five

Development of pellet coating tehnique using electrostati enhanced fluidized bed

收藏
Mendeley Data2024-01-31 更新2024-06-28 收录
下载链接:
http://doi.nrct.go.th/?page=resolve_doi&resolve_doi=10.14457/CU.the.2007.1841
下载链接
链接失效反馈
官方服务:
资源简介:
Fluidized bed has been used in the pharmaceutical industry for drying and coating products. The present study was aimed to develop pellet coating technique using electrostatic enhanced fluidized bed and investigate the effect of process variables on the coating efficiency and physicochemical properties of coated pellets. The variables studied were types of drug core pellets, film formers and electrical potential applied to the nozzle. Propranolol hydrochloride and diclofenac sodium pellets (50 %w/w) were prepared by extrusion-spheronization technique and used as the core pellets. The core pellets was coated with either the aqueous solution of hydroxypropylmethylcellulose or ethylcellulose aqueous dispersion. Electrical potential was applied to the nozzle at the magnitude of 4 kV. The resulting coated pellets were compared with those obtained from the conventional technique, i.e. fluidized bed with non-applied electrical potential. It was found that the coated pellets remained round shaped and free-flowing. The coating of diclofenac sodium core pellets resulted in homogeneous film regardless of the effect of coating conditions. In all cases, an image analysis showed that the film thickness was significantly influenced by types of drug core pellets and applied electrical potential (p<0.05). However, applying charged droplets to core pellets was not proved to significantly enhanced the coating efficiency (p>0.05) but rather improved its reproducibility. The drug released was primarily controlled by types of film former, although there were some influences from other process variables. The results showed that, no matter how complex the nature of electrostatic fluidized bed coating was, this technique may be useful for pharmaceuticals when process variables are carefully controlled.
创建时间:
2024-01-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作