On-line parallel factor analysis. A step forward in the monitoring of bioprocesses in real time

Abstract

There is a widely growing interest to obtain robust and rapid methodologies capable of monitoring bioprocesses in real time. Different analytical methods have been adapted to measure cell density evolution throughout a culture, and fluorescence spectroscopy is becoming promising technique due to its sensitivity, selectivity towards important chemical analytes and its easy implementation as a non-invasive procedure. This work is focused on showing the advantages of coupling the trilinear algorithm Parallel Factor Analysis (PARAFAC) to the Multivariate Statistical Process Control (MSPC) as a monitoring and real-time control tool for bioprocesses. In this context, both induced (growing on methanol) and non induced (growing on glycerol) Pichia pastoris cultures were monitored by multiwavelength-fluorescence. In the first one methanol was used as substrate; whereas glycerol was used in the second one. Taking advantages of the mathematical properties of PARAFAC, batches of a bioprocess measured under normal operating conditions (NOC) were used to develop a calibration models. Residuals of the model in combination with MSPC were used to establish two control limits. The control limits were used for new batches in real time. Fluorescence spectroscopy combined with PARAFAC and MSPC is a feasible approach for controlling and performing fault diagnosis of bioprocesses offering the opportunity of performing real-time process surveillance based on relevant quality measurements.