Ebube N K, Thosar S S, Roberts R A, Kemper M S, Rubinovitz R, Martin D L, Reier G E, Wheatley T A, Shukla A J
Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee, Memphis 38163, USA.
Pharm Dev Technol. 1999 Jan;4(1):19-26. doi: 10.1080/10837459908984220.
The purpose of this study was to use near-infrared spectroscopy (NIRS) as a nondestructive technique to (a) differentiate three Avicel products (microcrystalline cellulose [MCC] PH-101, PH-102, and PH-200) in powdered form and in compressed tablets with and without 0.5% w/w magnesium stearate as a lubricant; (b) determine the magnesium stearate concentrations in the tablets; and (c) measure hardness of tablets compressed at several compression forces. Diffuse reflectance NIR spectra from Avicel powders and tablets (compression forces ranging from 0.2 to 1.2 tons) were collected and distance scores calculated from the second-derivative spectra were used to distinguish the different Avicel products. A multiple linear regression model was generated to determine magnesium stearate concentrations (from 0.25 to 2% w/w), and partial least squares (PLS) models were generated to predict hardness of tablets. The NIRS technique could distinguish between the three different Avicel products, irrespective of lubricant concentration, in both the powdered form and in the compressed tablets because of the differences in the particle size of the Avicel products. The percent error for predicting the lubricant concentration of tablets ranged from 0.2 to 10% w/w. The maximum percent error of prediction of hardness of tablets compressed at the various compression forces was 8.8% for MCC PH-101, 5.3% for MCC PH-102, and 4.6% for MCC PH-200. The NIRS nondestructive technique can be used to predict the Avicel type in both powdered and tablet forms as well as to predict the lubricant concentration and hardness.
本研究的目的是使用近红外光谱（NIRS）作为一种无损技术，以（a）区分三种粉状及压片形式的微晶纤维素（MCC）产品（PH - 101、PH - 102和PH - 200），其中压片有无0.5% w/w硬脂酸镁作为润滑剂；（b）测定片剂中的硬脂酸镁浓度；以及（c）测量在几种压力下压片的硬度。收集了微晶纤维素粉末和片剂（压力范围为0.2至1.2吨）的漫反射近红外光谱，并使用从二阶导数光谱计算得到的距离分数来区分不同的微晶纤维素产品。生成了一个多元线性回归模型来确定硬脂酸镁浓度（范围为0.25至2% w/w），并生成了偏最小二乘法（PLS）模型来预测片剂的硬度。由于微晶纤维素产品的粒度差异，NIRS技术能够区分三种不同的微晶纤维素产品，无论润滑剂浓度如何，无论是粉状还是压片形式。预测片剂润滑剂浓度的百分比误差范围为0.2至10% w/w。对于在各种压力下压片的硬度预测，MCC PH - 101的最大百分比误差为8.8%，MCC PH - 102为5.3%，MCC PH - 200为4.6%。NIRS无损技术可用于预测粉状和片剂形式的微晶纤维素类型，以及预测润滑剂浓度和硬度。
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