Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis

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Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis. / Strachan, Clare J.; Pratiwi, Destari; Gordon, Keith C.; Rades, Thomas.

In: Journal of Raman Spectroscopy, Vol. 35, No. 5, 05.2004, p. 347-352.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Strachan, CJ, Pratiwi, D, Gordon, KC & Rades, T 2004, 'Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis', Journal of Raman Spectroscopy, vol. 35, no. 5, pp. 347-352. https://doi.org/10.1002/jrs.1140

APA

Strachan, C. J., Pratiwi, D., Gordon, K. C., & Rades, T. (2004). Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis. Journal of Raman Spectroscopy, 35(5), 347-352. https://doi.org/10.1002/jrs.1140

Vancouver

Strachan CJ, Pratiwi D, Gordon KC, Rades T. Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis. Journal of Raman Spectroscopy. 2004 May;35(5):347-352. https://doi.org/10.1002/jrs.1140

Author

Strachan, Clare J. ; Pratiwi, Destari ; Gordon, Keith C. ; Rades, Thomas. / Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis. In: Journal of Raman Spectroscopy. 2004 ; Vol. 35, No. 5. pp. 347-352.

Bibtex

@article{8d7c070e9fd54a4bb3cbf3c5529048ea,
title = "Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis",
abstract = "The polymorphic behaviour of drugs is a major concern of the pharmaceutical industry as it may have considerable formulation, therapeutic, legal and commercial implications. It is therefore crucial to be able adequately to identify and quantify different polymorphic forms of drugs as early as possible in the drug discovery and development process. The aim of the present study was to investigate the application of Raman spectroscopy and principal components analysis (PCA) to the quantitative analysis of polymorphic mixtures of carbamazepine forms III and I, based on both individual peak areas and heights in the Raman spectra and whole wavenumber ranges. Various linear regressions indicated that in general using every fourth wavenumber value of a larger region of the Raman spectrum gives better quantitative results than choosing defined peak areas and peak heights, as the spectral differences between the polymorphs were only subtle. Baseline correction of the spectral data did not appear to improve the quantitative analysis, with detection and quantification limits being the lowest (0.33 and 1.09%, respectively) and R 2 being the highest (0.96) when using every fourth wavenumber value from 2950 to 3100 cm-1 as input data for the PCA analysis without baseline correction. This study demonstrated that PCA of Raman spectroscopic data provides a sensitive method for the quantitative analysis of polymorphic forms, with a quantitation limit of <2%, if the spectral input data are selected carefully. In the absence of clear and distinct spectral differences at certain wavenumbers between the polymorphic forms, selection of larger spectral regions that contain most of the detectable differences between the two forms appears to be the best data selection technique.",
keywords = "Carbamazepine, Polymorphism, Principal components analysis, Quantitative analysis",
author = "Strachan, {Clare J.} and Destari Pratiwi and Gordon, {Keith C.} and Thomas Rades",
year = "2004",
month = may,
doi = "10.1002/jrs.1140",
language = "English",
volume = "35",
pages = "347--352",
journal = "Journal of Raman Spectroscopy",
issn = "0377-0486",
publisher = "JohnWiley & Sons Ltd",
number = "5",

}

RIS

TY - JOUR

T1 - Quantitative analysis of polymorphic mixtures of carbamazepine by Raman spectroscopy and principal components analysis

AU - Strachan, Clare J.

AU - Pratiwi, Destari

AU - Gordon, Keith C.

AU - Rades, Thomas

PY - 2004/5

Y1 - 2004/5

N2 - The polymorphic behaviour of drugs is a major concern of the pharmaceutical industry as it may have considerable formulation, therapeutic, legal and commercial implications. It is therefore crucial to be able adequately to identify and quantify different polymorphic forms of drugs as early as possible in the drug discovery and development process. The aim of the present study was to investigate the application of Raman spectroscopy and principal components analysis (PCA) to the quantitative analysis of polymorphic mixtures of carbamazepine forms III and I, based on both individual peak areas and heights in the Raman spectra and whole wavenumber ranges. Various linear regressions indicated that in general using every fourth wavenumber value of a larger region of the Raman spectrum gives better quantitative results than choosing defined peak areas and peak heights, as the spectral differences between the polymorphs were only subtle. Baseline correction of the spectral data did not appear to improve the quantitative analysis, with detection and quantification limits being the lowest (0.33 and 1.09%, respectively) and R 2 being the highest (0.96) when using every fourth wavenumber value from 2950 to 3100 cm-1 as input data for the PCA analysis without baseline correction. This study demonstrated that PCA of Raman spectroscopic data provides a sensitive method for the quantitative analysis of polymorphic forms, with a quantitation limit of <2%, if the spectral input data are selected carefully. In the absence of clear and distinct spectral differences at certain wavenumbers between the polymorphic forms, selection of larger spectral regions that contain most of the detectable differences between the two forms appears to be the best data selection technique.

AB - The polymorphic behaviour of drugs is a major concern of the pharmaceutical industry as it may have considerable formulation, therapeutic, legal and commercial implications. It is therefore crucial to be able adequately to identify and quantify different polymorphic forms of drugs as early as possible in the drug discovery and development process. The aim of the present study was to investigate the application of Raman spectroscopy and principal components analysis (PCA) to the quantitative analysis of polymorphic mixtures of carbamazepine forms III and I, based on both individual peak areas and heights in the Raman spectra and whole wavenumber ranges. Various linear regressions indicated that in general using every fourth wavenumber value of a larger region of the Raman spectrum gives better quantitative results than choosing defined peak areas and peak heights, as the spectral differences between the polymorphs were only subtle. Baseline correction of the spectral data did not appear to improve the quantitative analysis, with detection and quantification limits being the lowest (0.33 and 1.09%, respectively) and R 2 being the highest (0.96) when using every fourth wavenumber value from 2950 to 3100 cm-1 as input data for the PCA analysis without baseline correction. This study demonstrated that PCA of Raman spectroscopic data provides a sensitive method for the quantitative analysis of polymorphic forms, with a quantitation limit of <2%, if the spectral input data are selected carefully. In the absence of clear and distinct spectral differences at certain wavenumbers between the polymorphic forms, selection of larger spectral regions that contain most of the detectable differences between the two forms appears to be the best data selection technique.

KW - Carbamazepine

KW - Polymorphism

KW - Principal components analysis

KW - Quantitative analysis

UR - http://www.scopus.com/inward/record.url?scp=2442637707&partnerID=8YFLogxK

U2 - 10.1002/jrs.1140

DO - 10.1002/jrs.1140

M3 - Journal article

AN - SCOPUS:2442637707

VL - 35

SP - 347

EP - 352

JO - Journal of Raman Spectroscopy

JF - Journal of Raman Spectroscopy

SN - 0377-0486

IS - 5

ER -

ID: 299428672