Evidence map›Paper›PMID 28393480›Full record

ArticleBiotechnology progress2017

Characterization of mammalian cell culture raw materials by combining spectroscopy and chemometrics.

Nicholas Trunfio, Haewoo Lee, Jason Starkey, Cyrus Agarabi, Jay Liu, Seongkyu Yoon

Abstract read
In one paragraph

Article in Biotechnology progress, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nicholas TrunfioDept. of Chemical Engineering, University of Massachusetts, Lowell, MA, USA.
Haewoo LeeDept. of Chemical Engineering, University of Massachusetts, Lowell, MA, USA.
Jason StarkeyPfizer Inc, Chesterfield, USA, MO.
Cyrus AgarabiDiv. II, Office of Biotechnology Products, Office of Pharmaceutical Quality, CDER, FDA, Silver Spring, MD, USA.
Jay LiuDept. of Chemical Engineering, Pukyung National University, Busan, Nam-Gu, Korea.
Seongkyu YoonDept. of Chemical Engineering, University of Massachusetts, Lowell, MA, USA.ORCID http://orcid.org/0000-0002-5330-8784

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Principal Component AnalysisSpectrum Analysis, RamanAnimalsCell Culture TechniquesCells, CulturedCHO CellsCricetulusCulture MediaSpectrometry, FluorescenceSpectrophotometry, InfraredCulture Mediabioinformaticsbiologycell culturefluorescencemiddle infraredmultivariate data analysisnear infraredpartial least squares regressionsprincipal component analysisramanraw material characterizationspectroscopy

Identifiers

PMID28393480
PMCPMC5573913

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.