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首页> 外文期刊>Journal of pharmaceutical sciences. >Prediction of tablet hardness based on near infrared spectra of raw mixed powders by chemometrics.
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Prediction of tablet hardness based on near infrared spectra of raw mixed powders by chemometrics.

机译：通过化学计量学基于混合粉末的近红外光谱预测片剂硬度。

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The purpose of this research is to elucidate the effect of lubricant mixing on tablet hardness by near-infrared (NIR) chemometrics as a basic study of process analytical technology. Formulation cellulose (F-C) consisted of sulpyrine (SP), microcrystalline cellulose (MC), and magnesium stearate (MgSt). Formulation lactose/starch (F-L) consisted of SP bulk drug powder, spray-dried lactose (SL), corn starch (CS), and MgSt. First, F-L and F-C without MgSt were mixed in a twin-shell mixer for 60 min. MgSt was added to the mixed powder, and was mixed for various mixing times, after which the mixed powders were compressed by 8-mm diameter punch and die. NIR spectra of raw mixed powders of F-L and F-C were taken using a reflection type of Fourier transform NIR spectra spectrometer, and chemometric analysis was performed using principal component regression (PCR). The tablet hardnesses of F-L and F-C decreased with increasing mixing time. All NIR spectra of the mixed powders of F-L and F-C fluctuated depending on mixing time. In order to predict tablet hardness before tablet compression, NIR spectra of F-L and F-C mixed powders were analyzed and evaluated for hardness by PCR. The minimum standard error of cross-validation values could be realized by using five- and six-principal component models, respectively. In the cases of F-L and F-C, the relationships between the actual and predicted tablet hardnesses showed straight lines, respectively. In the regression vectors of F-L and FC, the peaks related to hydrogen groups of SP, CS, and MC appeared as positive peaks. In contrast, the peaks related to hydrocarbon due to MgSt appeared as negative peaks in the regression vectors. The calibration models to evaluate the tablet hardness were obtained based on NIR spectra of raw mixed powders by PCR. This approach to predicting tablet hardness prior to compression could be used as a routine test to indicate the quality of the final product without spending time and energy to produce samples of questionable quality. (c) 2006 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 95: 1425-1433, 2006.
机译：这项研究的目的是通过近红外（NIR）化学计量学来阐明润滑剂混合对片剂硬度的影响，作为过程分析技术的基础研究。配方纤维素（F-C）由舒比林（SP），微晶纤维素（MC）和硬脂酸镁（MgSt）组成。乳糖/淀粉制剂（F-L）由SP散装药物粉末，喷雾干燥的乳糖（SL），玉米淀粉（CS）和MgSt组成。首先，将不含MgSt的F-L和F-C在双壳混合器中混合60分钟。将MgSt添加到混合粉末中，并混合各种混合时间，然后通过8mm直径的冲头和模头将混合粉末压缩。使用反射型傅立叶变换近红外光谱仪获取F-L和F-C原始混合粉末的近红外光谱，并使用主成分回归（PCR）进行化学分析。 F-L和F-C的片剂硬度随混合时间的增加而降低。 F-L和F-C混合粉末的所有NIR光谱均根据混合时间而波动。为了预测压片前的片剂硬度，分析了F-L和F-C混合粉的NIR光谱，并通过PCR评估了硬度。交叉验证值的最小标准误差可以分别通过使用五个和六个主要成分模型来实现。在F-L和F-C情况下，实际和预测的片剂硬度之间的关系分别显示为直线。在F-L和FC的回归向量中，与SP，CS和MC的氢基相关的峰出现为正峰。相反，归因于MgSt的与烃有关的峰在回归向量中显示为负峰。基于原始混合粉末的NIR光谱，通过PCR获得评估片剂硬度的校准模型。这种在压片前预测片剂硬度的方法可以用作常规测试，以指示最终产品的质量，而无需花费时间和精力来生产质量可疑的样品。 （c）2006 Wiley-Liss，Inc.和美国药剂师协会J Pharm Sci 95：1425-1433，2006。

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