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浙江大学学报(工学版)
浙江大学学报(工学版)  2020, Vol. 54 Issue (2): 374-380    DOI: 10.3785/j.issn.1008-973X.2020.02.019
机械与能源工程     
基于粉体学性质的流化床制粒质量一致性评价方法
赵洁1(),瞿海斌1,*(),田埂2,魏燕定2
1. 浙江大学 药物信息学研究所，浙江 杭州 310058
2. 浙江大学 浙江省先进制造技术重点研究实验室，浙江 杭州 310027
Quality consistency evaluation method for granules in fluidized bed granulation based on powder properties
Jie ZHAO1(),Hai-bin QU1,*(),Geng TIAN2,Yan-ding WEI2
1. Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China
2. Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, Zhejiang University, Hangzhou 310027, China
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摘要：

为了评价流化床脉冲喷雾制粒（PSFBG）产品的质量，采用粉体学评价方法表征颗粒的堆积特性、可压性、流动性等物理属性. 构建由休止角、空隙率、粒径等12个指标构成的物理指纹谱. 基于物理指纹谱对PSFBG产品进行质量一致性评价，并通过构建参数指数、参数轮廓指数和良好可压性指数分析颗粒的压缩特性；运用多变量数据分析对不同批次颗粒的质量属性进行评价. 结果表明，所建立的物理指纹谱不仅可以反映不同制备工艺所获得颗粒的粉体学性质的异同，还能辅助判断颗粒压缩特性，结合多元统计分析方法在多个指标互相关联的情况下分析它们之间的规律. 物理指纹谱是评价产品粉体学性质的有效工具，为PSFBG产品质量一致性的综合评价提供思路.
关键词： 流化床;  脉冲喷雾;  物理属性;  物理指纹谱;  压缩特性;  多变量数据分析    
Abstract:

The physical properties of stackability, compressibility and flowability were comprehensively characterized by micromeritics evaluation method, in order to conduct a quality evaluation of granules produced by pulsed-spray fluid-bed granulation (PSFBG). Physical fingerprint were constructed with twelve indexes, such as angle of repose, porosity and particle size, to evaluate the quality consistence of PSFBG products. The parameter index, the parameter profile index and the good compressibility index were established to study the compressibility of particles. Multivariate data analysis was used to evaluate the quality attributes of different batches of granules. Results show that the physical fingerprint can not only reflect the similarities and differences of the properties of granules obtained by different granulation methods, but also assist in judging the compression characteristics of particles. Combined with the method of multivariate statistical analysis, the physical fingerprint can be used to analyze the regularity between multiple indicators when they are related to each other. Physical fingerprint spectroscopy is an effective tool for evaluating the properties of granules, which provides new insights into the quality consistence evaluation of PSFBG products.
Key words: fluid bed    pulsed spray    physical properties    physical fingerprint    compressibility    multivariate data analysis
收稿日期: 2018-12-30 出版日期: 2020-03-10
CLC:  TP 273  
基金资助: 国家科技重大专项资助项目（2018ZX09201011-002）
通讯作者: 瞿海斌     E-mail: zhaojie_1021@zju.edu.cn;quhb@zju.edu.cn
作者简介: 赵洁（1989—），女，博士生，从事药品生产全程质量控制方法研究. orcid.org/0000-0003-0465-1030. E-mail： zhaojie_1021@zju.edu.cn
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赵洁
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引用本文:

赵洁,瞿海斌,田埂,魏燕定. 基于粉体学性质的流化床制粒质量一致性评价方法[J]. 浙江大学学报(工学版), 2020, 54(2): 374-380.

Jie ZHAO,Hai-bin QU,Geng TIAN,Yan-ding WEI. Quality consistency evaluation method for granules in fluidized bed granulation based on powder properties. Journal of ZheJiang University (Engineering Science), 2020, 54(2): 374-380.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2020.02.019    或    http://www.zjujournals.com/eng/CN/Y2020/V54/I2/374

