LAPSE:2023.2491v1
Published Article

LAPSE:2023.2491v1
An Experimental and Modeling Combined Approach in Preparative Hydrophobic Interaction Chromatography
February 21, 2023
Abstract
Chromatography is a technique widely used in the purification of biopharmaceuticals, and generally consists of several chromatographic steps. In this work, Hydrophobic Interaction Chromatography (HIC) is investigated as a polishing step for the purification of therapeutic proteins. Adsorption mechanisms in hydrophobic interaction chromatography are still not completely clear and a limited amount of published data is available. In addition to new data on adsorption isotherms for some proteins (obtained both by high-throughput and frontal analysis method), and a comparison of different models proposed in the literature, two different approaches are compared in this work to investigate HIC. The predictive approach exploits an in-house code that simulates the behavior of the component in the column using the model parameters found from the fitting of experimental data. The estimation approach, on the other hand, exploits commercial software in which the model parameters are found by the fitting of a few experimental chromatograms. The two approaches are validated on some bind-elute runs: the predictive approach is very informative, but the experimental effort needed is high; the estimation approach is more effective, but the knowledge gained is lower. The second approach is also applied to an in-development industrial purification process and successfully resulted in predicting the behavior of the system, allowing for optimization with a reduction in the time and amount of sample needed.
Chromatography is a technique widely used in the purification of biopharmaceuticals, and generally consists of several chromatographic steps. In this work, Hydrophobic Interaction Chromatography (HIC) is investigated as a polishing step for the purification of therapeutic proteins. Adsorption mechanisms in hydrophobic interaction chromatography are still not completely clear and a limited amount of published data is available. In addition to new data on adsorption isotherms for some proteins (obtained both by high-throughput and frontal analysis method), and a comparison of different models proposed in the literature, two different approaches are compared in this work to investigate HIC. The predictive approach exploits an in-house code that simulates the behavior of the component in the column using the model parameters found from the fitting of experimental data. The estimation approach, on the other hand, exploits commercial software in which the model parameters are found by the fitting of a few experimental chromatograms. The two approaches are validated on some bind-elute runs: the predictive approach is very informative, but the experimental effort needed is high; the estimation approach is more effective, but the knowledge gained is lower. The second approach is also applied to an in-development industrial purification process and successfully resulted in predicting the behavior of the system, allowing for optimization with a reduction in the time and amount of sample needed.
Record ID
Keywords
high throughput, hydrophobic interaction chromatography, Modelling, preparative chromatography
Subject
Suggested Citation
Lietta E, Pieri A, Cardillo AG, Vanni M, Pisano R, Barresi AA. An Experimental and Modeling Combined Approach in Preparative Hydrophobic Interaction Chromatography. (2023). LAPSE:2023.2491v1
Author Affiliations
Lietta E: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy [ORCID]
Pieri A: Technological Research and Development, GSK, 53100 Siena, Italy
Cardillo AG: Technological Research and Development, GSK, 53100 Siena, Italy [ORCID]
Vanni M: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy
Pisano R: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy [ORCID]
Barresi AA: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy [ORCID]
Pieri A: Technological Research and Development, GSK, 53100 Siena, Italy
Cardillo AG: Technological Research and Development, GSK, 53100 Siena, Italy [ORCID]
Vanni M: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy
Pisano R: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy [ORCID]
Barresi AA: Department of Applied Science and Technology, Politecnico di Torino, 10129 Torino, Italy [ORCID]
Journal Name
Processes
Volume
10
Issue
5
First Page
1027
Year
2022
Publication Date
2022-05-20
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr10051027, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.2491v1
This Record
External Link

https://doi.org/10.3390/pr10051027
Publisher Version
Download
Meta
Record Statistics
Record Views
263
Version History
[v1] (Original Submission)
Feb 21, 2023
Verified by curator on
Feb 21, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
http://psecommunity.org/LAPSE:2023.2491v1
Record Owner
Auto Uploader for LAPSE
Links to Related Works
