Department of Pharmacy, National University of Singapore, 18 Science Drive 4, Singapore, 117543, Singapore.
AAPS PharmSciTech. 2013 Mar;14(1):86-100. doi: 10.1208/s12249-012-9890-4. Epub 2012 Dec 11.
This study assessed the utility of near-infrared (NIR) spectroscopy for the real-time monitoring of content uniformity and critical quality attributes (tensile strength, Young's modulus, and relative density) of ribbed roller compacted flakes made by axially corrugated or ribbed rolls. A custom-built setup was used to capture off-line NIR spectra from the flakes containing micronized chlorpheniramine maleate, microcrystalline cellulose, lactose, and magnesium stearate. The partial least square regression method was employed to build calibration models from these off-line NIR spectra using experimental design and validated using test set validation. During calibration model development, various factors, such as spectral acquisition mode, probe positioning, spectral preprocessing method, and beam size, were investigated to improve the prediction ability of the models. The statistical results obtained for calibration models and their validation revealed that dynamic spectral acquisition and proper probe positioning were very crucial to minimize the incorporation of variability in NIR spectra resulting from the flake's undulation. Calibration and validation statistics also suggested the importance of selecting appropriate spectral preprocessing method and beam size. In this study, best calibration models resulted from standard normal variate followed by first derivative preprocessed dynamic spectra captured using beam size ~1.2 mm. Best calibration models constructed from off-line NIR spectra were used in real-time analysis of flake attributes. Finally, adequacy of best calibration models was established from real-time prediction results. Overall, with the proposed setup, it was possible to monitor the roller compaction process in real time for various properties associated with the ribbed flakes in a rapid, efficient, and nondestructive manner.
本研究评估了近红外(NIR)光谱技术在实时监测轴向波纹或肋状辊压制的肋状辊压薄片的含量均匀性和关键质量属性(拉伸强度、杨氏模量和相对密度)中的应用。使用定制的装置从含有马来酸氯苯那敏、微晶纤维素、乳糖和硬脂酸镁的薄片中捕获离线 NIR 光谱。使用实验设计和测试集验证,采用偏最小二乘回归方法从这些离线 NIR 光谱中建立校准模型。在建立校准模型的过程中,研究了各种因素,如光谱采集模式、探头定位、光谱预处理方法和光束大小,以提高模型的预测能力。校准模型和验证的统计结果表明,动态光谱采集和适当的探头定位对于最小化由于薄片的波动导致的 NIR 光谱中的变异性非常重要。校准和验证统计数据还表明选择适当的光谱预处理方法和光束大小的重要性。在这项研究中,标准正态变量(SNV)预处理的动态光谱采集和最佳光束大小(~1.2mm)的探头定位结果最好。使用离线 NIR 光谱构建的最佳校准模型用于实时分析薄片属性。最后,从实时预测结果中确定了最佳校准模型的充分性。总体而言,通过所提出的装置,有可能以快速、高效和非破坏性的方式实时监测与肋状薄片相关的各种属性的辊压过程。