title: Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).
abstract: Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T2and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry.
authors.affiliation: LASIR CNRS UMR 8516, Université de Lille, Sciences et Technologies, 59655 Villeneuve d'Ascq Cedex, France.
authors.forename: Ya-Juan
authors.initials: YJ
authors.lastname: Liu
authors.affiliation: LASIR CNRS UMR 8516, Université de Lille, Sciences et Technologies, 59655 Villeneuve d'Ascq Cedex, France.
authors.forename: Silvère
authors.initials: S
authors.lastname: André
authors.affiliation: Sanofi Pasteur, 1541 Avenue Marcel Mérieux, 69280 Marcy-l'Étoile, France.
authors.forename: Lydia
authors.initials: L
authors.lastname: Saint Cristau
authors.affiliation: Merial, 29 Avenue Tony Garnier, 69007 Lyon, France.
authors.forename: Sylvain
authors.initials: S
authors.lastname: Lagresle
authors.affiliation: Merial, 29 Avenue Tony Garnier, 69007 Lyon, France.
authors.forename: Zahia
authors.initials: Z
authors.lastname: Hannas
authors.affiliation: Sanofi Pasteur, 1541 Avenue Marcel Mérieux, 69280 Marcy-l'Étoile, France.
authors.forename: Éric
authors.initials: É
authors.lastname: Calvosa
authors.affiliation: LASIR CNRS UMR 8516, Université de Lille, Sciences et Technologies, 59655 Villeneuve d'Ascq Cedex, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Devos
authors.affiliation: LASIR CNRS UMR 8516, Université de Lille, Sciences et Technologies, 59655 Villeneuve d'Ascq Cedex, France. Electronic address: ludovic.duponchel@univ-lille1.fr.
authors.forename: Ludovic
authors.initials: L
authors.lastname: Duponchel
mesh_terms: D000818:Animals; D016466:CHO Cells; D018929:Cell Culture Techniques; D003412:Cricetulus; D015233:Models, Statistical; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D013059:Spectrum Analysis, Raman
keywords: Cell culture; Chemometrics; Correlation optimized warping (COW); Multi-way principal component analysis (MPCA); Multivariate statistical process control (MSPC); Raman spectroscopy