论文标题
Terahertz频域传感与定量多元分析进行药品检查
Terahertz Frequency-Domain Sensing Combined with Quantitative Multivariate Analysis for Pharmaceutical Tablet Inspection
论文作者
论文摘要
近红外(NIR)和拉曼光谱与多变量分析相结合是确定和定量药物片剂的化学性质(如活性药物成分(API))的化学性质的建立技术。但是,这些技术对粒度变化具有高灵敏度,并且不是片剂片剂(例如片剂密度)的物理性质的理想选择。在这项工作中,我们探索了Terahertz频域光谱法的可行性,具有低散射效应的优势,并结合了多变量分析以量化API浓度和片剂密度。我们研究了33片,由布洛芬,甘露醇和具有API浓度和填充粒径的润滑剂组成,作为设计因子。使用矢量网络分析仪,频率扩展器,喇叭天线和四个轴心抛物线镜,以750 GHz至1.5 THZ的传输模式以传输模式测量Terahertz信号。预处理衰减光谱数据,并将正交部分最小二平方(OPL)回归应用于光谱数据,以获得用于API浓度和片剂密度的定量预测模型。使用测试集评估模型的性能。尽管获得了API浓度的公平模型,但显示了片剂密度的高质量模型。片剂密度的校准设置的确定系数为0.97,API浓度的确定系数为0.98,而测试集的相对预测误差分别为0.7%和片剂密度和API浓度模型的0.7%和6%。
Near infrared (NIR) and Raman spectroscopy combined with multivariate analysis are established techniques for the identification and quantification of chemical properties of pharmaceutical tablets like the concentration of active pharmaceutical ingredients (API). However, these techniques suffer from a high sensitivity to particle size variations and are not ideal for the characterization of physical properties of tablets such as tablet density. In this work, we have explored the feasibility of terahertz frequency-domain spectroscopy, with the advantage of low scattering effects, combined with multivariate analysis to quantify API concentration and tablet density. We studied 33 tablets, consisting of Ibuprofen, Mannitol, and a lubricant with API concentration and filler particle size as the design factors. The terahertz signal was measured in transmission mode across the frequency range 750 GHz to 1.5 THz using a vector network analyzer, frequency extenders, horn antennas, and four off-axis parabolic mirrors. The attenuation spectral data were pre-processed and orthogonal partial least square (OPLS) regression was applied to the spectral data to obtain quantitative prediction models for API concentration and tablet density. The performance of the models was assessed using test sets. While a fair model was obtained for API concentration, a high-quality model was demonstrated for tablet density. The coefficient of determination for the calibration set was 0.97 for tablet density and 0.98 for API concentration, while the relative prediction errors for the test set were 0.7% and 6%for tablet density and API concentration models, respectively.