da Silva Fabiana E B, Flores Érico M M, Parisotto Graciele, Müller Edson I, Ferrão Marco F
Departamento de Farmácia, Universidade Federal do Pampa, Uruguaiana, RS, Brasil.
Departamento de Química, Universidade Federal de Santa Maria, Santa Maria, RS, Brasil.
An Acad Bras Cienc. 2016 Mar;88(1):1-15. doi: 10.1590/0001-3765201620150057. Epub 2016 Mar 4.
An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.
开发了一种使用漫反射红外傅里叶变换光谱法(DRIFTS)和偏最小二乘回归(PLS)对磺胺甲恶唑(SMZ)和甲氧苄啶(TMP)进行定量的替代方法。应用间隔偏最小二乘法(iPLS)和协同偏最小二乘法(siPLS)来选择与全光谱模型相比预测误差最低的光谱范围。使用了15种市售片剂配方和49个合成样品。所考虑的浓度范围为400至900 mg g-1的SMZ和80至240 mg g-1的TMP。通过漫反射红外傅里叶变换光谱法(DRIFTS)在600至4000 cm-1之间以4 cm-1的分辨率记录光谱数据。将所提出的方法与高效液相色谱法(HPLC)进行比较。在使用siPLS对磺胺甲恶唑(SMZ)和甲氧苄啶(TMP)样品的模型进行验证期间,从预测均方根误差(RMSEP)获得的结果表明,该方法是用于药物制剂定量分析的有效技术。与全光谱PLS模型相比,所选的间隔算法允许构建误差较小的回归模型。通过siPLS选择最佳光谱区域后,SMZ的RMSEP为13.03 mg g-1,TMP的RMSEP为4.88 mg g-1。