Meningococcal polysaccharides identification by NIR spectroscopy and chemometrics
•NIR method enables the identification of meningococcal polysaccharides A and C.•NIR spectroscopy provides a fast, non-destructive alternative to existing methods.•SIMCA and PLS-DA models can be used as classification tools. Near-infrared (NIR) spectroscopy is an attractive tool for pharmaceutical a...
Saved in:
Published in | Carbohydrate polymers Vol. 216; pp. 36 - 44 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
15.07.2019
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | •NIR method enables the identification of meningococcal polysaccharides A and C.•NIR spectroscopy provides a fast, non-destructive alternative to existing methods.•SIMCA and PLS-DA models can be used as classification tools.
Near-infrared (NIR) spectroscopy is an attractive tool for pharmaceutical analyses. The main purpose of this study was to assess the potential of NIR spectroscopy coupled with different multivariate classification tools for the identification of meningococcal polysaccharide serogroups A and C. Moreover, it sought to determine, if the models established on production batches, could be used to correctly identify National Institute for Biological Standards and Control standards.
Two different classification tools were investigated: soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). Models’ performance was evaluated by external validation. Although both models were able to correctly classify 100% of meningococcal polysaccharides from serogroups A and C, they performed differently in the presence of similar non-target serogroups W135 and Y.
These results demonstrate that NIR spectroscopy, coupled with either SIMCA or PLS-DA, provides a method suitable for the identification of meningococcal polysaccharides A and C. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0144-8617 1879-1344 |
DOI: | 10.1016/j.carbpol.2019.03.102 |