Trunfio Nicholas, Lee Haewoo, Starkey Jason, Agarabi Cyrus, Liu Jay, Yoon Seongkyu
Dept. of Chemical Engineering, University of Massachusetts, Lowell, MA, USA.
Pfizer Inc, Chesterfield, USA, MO.
Biotechnol Prog. 2017 Jul;33(4):1127-1138. doi: 10.1002/btpr.2480. Epub 2017 May 16.
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.
表征哺乳动物细胞培养中所用原材料（如小麦水解物）变异性的两个主要问题是，对这些材料的分析可能耗时，且分析结果不易解释。为解决这些问题，光谱学可与化学计量学相结合，以提供一种快速、可靠且易于理解的原材料表征方法；通过评估给定原材料对最终产品质量的影响，这将改善细胞培养性能。在本研究中，四种光谱技术：近红外光谱、中红外光谱、拉曼光谱和荧光光谱与主成分分析结合使用，以表征小麦水解物的变异性，并提供证据证明对原材料的优劣批次进行分类是可行的。然后，将相同的光谱平台与偏最小二乘回归相结合，以定量预测两个细胞培养关键质量属性（CQA）：综合活细胞密度和IgG滴度。结果表明，近红外（NIR）光谱和荧光光谱能够表征小麦水解物的化学结构，其中NIR表现稍好；并且它们可用于估计原材料对CQA的影响。通过证明在小麦水解物中存在的所有成分中，六种氨基酸：精氨酸、甘氨酸、苯丙氨酸、酪氨酸、异亮氨酸和苏氨酸；以及五种微量元素：铜、磷、钼、砷和铝，对CQA有很大的、具有统计学意义的影响，并且NIR和荧光光谱在表征重要氨基酸方面表现最佳，从而证明了这些结果的合理性。还发现，所使用的任何光谱技术都不能很好地表征感兴趣的微量元素；然而，微量元素对CQA的影响也比氨基酸小。©2017作者 生物技术进展 由Wiley Periodicals, Inc.代表美国化学工程师学会出版，33:1127 - 1138, 2017。
