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近红外光谱法对磺胺二甲嘧啶大丸剂剂型物理和化学属性的无损分析评估

Assessment of NIR spectroscopy for nondestructive analysis of physical and chemical attributes of sulfamethazine bolus dosage forms.

作者信息

Tatavarti Aditya S, Fahmy Raafat, Wu Huiquan, Hussain Ajaz S, Marnane William, Bensley Dennis, Hollenbeck Gary, Hoag Stephen W

机构信息

School of Pharmacy, University of Maryland - Baltimore, 20 N. Pine Street, Baltimore, Maryland 21201, USA.

出版信息

AAPS PharmSciTech. 2005 Sep 20;6(1):E91-9. doi: 10.1208/pt060115.

Abstract

The goal of this study was to assess the utility of near infrared (NIR) spectroscopy for the determination of content uniformity, tablet crushing strength (tablet hardness), and dissolution rate in sulfamethazine veterinary bolus dosage forms. A formulation containing sulfamethazine, corn starch, and magnesium stearate was employed. The formulations were wet granulated with a 10% (wt/vol) starch paste in a high shear granulator and dried at 60 degrees C in a convection tray dryer. The tablets were compressed on a Stokes B2 rotary tablet press running at 30 rpm. Each sample was scanned in reflectance mode in the wavelengths of the NIR region. Principal component analysis (PCA) of the NIR tablet spectra and the neat raw materials indicated that the scores of the first 2 principal components were highly correlated with the chemical and physical attributes. Based on the PCA model, the significant wavelengths for sulfamethazine are 1514, (1660-1694), 2000, 2050, 2150, 2175, 2225, and 2275 nm; for corn starch are 1974, 2100, and 2325 nm; and for magnesium stearate are 2325 and 2375 nm. In addition, the loadings show large negative peaks around the water band regions ( approximately 1420 and 1940 nm), indicating that the partial least squares (PLS) models could be affected by product water content. A simple linear regression model was able to predict content uniformity with a correlation coefficient of 0.986 at 1656 nm; the use of a PLS regression model, with 3 factors, had an r (2) of 0.9496 and a standard error of calibration of 0.0316. The PLS validation set had an r (2) of 0.9662 and a standard error of 0.0354. PLS calibration models, based on tablet absorbance data, could successfully predict tablet crushing strength and dissolution in spite of varying active pharmaceutical ingredient (API) levels. Prediction plots based on these PLS models yielded correlation coefficients of 0.84 and 0.92 on independent validation sets for crushing strength and Q(120) (percentage dissolved in 120 minutes), respectively.

摘要

本研究的目的是评估近红外(NIR)光谱法在测定磺胺二甲嘧啶兽用大丸剂剂型的含量均匀度、片剂抗压强度(片剂硬度)和溶出速率方面的实用性。采用了一种含有磺胺二甲嘧啶、玉米淀粉和硬脂酸镁的制剂。将制剂在高剪切制粒机中用10%(重量/体积)的淀粉糊进行湿法制粒,并在对流盘式干燥器中于60℃干燥。片剂在运行速度为30转/分钟的斯托克斯B2旋转式压片机上压制。每个样品在近红外区域的波长下以反射模式进行扫描。对近红外片剂光谱和纯原料进行主成分分析(PCA)表明,前2个主成分的得分与化学和物理属性高度相关。基于PCA模型,磺胺二甲嘧啶的显著波长为1514、(1660 - 1694)、2000、2050、2150、2175、2225和2275 nm;玉米淀粉的显著波长为1974、2100和2325 nm;硬脂酸镁的显著波长为2325和2375 nm。此外,载荷在水带区域(约1420和1940 nm)周围显示出大的负峰,表明偏最小二乘法(PLS)模型可能会受到产品含水量的影响。一个简单的线性回归模型能够在1656 nm处预测含量均匀度,相关系数为0.986;使用具有3个因子的PLS回归模型,r²为0.9496,校准标准误差为0.0316。PLS验证集的r²为0.9662,标准误差为0.0354。基于片剂吸光度数据的PLS校准模型,尽管活性药物成分(API)水平不同,仍能成功预测片剂抗压强度和溶出度。基于这些PLS模型的预测图在独立验证集上对抗压强度和Q(120)(120分钟内溶解的百分比)的相关系数分别为0.84和0.92。

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