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http://dx.doi.org/10.5806/AST.2011.24.6.519

Real-time monitoring for blending uniformity of trimebutine CR tablets using near-infrared and Raman spectroscopy  

Woo, Young-Ah (Korea United Pharm. Inc.)
Publication Information
Analytical Science and Technology / v.24, no.6, 2011 , pp. 519-526 More about this Journal
Abstract
Chemometrics using near-infrared (NIR) and Raman spectroscopy have found significant uses in a variety quantitative and qualitative analyses of pharmaceutical products in complex matrixes. Most of the pharmaceutical can be measured directly with little or no sample preparation using these spectroscopic methods. During pharmaceutical manufacturing process, analytical techniques with no or less sample preparation are very critical to confirm the quality. This study showed NIR and Raman spectroscopy with principal component analysis (PCA) was very effective for the blending processing control. It is of utmost importance to evaluate critical parameters related to quality of products during pharmaceutical processing. The blending is confirmed by off-line determination of active pharmaceutical ingredient (API) by a conventional method such as high performance liquid chromatography (HPLC) and UV spectroscopy. These analytical methods are time-consuming and ineffective for real time control. This study showed the possibility for the determination of blend uniformity end-point of CR tablets with the use of both NIR and Raman spectroscopy. The samples were acquired from six positions during blending processing with U-type blender from 0 to 30 min. Using both collected NIR and Raman spectral data, principal component analysis (PCA) was used to follow the uniformity of blending and finally determine the end-point. The variation of homogeneity of six samples during blending was clearly found and blend uniformity end-point was successfully confirmed in the domains of principal component (PC) scores.
Keywords
trimebutine CR tablets; Blending; near-infrared (NIR) spectroscopy; Raman spectroscopy; Principal component analysis (PCA);
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