Compact strength and the particle-size distribution of milled roller compacted compacts were correlated to the slope of the best-fit line through nearinfrared spectra for samples prepared under different roll speeds and feed rates. The above correlations were found to hold for compacts prepared from
Characteristics of hydroxypropyl methylcellulose influencing compactibility and prediction of particle and tablet properties by infrared spectroscopy
✍ Scribed by Christina Gustafsson; Christer Nyström; Helena Lennholm; Maria C. Bonferoni; Carla M. Caramella
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 155 KB
- Volume
- 92
- Category
- Article
- ISSN
- 0022-3549
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✦ Synopsis
Particle characteristics, chemical substitution, compaction behavior, and tablet properties of hydroxypropyl methylcellulose powders from two different suppliers were related using multivariate data analysis. By Principal Component Analysis it was shown that the the degree of substitution of the HPMC powders did not correlate to the particle and compaction properties as strongly as anticipated. Particle shape and powder surface area seem to be more important for the compaction behaviour of the powders than the degree of substitution. In addition, particle and tablet properties were predicted from infrared spectral data. Fourier transform infrared (FTIR) and near infrared (NIR) spectral data of the powders were combined with measured values of the particle characteristics, compaction behavior, and tablet properties using the multivariate data analysis program SIMCA 7.1. Properties like density, particle shape, tablet tensile strength, and drug release characteristics of the HPMC powders and corresponding tablets in this study could be predicted using Partial Least Squares models. In conclusion, the particle shape and powder surface area of HPMC powders seem to be important factors for the quality of tablet attained. Further, this study confirms that NIR and FTIR analysis used in combination with multivariate analysis are powerful tools for predicting the properties of materials and the quality of the end product.
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