图 1  流化床脉冲喷雾制粒实验设备示意图
批次 工艺参数
θ/°C Hw/% V/（r?min?1） A/MPa T/min c/%
1 60 70 30 0.16 3 70
2 60 50 20 0.12 1 30
3 65 60 20 0.16 3 30
4 55 60 30 0.12 1 70
5 65 50 25 0.12 3 70
6 55 70 25 0.16 1 30
7 55 50 30 0.14 3 30
8 65 50 30 0.16 1 50
9 55 70 20 0.12 3 50
10 60 60 25 0.14 2 50
11 60 60 25 0.14 2 50
12 60 60 25 0.14 2 50
表 1  不同批次流化床脉冲喷雾制粒工艺参数
一级指标 二级指标 符号 单位
堆积特性 松密密度 ρb g/mL
振实密度 ρt g/mL
可压性 空隙率 ε %
卡尔指数 I ?
流动性 豪斯纳比率 H ?
休止角 α °
稳定性 水的质量分数 w %
均一性 颗粒累积分布为10%的粒径 d10 μm
颗粒累积分布为50%的粒径 d50 μm
颗粒累积分布为90%的粒径 d90 μm
粒径分布宽度 S ?
粒径范围 W μm
表 2  物理指纹谱的构成指标
图 2  不同批次流化床脉冲喷雾制粒产品的物理指纹谱
一级指标 二级指标 单位 实验值 转化值 属性均值
堆积特性 ρb g/mL 0.30 10.00 10.00
ρt g/mL 0.42 10.00 10.00
可压性 ε % 29.44 6.97 6.97
I ? 0.29 6.97 6.97
流动性 H ? 1.42 6.72 5.00
α ° 47.02 3.28 5.00
稳定性 w % 5.46 3.47 3.47
均一性 d10 μm 84.62 0.00 2.00
d50 μm 121.66 0.00 2.00
d90 μm 219.27 0.00 2.00
S ? 1.11 10.00 2.00
W μm 134.65 0.00 2.00
表 3  批次3颗粒物理指纹谱相关物理质量指标
图 3  不同批次流化床脉冲喷雾制粒产品的物理指纹谱叠加图
批次 批次
1 2 3 4 5 6 7 8 9 10 11 12
1 1 ? ? ? ? ? ? ? ? ? ? ?
2 0.759 9 1 ? ? ? ? ? ? ? ? ? ?
3 0.391 0 0.550 1 1 ? ? ? ? ? ? ? ? ?
4 0.813 6 0.926 7 0.578 0 1 ? ? ? ? ? ? ? ?
5 0.858 7 0.624 2 0.491 0 0.805 5 1 ? ? ? ? ? ? ?
6 0.395 4 0.657 4 0.967 1 0.632 6 0.443 5 1 ? ? ? ? ? ?
7 0.745 6 0.639 7 0.589 6 0.828 6 0.964 9 0.564 4 1 ? ? ? ? ?
8 0.396 9 0.666 1 0.809 3 0.566 6 0.348 6 0.921 2 0.462 8 1 ? ? ? ?
9 0.736 6 0.885 9 0.793 8 0.946 0 0.787 1 0.833 6 0.851 0 0.750 2 1 ? ? ?
10 0.824 9 0.599 0 0.498 3 0.816 3 0.988 3 0.440 7 0.964 1 0.315 4 0.793 9 1 ? ?
11 0.860 3 0.645 3 0.448 4 0.833 3 0.980 3 0.434 0 0.959 1 0.384 6 0.801 1 0.979 4 1 ?
12 0.827 0 0.654 4 0.358 8 0.828 3 0.939 2 0.382 6 0.934 4 0.386 7 0.772 8 0.933 4 0.983 2 1
表 4  不同批次流化床脉冲喷雾制粒产品的夹角余弦
批次 IP/% IPP IGC
　1）注：*表示数值在可接受范围内
1 33.33 4.78 4.56
2 50.00 4.85 4.63
3 50.00 4.78 4.57
4 50.00 4.84 4.62
5 66.67*1） 6.17* 5.89*
6 25.00 3.90 3.72
7 75.00* 6.19* 5.91*
8 25.00 2.64 2.52
9 50.00 5.03 4.81
10 75.00* 7.22* 6.90*
11 75.00* 6.47* 6.18*
12 50.00* 5.94* 5.67*
表 5  不同批次流化床脉冲喷雾制粒产品的压缩特性参数
图 4  12批次流化床脉冲喷雾制粒产品的主成分得分图
图 5  12批次流化床脉冲喷雾制粒产品的载荷图
图 6  颗粒不同物理属性对P1和P2的贡献率
1 LIM L J J, LIM E W C Mixing and segregation behaviors of a binary mixture in a pulsating fluidized bed[J]. Powder Technology, 2019, 345: 311- 328
doi: 10.1016/j.powtec.2019.01.026
2 PENN A, BOYCE C M, CONZELMANN N, et al Real-time magnetic resonance imaging of fluidized beds with internals[J]. Chemical Engineering Science, 2019, 198: 117- 123
doi: 10.1016/j.ces.2018.12.041
3 N?RV?NEN T, LIPSANEN T, ANTIKAINEN O, et al Controlling granule size by granulation liquid feed pulsing[J]. International Journal of Pharmaceutics, 2008, 357 (1): 132- 138
4 LIU H, WANG K, SCHLINDWEIN W, et al Using the Box-Behnken experimental design to optimise operating parameters in pulsed spray fluidised bed granulation[J]. International Journal of Pharmaceutics, 2013, 448 (2): 329- 338
doi: 10.1016/j.ijpharm.2013.03.057
5 EHLERS H, LIU A, R?IKK?NEN H, et al Granule size control and targeting in pulsed spray fluid bed granulation[J]. International Journal of Pharmaceutics, 2009, 377 (1): 9- 15
6 MADERUELO C, ZARZUELO A, LANAO J M Critical factors in the release of drugs from sustained release hydrophilic matrices[J]. Journal of Controlled Release, 2011, 154 (1): 2- 19
doi: 10.1016/j.jconrel.2011.04.002
7 刘涛, 付春梅, 唐玉, 等 不同干燥方式对桑枝提取物物理指纹图谱及其总黄酮含量的影响[J]. 中国实验方剂学杂志, 2018, 24 (20): 65- 69
