Comparison of novel granulated pellet-containing tablets and traditional pellet-containing tablets by artificial neural networks. (September 2015)

• Record Type: Journal Article
• Authors: Huang, Ying; Yao, Qinghe; Zhu, Chune; Zhang, Xuan; Qin, Lingzhen; Wang, Qinruo; Pan, Xin; Wu, Chuanbin
• Is Part Of: Pharmaceutical development and technology. Volume 20:Number 6(2015)
• Page Start: 670
• Page End: 675
• Publication Date: 2015-09
• Subjects: Drug delivery systems -- Periodicals; Pharmaceutical technology -- Periodicals; Drugs -- Administration -- Research -- Periodicals; Drug Delivery Systems -- Periodicals; Pharmaceutical Preparations -- Periodicals; Technology, Pharmaceutical -- Periodicals; 615
• Languages: English
• ISSNs: 1083-7450

Abstract

<abstract> <title>Abstract</title> <p>Novel granulated pellets technique was adopted to prepare granulated pellet-containing tablets (GPCT). GPCT and traditional pellet-containing tablets (PCT) were prepared according to 29 formulations devised by the Design Expert 7.0, with doxycycline hydrochloride as model drug, blends of Eudragit FS 30D and Eudragit L 30D-55 as coating materials, for the comparison study to confirm the superiority of GPCT during compaction. Eudragit FS 30D content, coating weight gain, tablet hardness and pellet size were chosen as influential factors to investigate the properties and drug release behavior of tablets. The correlation coefficients between the experimental values and the predicted values by artificial neural networks (ANNs) for PCT and GPCT were 0.9474 and 0.9843, respectively, indicating the excellent prediction of ANNs. The similarity factors (<italic>f</italic>₂) for release profiles of GPCT and the corresponding original pellets were higher than those of PCT, suggesting that the excipient layer of granulated pellets absorbed the compressing force and protected the integrity of coating films during compaction.</p> </abstract>