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通过析因设计对瑞格列奈速释片进行处方设计、研发及优化。

Formulation, development, and optimization of immediate release nateglinide tablets by factorial design.

作者信息

Pani N R, Nath L K, Bhunia B

机构信息

Department of Pharmaceutics, Gayatri College of Pharmacy, Sambalpur, Orissa, India.

出版信息

Drug Discov Ther. 2010 Dec;4(6):453-8.

PMID:22491311
Abstract

In the present study, selection of superdisintegrants among sodium starch glycolate, cross povidone, Starch-1500 and cross carmellose sodium (CCS) was carried out for development of immediate release nateglinide tablets (NTG). A 3(2) full factorial design was used to investigate the influence of two independent variables, i.e., amount of selected superdisintegrants and hardness of the tablets, on two dependent variables, i.e., disintegration time and percentage of drug release at 30 min (DR(0.5h)). The results revealed that CCS was the best superdisintegrant for the development of immediate release tablets of NTG. The sign of the coefficient of the polynomial equation signified that the disintegration time was decreased and DR(0.5h) was increased by decreasing the hardness of the tablets as well as by increasing the concentration of CCS in the tablets. A checkpoint batch of the tablets was prepared by changing the value of independent variables within the range used in the preparation of factorial batches of tablets to check the validity of the evolved optimized mathematical model. Stability studies of optimized formulations indicated that there was no significant change in the physical parameters, disintegration time, and percentage of drug release of tablets. The systematic formulation approach helped to understand the effect of formulation processing variables.

摘要

在本研究中,为开发那格列奈速释片(NTG),对羟丙甲纤维素、交联聚维酮、淀粉-1500和交联羧甲基纤维素钠(CCS)进行了超级崩解剂的筛选。采用3(2)全因子设计来研究两个自变量,即所选超级崩解剂的用量和片剂硬度,对两个因变量,即崩解时间和30分钟时的药物释放百分比(DR(0.5h))的影响。结果表明,CCS是开发那格列奈速释片的最佳超级崩解剂。多项式方程系数的符号表明,通过降低片剂硬度以及增加片剂中CCS的浓度,崩解时间缩短,DR(0.5h)增加。通过在制备析因批次片剂所用范围内改变自变量的值,制备了一批检验批次的片剂,以检验所建立的优化数学模型的有效性。优化制剂的稳定性研究表明,片剂的物理参数、崩解时间和药物释放百分比没有显著变化。系统的制剂方法有助于理解制剂工艺变量的影响。

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