title: Advances in inline quantification of co-eluting proteins in chromatography: Process-data-based model calibration and application towards real-life separation issues.
abstract: Pooling decisions in preparative liquid chromatography for protein purification are usually based on univariate UV absorption measurements that are not able to differentiate between product and co-eluting contaminants. This can result in inconsistent pool purities or yields, if there is a batch-to-batch variability of the feedstock. To overcome this analytical bottleneck, a tool for selective inline quantification of co-eluting model proteins using mid-UV absorption spectra and Partial Least Squares Regression (PLS) was presented in a previous study and applied for real-time pooling decisions. In this paper, a process-data-based method for the PLS model calibration will be introduced that allows the application of the tool towards chromatography steps of real-life processes. The process-data-based calibration method uses recorded inline mid-UV absorption spectra that are correlated with offline fraction analytics to calibrate PLS models. In order to generate average spectra from the inline data, a Visual Basic for Application macro was successfully developed. The process-data-based model calibration was established using a ternary model protein system. Afterwards, it was successfully demonstrated in two case studies that the calibration method is applicable towards real-life separation issues. The calibrated PLS models allowed a successful quantification of the co-eluting species in a cation-exchange-based aggregate and fraction removal during the purification of monoclonal antibodies and of co-eluting serum proteins in an anion-exchange-based purification of Cohn supernatant I. Consequently, the presented process-data-based PLS model calibration in combination with the tool for selective inline quantification has a great potential for the monitoring of future chromatography steps and may contribute to manage batch-to-batch variability by real-time pooling decisions.
authors: Karlsruhe Institute of Technology, Engler-Bunte-Ring 1, 76131, Karlsruhe, Germany.
authors: Nina
authors: N
authors: Brestrich
authors: Karlsruhe Institute of Technology, Engler-Bunte-Ring 1, 76131, Karlsruhe, Germany.
authors: Adrian
authors: A
authors: Sanden
authors: Karlsruhe Institute of Technology, Engler-Bunte-Ring 1, 76131, Karlsruhe, Germany.
authors: Axel
authors: A
authors: Kraft
authors: CSL Behring Australia, Broadmeadows, VIC, Australia.
authors: Karl
authors: K
authors: McCann
authors: CSL Behring Australia, Broadmeadows, VIC, Australia.
authors: Joseph
authors: J
authors: Bertolini
authors: Karlsruhe Institute of Technology, Engler-Bunte-Ring 1, 76131, Karlsruhe, Germany. juergen.hubbuch@kit.edu.
authors: Jürgen
authors: J
authors: Hubbuch
mesh_terms: D002138:Calibration; D002853:Chromatography, Liquid / Q000379:methods* / Q000592:standards*; D011506:Proteins / Q000032:analysis* / Q000302:isolation & purification*; D013056:Spectrophotometry, Ultraviolet / Q000379:methods
chemical_list: D011506:Proteins
keywords: bioprocess monitoring; chemometrics; inline monitoring; partial least squares regression; process analytical technology; protein analytics; selective protein quantification