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作 者:秦晓东 朱俐[1] 赵瑜[1] 尹利辉[1] Qin Xiaodong;Zhu Li;Zhao Yu;Yin Lihui(National Institutes for Food and Drug Control,NMPA Key Laboratory for Quality Research and Evaluation of Chemical Drugs,Beijing 102629,China;China Pharmaceutical University)
机构地区:[1]中国食品药品检定研究院化学药品质量研究与评价重点实验室,北京102629 [2]中国药科大学
出 处:《中国药师》2020年第10期2052-2056,共5页China Pharmacist
摘 要:目的:利用近红外(NIR)光谱技术,建立定性和定量通用模型,实现注射用头孢硫脒的快速鉴别与含量、水分检测。方法:采用聚类分析法与模式识别模型对注射用头孢硫脒原料来源进行快速分类鉴别,用偏最小二乘法(PLS)建立注射用头孢硫脒含量和水分的定量分析模型。结果:聚类分析法与模式识别模型对原料来源分类识别结果一致,准确性好。注射用头孢硫脒含量模型的最终优化结果如下:交叉验证相关系数(R2)为60.88,校正集均方根误差(RMSEE)为0.00468,相对分析偏差(RPD)为1.6,偏差为0.0005;水分模型的最终优化结果如下:R2为65.12,RMSEE为0.169,RPD为1.69,偏差为-0.0428。含量和水分模型预测相对偏差分别为0.012%和0.301%。结论:所建定性与定量分析方法可用于注射用头孢硫脒的快速分析,方法简单、准确可靠。Objective:To develop qualitative and quantitative methods to achieve rapid identification and content and moisture detection of cefathiamidine for injection by using near infrared diffused reflectance spectroscopy.Methods:Cluster analysis and identification method were used for the rapid recognition of cefathiamidine for injection.The quantitative model for the content and moisture were established by means of PLS.Results:The results of cluster analysis and identification model were consistent and accurate.The final optimized results of API content PLS model were R2=60.88,RMSEE=0.00468,RPD=1.6 and bias=0.0005,while the final optimized results of moisture PLS method were R2=65.12,RMSEE=0.169,RPD=1.69 and bias=-0.0428.The relative deviations predicted by the API content and moisture models were 0.012%and 0.301%,respectively.Conclusion:The established qualitative and quantitative methods are simple,accurate and reliable in the rapid analysis of cefathiamidine for injection.
关 键 词:近红外光谱 聚类分析 因子分析 含量测定 水分测定
分 类 号:R917[医药卫生—药物分析学]
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