilized residence time distribution theory to model sample behavior.
- Accounted for the residence time of the sample in upstream components like injection loops, connecting tubes, and heat exchangers.
- Validated the model against experimental data from the literature for 20 operating conditions.
Main Results:
- Achieved average errors of 8.98% for the mean and 8.52% for the variance of predicted injection profiles.
- Demonstrated accurate prediction across various sample volumes and loop-filling levels without calibration.
- The model is based on fundamental equations and specific hardware details.
Conclusions:
- The proposed modeling approach significantly enhances the accuracy of injection profile predictions in liquid chromatography.
- This method improves the quality of in-silico simulations and optimization for analytical chromatography.
- It offers a robust, calibration-free solution for predicting injection profiles, benefiting pharmaceutical research and development.
Keywords:
Analytical chromatographyIn-silico optimizationInjection profileLiquid chromatographyResidence time distribution theoryMore Related Videos
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