Chemometric evaluation of pharmaceutical properties of antipyrine granules by near-infrared spectroscopy |
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Authors: | Makoto Otsuka Yoshifumi Mouri Yoshihisa Matsuda |
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Institution: | (1) Department of Pharmaceutical Technology, Kobe Pharmaceutical University, Higashi-Nada, 658-8558 Kobe, Japan |
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Abstract: | The purpose of this research was to apply near-infrared (NIR) spectroscopy with chemometrics to predict the change of pharmaceutical
properties of antipyrine granules during granulation by regulation of the amount of water added. The various kinds of granules
(mean particle size, 70–750 μm) were obtained from the powder mixture (1 g of antipyrine, 6 g of hydroxypropylcellulose, 140
g of lactose, and 60 g of potato starch) by regulation of the added water amount (11–19 wt/wt%) in a high-speed mixer. The
granules were characterized by mean particle size, angle of repose, compressibility, tablet porosity, and tablet hardness
as parameters of pharmaceutical properties. To predict the pharmaceutical properties, NIR spectra of the granules were measured
and analyzed by principal component regression, (PCR) analysis. The mean particle size of the granules increased from 81 μm
to 650 μm with an increase in the amount of water, and it was possible to make larger spherical granules with narrow particle
size distribution using a high-speed mixer. Angle of repose, compressibility, and porosity of the tablets decreased with an
increase of added water, but tablet hardness increased. The independent calibration models to evaluate particle size, angle
of repose, and tablet porosity and hardness were established by using PCR based on NIR spectra of granules, respectively.
The correlation coefficient constants of calibration curves for prediction of mean particle size, angle of repose, tablet
porosity, and tablet hardness were 0.9109, 0.8912, 0.7437, and 0.8064, respectively. It is possible that the pharmaceutical
properties of the granule, such as mean particle size, angle of repose, tablet porosity, and tablet hardness, could be predicted
by an NIR-chemometric method. |
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Keywords: | agitating granulating physical properties near-infrared spectroscopy chemomemetrics principle component regression analysis |
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