School of Pharmacy, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK.
Norwich Research Park, Quadram Institute Bioscience, Colney Norwich, Norfolk, NR4 7UA, UK.
Pharm Res. 2018 May 31;35(8):151. doi: 10.1007/s11095-018-2432-3.
The filament-based feeding mechanism employed by the majority of fused deposition modelling (FDM) 3D printers dictates that the materials must have very specific mechanical characteristics. Without a suitable mechanical profile, the filament can cause blockages in the printer. The purpose of this study was to develop a method to screen the mechanical properties of pharmaceutically-relevant, hot-melt extruded filaments to predetermine their suitability for FDM.
A texture analyzer was used to simulate the forces a filament is subjected to inside the printer. The texture analyzer produced a force-distance curve referred to as the flexibility profile. Principal Component Analysis and Correlation Analysis statistical methods were then used to compare the flexibility profiles of commercial filaments to in-house made filaments.
Principal component analysis showed clearly separated clustering of filaments that suffer from mechanical defects versus filaments which are suitable for printing. Correlation scores likewise showed significantly greater values with feedable filaments than their mechanically deficient counterparts.
The screening method developed in this study showed, with statistical significance and reproducibility, the ability to predetermine the feedability of extruded filaments into an FDM printer.
大多数熔融沉积建模(FDM)3D 打印机采用基于细丝的送料机构,这就要求材料必须具有非常特定的机械特性。如果没有合适的机械特性,细丝可能会导致打印机堵塞。本研究的目的是开发一种筛选与药物相关的热熔挤出细丝机械性能的方法,以预先确定其是否适合 FDM。
使用质地分析仪模拟细丝在打印机内所受的力。质地分析仪生成一个力-距离曲线,称为柔韧性曲线。然后使用主成分分析和相关分析统计方法将商业细丝和内部制造细丝的柔韧性曲线进行比较。
主成分分析清楚地显示了有机械缺陷的细丝与适合打印的细丝的聚类分离。相关评分同样显示,可进料细丝的评分明显高于机械缺陷细丝。
本研究中开发的筛选方法具有统计学意义和可重复性,能够预先确定挤出细丝在 FDM 打印机中的进料性。