Comparison of novel granulated pellet-containing tablets and traditional pellet-containing tablets by artificial neural networks

Comparison of novel granulated pellet-containing tablets and traditional pellet-containing tablets by artificial neural networks
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DOI:
10.3109/10837450.2014.910809
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发表时间:
2015-07
影响因子:
3.4
通讯作者:
Ying Huang;Qinghe Yao;Chune Zhu;Xuan Zhang;Lingzhen Qin;Qin-ruo Wang;Xin Pan;Chuanbin Wu
Ying Huang;Qinghe Yao;Chune Zhu;Xuan Zhang;Lingzhen Qin;Qin-ruo Wang;Xin Pan;Chuanbin Wu
中科院分区:
医学4区
文献类型:
--
作者:
Ying Huang;Qinghe Yao;Chune Zhu;Xuan Zhang;Lingzhen Qin;Qin-ruo Wang;Xin Pan;Chuanbin Wu

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Abstract 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 (f2) 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.