Ma Hua, Anderson Carl A
Graduate School of Pharmaceutical Sciences, Duquesne University, Pittsburgh, Pennsylvania 15282, USA.
J Pharm Sci. 2008 Aug;97(8):3305-20. doi: 10.1002/jps.21230.
This study demonstrates the capabilities of NIR imaging as an effective tool for characterization of pharmaceutical powder blends. The powder system used in this small-scale powder blending study consists of acetaminophen (APAP, the model API), microcrystalline cellulose (MCC) and lactose monohydrate. Mixtures of these components were blended for different times for a total of ten time points (ten blending trials). Images collected from multiple locations of the blends were used to generate a qualitative description of the components' blending dynamics and a quantitative determination of both the blending end point and the distribution variability of the components. Multivariate analyses, including pure-component PCA and discriminate PLS, were used to treat the imaging data. A good correlation was observed between imaging results and a UV-Vis monitoring method for determining blend homogeneity. Score images indicated general trends of the distribution of blending constituents for all ten blending trials. The API distribution pattern throughout blending was detected and the API domain size for different blending trials was compared. Blending insights obtained from this study may be transferable to large scale powder blending. Blending process understanding obtained from this study has the potential to facilitate the optimization of blending process control in the future.
本研究证明了近红外成像作为表征药物粉末混合物的有效工具的能力。本小规模粉末混合研究中使用的粉末系统由对乙酰氨基酚(APAP,模型活性成分)、微晶纤维素(MCC)和一水乳糖组成。这些成分的混合物在不同时间进行混合,总共十个时间点(十次混合试验)。从混合物的多个位置收集的图像用于生成成分混合动态的定性描述以及成分混合终点和分布变异性的定量测定。多元分析,包括纯成分主成分分析和判别偏最小二乘法,用于处理成像数据。成像结果与用于确定混合均匀性的紫外-可见监测方法之间观察到良好的相关性。得分图像表明了所有十次混合试验中混合成分分布的总体趋势。检测了整个混合过程中活性成分的分布模式,并比较了不同混合试验中活性成分的域大小。本研究获得的混合见解可能适用于大规模粉末混合。本研究获得的对混合过程的理解有可能在未来促进混合过程控制的优化。