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Number of results

Journal

2013 | 11 | 7 | 1091-1100

Article title

Impurity profile analysis of drug products containing acetylsalicylic acid: a chemometric approach

Content

Title variants

Languages of publication

EN

Abstracts

EN
In this work attention is focused on impurity profile analysis in combination with infrared spectroscopy and chemometric methods. This approach is considered as an alternative to generally complex and time-consuming classic analytical techniques such as liquid chromatography. Various strategies for constructing descriptive models able to identify relations among drug impurity profiles hidden in multivariate chromatographic data sets are also presented and discussed. The hierarchical (cluster analysis) and non-hierarchical segmentation algorithms (k-means method) and principal component analysis are applied to gain an overview of the similarities and dissimilarities among impurity profiles of acetylsalicylic acid formulations. A tree regression algorithm based on infrared spectra is used to predict the relative content of impurities in the drug products investigated. Satisfactory predictive abilities of the models derived indicate the possibility of implementing them in the quality control of drug products. [...]

Publisher

Journal

Year

Volume

11

Issue

7

Pages

1091-1100

Physical description

Dates

published
1 - 7 - 2013
online
26 - 4 - 2013

Contributors

  • Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, 85-094, Bydgoszcz, Poland
  • Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, 85-094, Bydgoszcz, Poland
  • Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, 85-094, Bydgoszcz, Poland
  • Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, 85-094, Bydgoszcz, Poland

References

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  • [13] T. Hastie, R. Tibshirani, J. Friedman, The elements of statistical learning: Data mining, inference, and prediction, 2nd edition (Springer-Verlag, New York, 2009) http://dx.doi.org/10.1007/978-0-387-84858-7[Crossref]
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Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.-psjd-doi-10_2478_s11532-013-0243-2
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