CAJ | 학술논문

以不同厂家阿莫西林胶囊及其内容物近红外( Near infrared, NIR)光谱为例,寻找评价分段直接标准化算法( Piecewise direct standardization, PDS)进行光谱校正是否成功的量化指标。本研究共涉及76批阿莫西林胶囊样品,其中54批用于建立胶囊剂的定量模型。通过聚类分析,所有胶囊的NIR光谱分成5类,每类视为一个均质样本；分别计算每个均质样本的平均光谱,从该样本中选择10~15张光谱作为PDS校正的目标光谱,对76批阿莫西林胶囊内容物粉末光谱进行校正,利用阿莫西林胶囊定量模型对校正后的光谱进行含量预测；计算校正后的光谱与PDS校正中目标光谱所属均质样本的平均光谱的相似系数,分析其与预测误差的关系。结果表明,校正结果与所选择的目标光谱关系密切。 PDS校正光谱与模型中不同均质样本平均光谱的相似系数( r)越大,通常校正效果越好；当r<99%时,一般可判断PDS校正失败(预测误差>5%)。因此,可以用PDS校正后光谱与校正时使用的目标光谱所属的均质样本的平均光谱的相似系数作为判断PDS校正是否成功的标志。
이불동엄가아막서림효낭급기내용물근홍외( Near infrared, NIR)광보위례,심조평개분단직접표준화산법( Piecewise direct standardization, PDS)진행광보교정시부성공적양화지표。본연구공섭급76비아막서림효낭양품,기중54비용우건립효낭제적정량모형。통과취류분석,소유효낭적NIR광보분성5류,매류시위일개균질양본；분별계산매개균질양본적평균광보,종해양본중선택10~15장광보작위PDS교정적목표광보,대76비아막서림효낭내용물분말광보진행교정,이용아막서림효낭정량모형대교정후적광보진행함량예측；계산교정후적광보여PDS교정중목표광보소속균질양본적평균광보적상사계수,분석기여예측오차적관계。결과표명,교정결과여소선택적목표광보관계밀절。 PDS교정광보여모형중불동균질양본평균광보적상사계수( r)월대,통상교정효과월호；당r<99%시,일반가판단PDS교정실패(예측오차>5%)。인차,가이용PDS교정후광보여교정시사용적목표광보소속적균질양본적평균광보적상사계수작위판단PDS교정시부성공적표지。
The near infrared ( NIR ) spectra of 76 batches of the amoxicillin capsules from different manufacturers and their corresponding content powder without capsules cell were used to find some quantitative indicators to evaluate whether the piecewise direct standardization ( PDS ) algorithm succeeded in NIR quantitative model updating. 54 batches were used to construct the NIR quantitative model for capsule preparation. All the NIR spectra of amoxicillin capsules were divided into five classes by cluster analysis, and each class can be regarded as a homology sample set. The average spectrum for each homology sample set was calculated. Ten to Fifteen spectra were selected from each homology sample set as the corresponding master spectra of the PDS algorithm to correct all the NIR spectra of the amoxicillin content powder respectively. Then the corrected spectra were predicted by the constructed NIR quantitative model for amoxicillin capsules. The prediction error for each corrected powder spectrum, and the correlation coefficient between each corrected powder spectrum and the average spectrum of the corresponding homolog sample set which the PDS master spectra came from, were calculated. Finally, the relationship between the prediction error and its corresponding correlation coefficient were studied. It was found that the correction results correlated closely with the selected master spectra set in PDS algorithm. The bigger the correlation coefficient ( r) , the better the correction results. In general, when r is less than 99%, it can be judged that the PDS correction is failed. At this condition, the prediction error is often more than 5%. Therefore, the correlation coefficient between the corrected spectrum and its corresponding average spectrum of the homology sample set can be used as an indicator to evaluate the efficiency of the PDS correction.