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

被引:6
|
作者
Fayed, Mohamed H. [1 ]
Alalaiwe, Ahmed [2 ]
Almalki, Ziyad S. [3 ]
Helal, Doaa A. [1 ]
机构
[1] Fayoum Univ, Fac Pharm, Dept Pharmaceut, Al Fayyum 63514, Egypt
[2] Prince Sattam Bin Abdulaziz Univ, Coll Pharm, Dept Pharmaceut, Al Kharj 11942, Saudi Arabia
[3] Prince Sattam Bin Abdulaziz Univ, Coll Pharm, Dept Clin Pharm, Al Kharj 11942, Saudi Arabia
关键词
green fluidized bed granulation; design space; quality-by-design; design-of-experiment; granules and tablets; CRITICAL QUALITY ATTRIBUTES; HIGH-SHEAR; WET GRANULATION; GRANULES; TABLETS; DRUG; FLOWABILITY; PARAMETERS; LUBRICANTS; BREAKAGE;
D O I
10.3390/pharmaceutics14071471
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
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(2) full-factorial design was performed to explore the effect of water amount (X-1; 1-6% w/w) and spray rate (X-2; 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-1 and X-2 significantly affect (p <= 0.05) the CQAs of granules and tablets. Particularly, X-1 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-1 and X-2 at high (5.69% w/w) and low (2 g/min) levels, respectively, demonstrated the optimum operating conditions. By optimizing X-1 and X-2, 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.
引用
收藏
页数:17
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