Department of Pharmacy, Faculty of Science, National University of Singapore, 18 Science Drive 4, Singapore 117543, Republic of Singapore.
Int J Pharm. 2010 Feb 15;386(1-2):138-48. doi: 10.1016/j.ijpharm.2009.11.011. Epub 2009 Nov 13.
This work was aimed at investigating the utility of near infrared (NIR) spectroscopy for simultaneous in-line quantification of drug and excipients in cohesive powder blends in a bin blender. A model formulation containing micronized chlorpheniramine maleate (microCPM), lactose, microcrystalline cellulose (MCC) and magnesium stearate (MgSt) was selected for the blending study. An optical head comprising a sapphire window mounted on the lid of the bin was used to collect in-line NIR spectral data of the powder blends. Validated partial least square (PLS) calibration models were used to quantify each component from the NIR spectra of the blends. Additionally, effects of premixing by sieving and high shear mixing and use of an internal prism fixed within the bin on the mixing performance of each component were studied. The statistical results obtained for PLS calibration models and their validation showed the sensitivity of NIR for accurate quantification of blend components. The blend prepared with high shear premixing and with prism achieved uniformity more rapidly than that with high shear premixing but without prism during blending in a bin blender. Premixing using sieving proved to be inadequate for uniform mixing of the blend components as none of the components except MgSt achieved uniform distribution after the preset blending time when blended in the bin blender. This study demonstrated that by high speed sampling and rapid spectral acquisition, distribution of individual blend components can be assessed with high accuracy during blending. Furthermore, high shear premixing facilitated rapid distribution and uniformity achievement of blend components. This technique may be used to monitor the relative distribution of individual blend components in real time and thus, to assess the performance of a bin blender for mixing of cohesive multi-component powder blends during development and production.
这项工作旨在研究近红外（NIR）光谱技术在桶式混合机中对粘性粉末混合物中药物和赋形剂的同时在线定量分析的应用。选择含有马来酸氯苯那敏（微 CPM）、乳糖、微晶纤维素（MCC）和硬脂酸镁（MgSt）的模型配方进行混合研究。采用安装在桶盖上的蓝宝石窗口光学头收集粉末混合物的在线近红外光谱数据。使用验证的偏最小二乘（PLS）校准模型从混合物的近红外光谱中定量每个成分。此外，还研究了筛网预混合、高剪切混合以及在桶内使用内置棱镜对内部分散性能的影响。PLS 校准模型及其验证的统计结果表明，NIR 对混合物成分的准确定量具有很高的灵敏度。与高剪切预混合但无棱镜的混合物相比，高剪切预混合并带有棱镜的混合物在桶式混合机中混合时更快地达到均匀性。筛分预混合被证明不足以均匀混合混合物成分，因为当在桶式混合机中混合时，除了 MgSt 之外，没有一种成分在预设的混合时间后达到均匀分布。这项研究表明，通过高速采样和快速光谱采集，可以在混合过程中非常准确地评估单个混合物成分的分布情况。此外，高剪切预混合有助于快速分布和均匀性实现混合物成分。该技术可用于实时监测各个混合成分的相对分布情况，从而评估桶式混合机在开发和生产过程中对粘性多成分粉末混合物的混合性能。
