MIA and NIR Chemical Imaging for pharmaceutical product characterization

Chemometrics and Intelligent Laboratory Systems

Volumn 117, Issue , 2012, Pages 240-249

  Prats Montalbán, José M ^a   Jerez Rozo, Jackeline I ^b   Romañach, Rodolfo J ^b   Ferrer, Alberto ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b UNIVERSITY OF PUERTO RICO   (Puerto Rico)

Author keywords

CLS; Hyperspectral images; MCR; MIA; PAT; Resolution; Solubility; Texture

Indexed keywords

GRISEOFULVIN; HYDROXYPROPYLMETHYLCELLULOSE;

ARTICLE; CLASSICAL LEAST SQUARES; DATA EXTRACTION; DRUG FORMULATION; DRUG IDENTIFICATION; DRUG SOLUBILITY; IMAGE ANALYSIS; IMAGE QUALITY; IMAGING; MULTIVARIATE CURVE RESOLUTION; MULTIVARIATE IMAGE ANALYSIS; NEAR INFRARED CHEMICAL IMAGING; PRIORITY JOURNAL; STATISTICAL ANALYSIS;

EID: 84867231015     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.04.002     Document Type: Article

References (25)

1. Gendrin C., Roggo Y., Collet C. Pharmaceutical applications of vibrational chemical imaging and chemometrics: a review. Journal of Pharmaceutical and Biomedical Analysis 2008, 48:533-553.
2. Verreck G., Chun I., Peeters J., Rosenblatt J., Brewster M.E. Preparation and characterization of nanofibers containing amorphous drug dispersions generated by electrostatic spinning. Pharmaceutical Research 2003, 20:810-817.
3. Meng X., Chen Y., Chowdhury S.R., Yang D., Mitra S. Stabilizing dispersions of hydrophobic drug molecules using cellulose ethers during anti-solvent synthesis of micro-particulates. Colloids and Surfaces. B, Biointerfaces 2009, 70:7-14.
4. Amigo J.M., Cruz J., Bautista M., Maspoch S., Coello J., Blanco M. Study of pharmaceutical samples by NIR chemical-image and multivariate analysis. TRAC Trends in Analytical Chemistry 2008, 27:696-713.
5. Jérez Rozo J.I., Zarow A., Zhou B., Pinal R., Iqbal Z., Romañach R.J. Complementary near-infrared and Raman chemical imaging of pharmaceutical thin films. Journal of Pharmaceutical Sciences 2011, 100(11):4888-4895.
6. Tauler R. Multivariate curve resolution applied to second order data. Chemometrics and Intelligent Laboratory Systems 1995, 30:133-146.
7. de Juan A., Maeder M., Hancewicz T., Tauler R. Use of local-rank based spatial information for resolution of spectroscopic images. Journal of Chemometrics 2008, 22:291-298.
8. Kalivas J. Calibration methodologies. Comprehensive Chemometrics: Chemical and Biochemical data analysis 2009, Elsevier, Amsterdam. S. Brown, R. Tauler, B. Walczak (Eds.).
9. Haaland D.M., Melgaard D.K. New augmented classical least squares methods for improved quantitative spectral analyses. Vibrational Spectroscopy 2002, 29:171-175.
10. Prats-Montalbán J.M., de Juan A., Ferrer A. Multivariate image analysis: a review with applications. Chemometrics and Intelligent Laboratory Systems 2011, 107:1-23.
11. Geladi P., Grahn H. Multivariate Image Analysis 1996, John Wiley & Sons Ltd, Chichester, England.
12. de Juan A., Maeder M., Hancewicz T., Duponchel L., Tauler R. Chemometric tools for image analysis. Infrared and Raman Spectroscopic Imaging 2009, 65-109. Wiley-VCH Verlag GmbH & Co. KGaA.
13. Burger J. Bad pixel detection in hyperspectral staring camera systems. NIR News 2009, 20(1):9-12.
14. Jaumot J., Gargallo R., Dejuan A., Tauler R. A graphical user-friendly interface for MCR-ALS: a new tool for multivariate curve resolution in MATLAB. Chemometrics and Intelligent Laboratory Systems 2005, 76:101-110.
15. de Juan A., Tauler R., Dyson R., Marcolli C., Rault M., Maeder M. Spectroscopic imaging and chemometrics: a powerful combination for global and local sample analysis. TRAC Trends in Analytical Chemistry 2004, 23:70-79.
16. de Juan A., Maeder M., Hancewicz T., Tauler R. Local rank analysis for exploratory spectroscopic image analysis. Fixed Size Image Window-Evolving Factor Analysis. Chemometrics and Intelligent Laboratory Systems 2005, 77:64-74.
17. Jackson J.E. A User's Guide to Principal Components 1991, John Wiley & Sons, Inc.
18. Bharati M.H., MacGregor J.F. Texture analysis of images using principal component analysis. SPIE/Photonics Conference on Process Imaging for Automatic Control, Boston (2000) 2001, 27-37.
19. Prats-Montalbán J.M., Ferrer A. Integration of colour and textural information in multivariate image analysis: defect detection and classification issues. Journal of Chemometrics 2007, 21:10-23.
20. Geladi P., Kowalski B.R. Partial least-squares regression: a tutorial. Analytica Chimica Acta 1986, 185:1-17.
21. Soille P. Morphological Image Analysis: Principles and Applications 1999, Springer, NY.
22. Haralick R.M., Sternberg S.R., Zhuang X. Image analysis using mathematical morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence 1987, 9:532-550.
23. Yin W., Chen T., Zhou S.X., Chakraborty A. Background correction for cDNA microarray images using the TV+L1 model. Bioinformatics 2005, 21:2410-2416.
24. Prats-Montalbán J.M., Ferrer A., Bro R., Hancewicz T. Prediction of skin quality properties by different Multivariate Image Analysis methodologies. Chemometrics and Intelligent Laboratory Systems 2009, 96:6-13.
25. Rinnan A., van der Berg F., Engelsen S.B. Review of the most common pre-processing techniques for near-infrared spectra. Trends in Analytical Chemistry 2009, 28(10):1201-1222.