Sensum, Computer Vision Systems, Tehnoloski Park 21, 1000 Ljubljana, Slovenia.
Eur J Pharm Sci. 2010 Sep 11;41(1):156-62. doi: 10.1016/j.ejps.2010.06.001. Epub 2010 Jun 9.
Pellet coating processes are usually driven by fairly well optimized procedures, while coating suspension sprayed on pellets and adverse effects, such as agglomeration, can not be seen during coating process and are only detected at the very end of the process, when it is too late for any adjustments of the coating process. The aim of this study is to evaluate digital visual imaging as process analytical technology (PAT) tool for fluid-bed pellet coating processes. The method accurately estimates spherical diameter, coating thickness and adverse agglomeration of pellets by contactless measurements, classification and analysis of pellets based on digital imaging. Calibration and thorough assessment of the accuracy, precision, stability and speed of the proposed method was performed with high precision bearing balls. The obtained results on real pellets indicated that the method is feasible for real-time controlling, understanding, designing and optimizing of fluid-bed pellet coating processes according to PAT guidance.
丸剂包衣过程通常由相当优化的程序驱动,而喷涂在丸剂上的包衣悬浮液在包衣过程中看不到不良影响,例如团聚,只能在过程的最后阶段检测到,此时调整包衣过程已经为时过晚。本研究的目的是评估数字视觉成像作为流化床丸剂包衣过程的分析技术(PAT)工具。该方法通过基于数字成像的非接触式测量、分类和分析丸剂,准确估计丸剂的球形直径、涂层厚度和不良团聚。使用高精度轴承球对所提出方法的准确性、精密度、稳定性和速度进行了校准和彻底评估。在实际丸剂上获得的结果表明,该方法可根据 PAT 指导实时控制、理解、设计和优化流化床丸剂包衣过程。