Faculty of Pharmacy, Division of Pharmaceutical Chemistry and Technology, University of Helsinki, P.O. Box 56, Viikinkaari 5E, 00014, Helsinki, Finland.
AAPS PharmSciTech. 2017 Nov;18(8):3198-3207. doi: 10.1208/s12249-017-0778-1. Epub 2017 May 24.
A new dry granulation technique, gas-assisted roller compaction (GARC), was compared with conventional roller compaction (CRC) by manufacturing 34 granulation batches. The process variables studied were roll pressure, roll speed, and sieve size of the conical mill. The main quality attributes measured were granule size and flow characteristics. Within granulations also the real applicability of two particle size analysis techniques, sieve analysis (SA) and fast imaging technique (Flashsizer, FS), was tested. All granules obtained were acceptable. In general, the particle size of GARC granules was slightly larger than that of CRC granules. In addition, the GARC granules had better flowability. For example, the tablet weight variation of GARC granules was close to 2%, indicating good flowing and packing characteristics. The comparison of the two particle size analysis techniques showed that SA was more accurate in determining wide and bimodal size distributions while FS showed narrower and mono-modal distributions. However, both techniques gave good estimates for mean granule sizes. Overall, SA was a time-consuming but accurate technique that provided reliable information for the entire granule size distribution. By contrast, FS oversimplified the shape of the size distribution, but nevertheless yielded acceptable estimates for mean particle size. In general, FS was two to three orders of magnitude faster than SA.
一种新的干法造粒技术,气体辅助辊压(GARC),通过制造 34 个造粒批次与常规辊压(CRC)进行了比较。研究的工艺变量是轧辊压力、轧辊速度和锥形磨的筛网尺寸。测量的主要质量属性是颗粒大小和流动特性。在颗粒中还测试了两种粒径分析技术的实际适用性,即筛析(SA)和快速成像技术(Flashsizer,FS)。所有获得的颗粒都是可接受的。一般来说,GARC 颗粒的粒径略大于 CRC 颗粒的粒径。此外,GARC 颗粒具有更好的流动性。例如,GARC 颗粒的片剂重量变化接近 2%,表明具有良好的流动和填充特性。两种粒径分析技术的比较表明,SA 在确定宽和双峰粒径分布方面更准确,而 FS 则显示出更窄和单峰分布。然而,这两种技术都能很好地估计平均颗粒尺寸。总的来说,SA 是一种耗时但准确的技术,为整个颗粒粒径分布提供了可靠的信息。相比之下,FS 过于简化了粒径分布的形状,但仍然能够对平均粒径进行可接受的估计。一般来说,FS 比 SA 快两到三个数量级。