硫酸羟氯喹颗粒水分含量测定近红外定量模型的建立

Establishment of quantitative model for determination of moisture content of hydroxychloroquine sulfate particles by near infrared spectroscopy

目的建立微型近红外光谱仪测定硫酸羟氯喹颗粒水分含量的定量分析模型。方法真空干燥和加湿实验改变硫酸羟氯喹颗粒的含水量范围,采用标准正则变换(standard normal variate transformation,SNV)、二阶导数(second derivative,2nd Derivative)和Karl Norris平滑的光谱预处理方法,选择617~1 068 nm波段,运用偏最小二乘回归(partial least squares,PLS)建立近红外定量分析模型。结果所建模型的校正误差均方根(root mean square error of calibration,RMSEC)为0.178,相关系数Rc为0.991 6,预测误差均方根(root mean square error of prediction,RMSEP)为0.197,相关系数Rp为0.989 6,验证集标准偏差与预测标准偏差的比值(ratio of standard deviation of the validation set to error of prediction,RPD)为6.95,方法学验证中准确度和重复性符合要求。结论微型近红外光谱仪应用于测定硫酸羟氯喹颗粒的含水量是可行的,为微型近红外光谱仪应用于药物的在线干燥过程提供了实验基础。

Objective To establish a quantitative analysis model for determining the moisture content of hydroxychloroquine sulfate particles by micro-NIR spectrometer.Methods The range of water content of hydroxychloroquine sulfate particles was changed by vacuum drying and humidification experiments.The standard normal variate transformation(SNV)and second derivative followed by Karl Norris smooth were used for spectra pretreating and 617-1 068 nm were selected as the spectral range.The near infrared quantitative analysis model was developed using the partial least squares(PLS)regression.Results The quantitative calibration model had good correlation coefficients R with an Rc value equal to 0.991 6 and an Rp value equal to 0.989 6.The root mean square error of calibration(RMSEC)was 0.178 and the root mean square error of prediction error(RMSEP)was 0.197.The ratio of standard deviation of validation set to standard error of prediction(RPD)was 6.95.In addition,good accuracy and repeatability was obtained in model validation.Conclusion It is feasible to determine water content of hydroxychloroquine sulfate particles by micro-NIR spectrometer.It provides the experimental basis for the application of micro-NIR spectrometer in online monitoring of drying of drugs.