Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.
Spectrochim Acta A Mol Biomol Spectrosc. 2022 May 5;272:120996. doi: 10.1016/j.saa.2022.120996. Epub 2022 Feb 4.
Raman spectroscopy is an outstanding analytical tool increasingly utilized in the pharmaceutical field for the solid-state pharmaceutical drug analysis. In current study, the potential of Raman spectroscopy has been investigated for qualitative and quantitative analysis of solid dosage form of Losartan potassium. For this purpose, different solid dosage forms/concentrations of losartan potassium were prepared to compensate the commercially available pharmaceutical drug formulations and their Raman spectral data showed a gradual change in the specific Raman spectral features associated with the active pharmaceutical ingredient (API) of Losartan potassium as a function of change in the concentration. The Raman spectral data was analyzed by using Principal Component Analysis (PCA) for the classification of different spectral data sets of different concentrations of drug. Moreover, partial least square regression (PLSR) analysis was performed for monitoring the quantitative relation among different concentrations of Losartan potassium API and spectral data by constructing a predictive model. From the model, the value of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were observed to be 0.38 and 2.98 respectively and the value of goodness of fit was found to be 0.99. Furthermore, the quantity of unknown/blind sample of Losartan potassium formulation was also estimated by using PLSR model. From these results, it is demonstrated that Raman spectroscopy can be considered to be used for quick and reliable quantitative analysis of pharmaceutical solids.
拉曼光谱是一种出色的分析工具,在制药领域越来越多地用于药物的固态分析。在本研究中,研究了拉曼光谱在洛沙坦钾固体制剂的定性和定量分析中的潜力。为此,制备了不同的洛沙坦钾固体制剂/浓度,以补偿市售的药物制剂,并显示出其拉曼光谱数据与洛沙坦钾的活性药物成分(API)的特定拉曼光谱特征逐渐发生变化,这是浓度变化的函数。通过使用主成分分析(PCA)对不同浓度药物的不同光谱数据集进行分类,对拉曼光谱数据进行了分析。此外,通过构建预测模型,进行了偏最小二乘回归(PLSR)分析,以监测不同浓度的洛沙坦钾 API 和光谱数据之间的定量关系。从模型中可以观察到校准的均方根误差(RMSEC)和预测的均方根误差(RMSEP)的值分别为 0.38 和 2.98,拟合度的值为 0.99。此外,还通过 PLSR 模型估计了洛沙坦钾制剂的未知/盲样的数量。从这些结果可以看出,拉曼光谱可用于对药物固体进行快速可靠的定量分析。