A novel multivariate approach using science-based calibration for direct coating thickness determination in real-time NIR process monitoring

被引:18
作者
Moeltgen, C. -V. [1 ]
Herdling, T. [2 ]
Reich, G. [1 ]
机构
[1] Heidelberg Univ, Inst Pharm & Mol Biotechnol, Dept Pharmaceut Technol & Biopharmaceut, D-69120 Heidelberg, Germany
[2] Merck Serono, PAT Lab, Qual Operat, Darmstadt, Germany
关键词
Science-based calibration (SBC); Matched filter; Wiener filter; Direct coating thickness; NIRS; PAT; Coating process; Thin film; PROCESS ANALYTICAL TECHNOLOGY; QUANTITATIVE-ANALYSIS; PURE COMPONENT; FILM THICKNESS; SPECTROSCOPY; SPECTROMETRY; PREDICTION; TABLETS;
D O I
10.1016/j.ejpb.2013.09.011
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
This study demonstrates an approach, using science-based calibration (SBC), for direct coating thickness determination on heart-shaped tablets in real-time. Near-Infrared (NIR) spectra were collected during four full industrial pan coating operations. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film up to a film thickness of 28 mu m. The application of SBC permits the calibration of the NIR spectral data without using costly determined reference values. This is due to the fact that SBC combines classical methods to estimate the coating signal and statistical methods for the noise estimation. The approach enabled the use of NIR for the measurement of the film thickness increase from around 8 to 28 mu m of four independent batches in real-time. The developed model provided a spectroscopic limit of detection for the coating thickness of 0.64 +/- 0.03 mu m root-mean square (RMS). In the commonly used statistical methods for calibration, such as Partial Least Squares (PLS), sufficiently varying reference values are needed for calibration. For thin non-functional coatings this is a challenge because the quality of the model depends on the accuracy of the selected calibration standards. The obvious and simple approach of SBC eliminates many of the problems associated with the conventional statistical methods and offers an alternative for multivariate calibration. (cC) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:1056 / 1063
页数:8
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