title: A tool for selective inline quantification of co-eluting proteins in chromatography using spectral analysis and partial least squares regression.
abstract: Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities.
authors: Institute of Process Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Engler-Bunte-Ring 1, 76131 Karlsruhe, Germany.
authors: Nina
authors: N
authors: Brestrich
authors: Till
authors: T
authors: Briskot
authors: Anna
authors: A
authors: Osberghaus
authors: Jürgen
authors: J
authors: Hubbuch
mesh_terms: D002845:Chromatography / Q000295:instrumentation / Q000379:methods*; D016018:Least-Squares Analysis; D011506:Proteins / Q000032:analysis*; D012984:Software; D013057:Spectrum Analysis / Q000295:instrumentation / Q000379:methods*
chemical_list: D011506:Proteins
keywords: bioprocess monitoring; chemometrics; inline monitoring; partial least squares regression; process analytical technology; protein analytics; selective protein quantification