Hansuld Erin M, Briens Lauren, McCann Joe A B, Sayani Amyn
The Western Fluidization Group, Faculty of Engineering, The University of Western Ontario, London, Ontario, N6A 5B9, Canada.
Int J Pharm. 2009 Aug 13;378(1-2):37-44. doi: 10.1016/j.ijpharm.2009.05.042. Epub 2009 May 27.
Previous work has shown analysis of audible acoustic emissions from high-shear wet granulation has potential as a technique for end-point detection. In this research, audible acoustic emissions (AEs) from three different formulations were studied to further develop this technique as a process analytical technology. Condenser microphones were attached to three different locations on a PMA-10 high-shear granulator (air exhaust, bowl and motor) to target different sound sources. Size, flowability and tablet break load data was collected to support formulator end-point ranges and interpretation of AE analysis. Each formulation had a unique total power spectral density (PSD) profile that was sensitive to granule formation and end-point. Analyzing total PSD in 10 Hz segments identified profiles with reduced run variability and distinct maxima and minima suitable for routine granulation monitoring and end-point control. A partial least squares discriminant analysis method was developed to automate selection of key 10 Hz frequency groups using variable importance to projection. The results support use of frequency refinement as a way forward in the development of acoustic emission analysis for granulation monitoring and end-point control.
先前的研究表明，对高剪切湿法制粒过程中可听声发射进行分析，有潜力成为一种终点检测技术。在本研究中，对三种不同配方的可听声发射进行了研究，以进一步将该技术发展成为一种过程分析技术。将电容式麦克风连接到PMA - 10高剪切制粒机的三个不同位置（排气口、制粒碗和电机），以针对不同的声源。收集了颗粒大小、流动性和片剂破碎负荷数据，以支持配方师确定终点范围并解释声发射分析结果。每种配方都有独特的总功率谱密度（PSD）曲线，该曲线对颗粒形成和终点敏感。在10 Hz频段分析总PSD，可识别出运行变异性降低且具有适合常规制粒监测和终点控制的明显最大值和最小值的曲线。开发了一种偏最小二乘判别分析方法，以利用投影变量重要性自动选择关键的10 Hz频率组。研究结果支持将频率细化作为颗粒监测和声发射分析终点控制发展的前进方向。
