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2013 | 11 | 7 | 1091-1100
Tytuł artykułu

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

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
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. [...]
Wydawca

Czasopismo
Rocznik
Tom
11
Numer
7
Strony
1091-1100
Opis fizyczny
Daty
wydano
2013-07-01
online
2013-04-26
Twórcy
  • Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, 85-094, Bydgoszcz, Poland, joanna.ronowicz@cm.umk.pl
  • 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
Bibliografia
  • [1] Guidance for industry: PAT - a framework for innovative pharmaceutical development, manufacturing, and quality assurance (U.S. Department of Health and Human Services, Food and Drug Administration, USA, September 2004)
  • [2] D.C. Hinz, Anal. Bioanal. Chem. 384, 1036 (2006) http://dx.doi.org/10.1007/s00216-005-3394-y[Crossref]
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  • [4] D.S. Hausman, R.T. Cambron, A. Sakr, Int. J. Pharm. 298, 80 (2005) http://dx.doi.org/10.1016/j.ijpharm.2005.04.011[Crossref]
  • [5] E.T.S. Skibsted, J.A. Westerhuis, A.K. Smilde, D.T. Witte, J. Pharm. Biomed. Anal. 43, 1297 (2007) http://dx.doi.org/10.1016/j.jpba.2006.10.037[Crossref]
  • [6] C. Buschmüler, W. Wiedey, C. Döscher, J. Dressler, J. Breitkreutz, Eur. J. Pharm. Biopharm. 69, 380 (2008) http://dx.doi.org/10.1016/j.ejpb.2007.09.014[Crossref]
  • [7] V. Lourenço, T. Herdling, G. Reich, J.C. Menezes, D. Lochmann, Eur. J. Pharm. Biopharm. 78, 513 (2011) http://dx.doi.org/10.1016/j.ejpb.2011.02.008[Crossref]
  • [8] A.C.F. Rumondor, L.S. Taylor, Int. J. Pharm. 398, 155 (2010) http://dx.doi.org/10.1016/j.ijpharm.2010.07.049[Crossref]
  • [9] F. Clarke, Vib. Spectrosc. 34, 25 (2004) http://dx.doi.org/10.1016/j.vibspec.2003.08.005[Crossref]
  • [10] K. Pöllänen, A. Häkkinen, S. Reinikainen, J. Rantanen, M. Karjalainen, M. Louhi-Kultanen, L. Nyström, J. Pharm. Biomed. Anal. 38, 275 (2005) http://dx.doi.org/10.1016/j.jpba.2005.01.009[Crossref]
  • [11] T. Rajalahti, O.M. Kvalheim, Int. J. Pharm. 417, 280 (2011) http://dx.doi.org/10.1016/j.ijpharm.2011.02.019[Crossref]
  • [12] T. Hill, P. Lewicki, STATISTICS: Methods and Applications. A Comprehensive Reference for Science, Industry, and Data Mining (StatSoft, Tulsa, Oklahoma, 2006)
  • [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]
  • [14] S. Görög, Anal. Bioanal. Chem. 377, 852 (2003) http://dx.doi.org/10.1007/s00216-003-2140-6[Crossref]
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.-psjd-doi-10_2478_s11532-013-0243-2
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