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A systematic approach for estimating colloidal particle adsorption model parameters
Oliver Lorenz-Cristea1, Angela Wiebe1, Judith Thoma1
1DSP Development, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.
Journal of Chromatography. A
|November 16, 2024
Summary
A new strategy systematically estimates parameters for the Colloidal Particle Adsorption (CPA) model, crucial for biopharmaceutical downstream process development. This method reduces experiments needed for accurate ion-exchange chromatography modeling.
Area of Science:
- Biochemical Engineering
- Chromatography
- Process Development
Background:
- Accurate ion-exchange chromatography (IEX) model parameters are vital for biopharmaceutical downstream process development.
- Current model calibration methods face challenges due to model limitations and parameter correlations, causing inefficiencies.
- A systematic approach is needed for parameter estimation in the emerging Colloidal Particle Adsorption (CPA) model.
Purpose of the Study:
- To present a novel, systematic strategy for estimating CPA model parameters.
- To improve the efficiency and accuracy of model-assisted biopharmaceutical downstream process development.
- To enable prediction of elution behavior across various loading conditions and elution modes.
Main Methods:
- Performed parameter sensitivity analysis to identify key estimation levers.
- Developed a minimal experimental dataset strategy using breakthrough and gradient elution experiments.
- Utilized a surrogate-assisted global-optimization tool and a customized objective function for efficient parameter fitting.
- Validated the approach on three model proteins (50, 150, 200 kDa) using strong cation exchange chromatography.
Main Results:
- Identified key parameters and their correlation structure for CPA model estimation.
- Demonstrated successful prediction of elution behavior for low and high load densities in gradient and step elution.
- Established a minimal experimental design requiring only one breakthrough, one high-load, and three low-load gradient elution experiments.
- Achieved high-throughput CPA model calibration for single components.
Conclusions:
- The developed strategy offers significant improvements for CPA model parameter estimation.
- The validated CPA models accurately describe various experimental conditions, including non-binding pulses, gradient/isocratic elution, and breakthrough.
- This approach enhances the efficiency of model-assisted downstream process development for biopharmaceuticals.
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