陈如心, 韩晓璐, 刘伯石, 刘原兵, 刘婷, 王增明, 刘中成, 郑爱萍. 3D打印氯氮平分散片工艺优化及个性化剂量模型建立J. 药学学报, 2021,56(4): 1155-1162. doi: 10.16438/j.0513-4870.2020-1678
引用本文: 陈如心, 韩晓璐, 刘伯石, 刘原兵, 刘婷, 王增明, 刘中成, 郑爱萍. 3D打印氯氮平分散片工艺优化及个性化剂量模型建立J. 药学学报, 2021,56(4): 1155-1162. doi: 10.16438/j.0513-4870.2020-1678
CHEN Ru-xin, HAN Xiao-lu, LIU Bo-shi, LIU Yuan-bing, LIU Ting, WANG Zeng-ming, LIU Zhong-cheng, ZHENG Ai-ping. Optimization of process parameters of 3D printed clozapine dispersive tablets and establishment of personalized dose modelJ. Acta Pharmaceutica Sinica, 2021,56(4): 1155-1162. doi: 10.16438/j.0513-4870.2020-1678
Citation: CHEN Ru-xin, HAN Xiao-lu, LIU Bo-shi, LIU Yuan-bing, LIU Ting, WANG Zeng-ming, LIU Zhong-cheng, ZHENG Ai-ping. Optimization of process parameters of 3D printed clozapine dispersive tablets and establishment of personalized dose modelJ. Acta Pharmaceutica Sinica, 2021,56(4): 1155-1162. doi: 10.16438/j.0513-4870.2020-1678

3D打印氯氮平分散片工艺优化及个性化剂量模型建立

Optimization of process parameters of 3D printed clozapine dispersive tablets and establishment of personalized dose model

  • 摘要: 本研究旨在以全因子实验设计(design of experiment,DoE)为核心,建立黏结剂喷射型3D打印的关键工艺设计空间,通过Minitab软件设计了三因素两水平三个中心点的实验方案,分析显著影响片剂质量属性的因子及因子之间的交互作用。其次,利用计算机辅助软件(computer aided drafting,CAD)在固定模型半径与高度比值(r/h=1.25)的前提下,对模型体积大小进行调整,建立模型体积与剂量的线性回归方程,从而实现药物剂量的灵活可控。最终确定工艺参数:喷墨量为12、层厚为150 μm、打印头在X轴方向运行速度为635 mm·s-1。含药量(y)与模型体积(x)的回归方程:y=0.062 x-0.582 7(R2=0.999 9),线性关系良好。结果说明,通过DoE获得了稳健可行的工艺参数且实现了不同剂量片剂的精确制备,重现性良好。

     

    Abstract: This study aims to establish the design space of the key processes for drop-on-powder 3D printing based on design of experiment (DoE). By utilizing Minitab, an experimental scheme with three factors, two levels and three center points was designed to analyze the factors that significantly affected the tablet quality attributes. Furthermore, the factor interactions were analyzed using Minitab. subsequently, the computer aided drafting (CAD) software was used to adjust the model volume with fixed radius/height ratio (r/h=1.25) and establish a linear regression equation between model volume and dose. As a result, the drug dose could be controlled in a flexible manner. The finally determined process parameters were:ink-jet level is 12, layer thickness is 150 μm, and the X-axis printing head speed of 635 mm·s-1. Regression equation between drug content (y) and model volume (x) was y=0.062 x-0.582 7 (R2=0.999 9) showing good linear relationship. This indicated that robust and feasible process parameters were obtained through DoE, and the preparation of personalized-dose tablets was realized with good reproducibility.

     

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