ABSTRACT: Two of the primary issues with characterizing the variability of raw materials used in mammalian cell culture, such as wheat hydrolysate, is that the analyses of these materials can be time consuming, and the results of the analyses are not straightforward to interpret. To solve these issues, spectroscopy can be combined with chemometrics to provide a quick, robust and easy to understand methodology for the characterization of raw materials; which will improve cell culture performance by providing an assessment of the impact that a given raw material will have on final product quality. In this study, four spectroscopic technologies: near infrared spectroscopy, middle infrared spectroscopy, Raman spectroscopy, and fluorescence spectroscopy were used in conjunction with principal component analysis to characterize the variability of wheat hydrolysates, and to provide evidence that the classification of good and bad lots of raw material is possible. Then, the same spectroscopic platforms are combined with partial least squares regressions to quantitatively predict two cell culture critical quality attributes (CQA): integrated viable cell density and IgG titer. The results showed that near infrared (NIR) spectroscopy and fluorescence spectroscopy are capable of characterizing the wheat hydrolysate's chemical structure, with NIR performing slightly better; and that they can be used to estimate the raw materials' impact on the CQAs. These results were justified by demonstrating that of all the components present in the wheat hydrolysates, six amino acids: arginine, glycine, phenylalanine, tyrosine, isoleucine and threonine; and five trace elements: copper, phosphorus, molybdenum, arsenic and aluminum, had a large, statistically significant effect on the CQAs, and that NIR and fluorescence spectroscopy performed the best for characterizing the important amino acids. It was also found that the trace elements of interest were not characterized well by any of the spectral technologies used; however, the trace elements were also shown to have a less significant effect on the CQAs than the amino acids. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers, 33:1127-1138, 2017.