LIU Tao, FU Chun-mei, TANG Yu, et al Effect of different drying methods on physical fingerprint and total flavonoids content of Mori Ramulus extract[J]. Chinese Journal of Experimental Traditional Medical Formulae, 2018, 24 (20): 65- 69
8 SU?é-NEGRE J M, PéREZLOZANO P, MI?ARRO M, et al Application of the SeDeM diagram and a new mathematical equation in the design of direct compression tablet formulation[J]. European Journal of Pharmaceutics and Biopharmaceutics, 2008, 69 (3): 1029- 1039
doi: 10.1016/j.ejpb.2008.01.020
9 SU?é-NEGRE J M, PéREZLOZANO P, ROIG M, et al Optimization of parameters of the SeDeM diagram expert system: Hausner index (IH) and relative humidity (%RH)[J]. European Journal of Pharmaceutics and Biopharmaceutics, 2011, 79 (2): 464- 472
doi: 10.1016/j.ejpb.2011.04.002
10 张毅, 徐冰, 孙飞, 等 中药提取物粉末物理指纹谱研究及应用[J]. 中国中药杂志, 2016, 41 (12): 2221- 2227
ZHANG Yi, XU Bing, SUN Fei, et al Physical fingerprint for quality control of traditional Chinese medicine extract powders[J]. China Journal of Chinese Materia Medica, 2016, 41 (12): 2221- 2227
11 崔向龙, 徐冰, 张毅, 等 质量源于设计在银杏叶片制粒工艺中的应用(Ⅰ): 颗粒粉体学性质综合评价[J]. 中国中药杂志, 2017, (6): 1037- 1042
CUI Xiang-long, XU Bing, ZHANG Yi, et al Application of quality by design in granulation process for ginkgo leaf tablet(I): comprehensive characterization of granule properties[J]. China Journal of Chinese Materia Medica, 2017, (6): 1037- 1042
12 NOFRERIAS I, NARDI A, SU?éPOU M, et al Comparison between microcrystalline celluloses of different grades made by four manufacturers using the SeDeM diagram expert system as a pharmaceutical characterization tool[J]. Powder Technology, 2019, 342: 780- 788
doi: 10.1016/j.powtec.2018.10.048
13 SAURí J, MILLáN D, SU?éNEGRE J M, et al The use of the SeDeM diagram expert system for the formulation of Captopril SR matrix tablets by direct compression[J]. International Journal of Pharmaceutics, 2014, 461 (1): 38- 45
14 GALDóN E, CASAS M, GAYANGO M, et al First study of the evolution of the SeDeM expert system parameters based on percolation theory: monitoring of their critical behavior[J]. European Journal of Pharmaceutics and Biopharmaceutics, 2016, 109: 158- 164
doi: 10.1016/j.ejpb.2016.10.004
15 LUO G, XU B, ZHANG Y, et al Scale-up of a high shear wet granulation process using a nucleation regime map approach[J]. Particuology, 2017, 31: 87- 94
doi: 10.1016/j.partic.2016.04.007
16 李延年, 伍振峰, 尚悦, 等 基于浸膏物理指纹谱评价不同干燥方式对浸膏粉体性质的影响[J]. 中草药, 2018, (10): 2372- 2377
LI Yan-nian, WU Zhen-feng, SHANG Yue, et al Effect on different drying methods on powder properties of extraction paste based on physical fingerprint of extract[J]. Chinese Traditional and Herbal Drugs, 2018, (10): 2372- 2377
doi: 10.7501/j.issn.0253-2670.2018.10.019
17 DAI S, XU B, SHI G, et al SeDeM expert system for directly compressed tablet formulation: a review and new perspectives[J]. Powder Technology, 2019, 342: 517- 527
doi: 10.1016/j.powtec.2018.10.027
18 SCHOLTZ J C, STEENEKAMP J H, HAMMAN J H, et al The SeDeM expert diagram system: its performance and predictability in direct compressible formulations containing novel excipients and different types of active ingredients[J]. Powder Technology, 2017, 312: 222- 236
doi: 10.1016/j.powtec.2017.02.019
19 ZHAO J, LI W, QU H, et al Application of definitive screening design to quantify the effects of process parameters on key granule characteristics and optimize operating parameters in pulsed-spray fluid-bed granulation[J]. Particuology, 2019, 43: 56- 65
doi: 10.1016/j.partic.2018.03.007
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