Suppr超能文献

使用实验设计对难溶性非诺贝特制粒中绿色流化床制粒工艺进行优化的设计空间方法

Design Space Approach for the Optimization of Green Fluidized Bed Granulation Process in the Granulation of a Poorly Water-Soluble Fenofibrate Using Design of Experiment.

作者信息

Fayed Mohamed H, Alalaiwe Ahmed, Almalki Ziyad S, Helal Doaa A

机构信息

Department of Pharmaceutics, Faculty of Pharmacy, Fayoum University, Fayoum 63514, Egypt.

Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia.

出版信息

Pharmaceutics. 2022 Jul 15;14(7):1471. doi: 10.3390/pharmaceutics14071471.

Abstract

In the pharmaceutical industry, the systematic optimization of process variables using a quality-by-design (QbD) approach is highly precise, economic and ensures product quality. The current research presents the implementation of a design-of-experiment (DoE) driven QbD approach for the optimization of key process variables of the green fluidized bed granulation (GFBG) process. A 3 full-factorial design was performed to explore the effect of water amount (X; 1-6% /) and spray rate (X; 2-8 g/min) as key process variables on critical quality attributes (CQAs) of granules and tablets. Regression analysis have demonstrated that changing the levels of X and X significantly affect ( ≤ 0.05) the CQAs of granules and tablets. Particularly, X was found to have the pronounced effect on the CQAs. The GFBG process was optimized, and a design space (DS) was built using numerical optimization. It was found that X and X at high (5.69% /) and low (2 g/min) levels, respectively, demonstrated the optimum operating conditions. By optimizing X and X, GFBG could enhance the disintegration and dissolution of tablets containing a poorly water-soluble drug. The prediction error values of dependent responses were less than 5% that confirm validity, robustness and accuracy of the generated DS in optimization of GFBG.

摘要

在制药行业,采用质量源于设计(QbD)方法对工艺变量进行系统优化具有高精度、经济性,并能确保产品质量。当前研究展示了一种基于实验设计(DoE)的QbD方法在绿色流化床制粒(GFBG)工艺关键工艺变量优化中的应用。进行了三因素全因子设计,以探究水量(X₁;1 - 6% /)和喷雾速率(X₂;2 - 8 g/min)作为关键工艺变量对颗粒剂和片剂关键质量属性(CQAs)的影响。回归分析表明,改变X₁和X₂的水平会显著影响(p ≤ 0.05)颗粒剂和片剂的CQAs。特别是,发现X₁对CQAs有显著影响。对GFBG工艺进行了优化,并通过数值优化构建了设计空间(DS)。结果发现,分别在高(5.69% /)和低(2 g/min)水平的X₁和X₂展示了最佳操作条件。通过优化X₁和X₂,GFBG可以提高含难溶性药物片剂的崩解和溶出度。相关响应的预测误差值小于5%,这证实了所生成的DS在GFBG优化中的有效性、稳健性和准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/71cb/9316798/05755bbc39d7/pharmaceutics-14-01471-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验