替莫唑胺纳米颗粒的3因子2水平析因设计及优化。

Biomatter Pub Date : 2013-04-01 DOI:10.4161/biom.25102
Aviral Jain, Sanjay K Jain
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引用次数: 29

摘要

本研究的目的是考察3个自变量对乳化溶剂蒸发法制备非聚乙二醇化和聚乙二醇化的替莫唑胺纳米颗粒的综合影响。采用3因子2水平设计,推导多项式二次模型并构建等高线图预测反应。选取的自变量为药物浓度(A)、PLGA/PEG-PLGA浓度(B)、水溶液中PVA浓度(C)和超声时间(D),并对药物包封率(PDE)和粒径(PS)进行评价。采用3(4)因子设计,4个因素(A、B、C和D)在3个水平上,并对所有82种可能的组合进行了实验试验。在本工作中,28组试验被认为是初步试验,结果表明,当药物浓度从2.5 mg增加到5 mg时,药物包裹率增加,但当药物浓度进一步增加(即增加到7.5 mg)时,药物包裹率和粒径没有明显影响。使用3(4)因子设计推导多项式二次模型并构建等高线图来预测响应。绘制等高线图,显示A、B、C和D对PDE和PS的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Formulation and optimization of temozolomide nanoparticles by 3 factor 2 level factorial design.

Formulation and optimization of temozolomide nanoparticles by 3 factor 2 level factorial design.

Formulation and optimization of temozolomide nanoparticles by 3 factor 2 level factorial design.

Formulation and optimization of temozolomide nanoparticles by 3 factor 2 level factorial design.

The aim of this study was to investigate the combined influence of 3 independent variables in the preparation of temozolomide bearing Non-PEGylated and PEGylated nanoparticles by emulsification solvent evaporation method. A 3 factor 2 level design was used to derive a polynomial quadratic model and construct contour plots to predict responses. The independent variables selected were concentration of drug (A), concentration of PLGA/PEG-PLGA (B), PVA concentration in aqueous phase (C) and sonication time (D) and evaluated for percentage drug entrapment (PDE) and particle size (PS). A 3(4) factorial design was used with 4 factors (A, B, C and D) at 3 levels and experimental trials were performed at all 82 possible combinations. In the present work, 28 runs are considered as the preliminary trials revealed that on increasing drug concentration from 2.5 to 5 mg the percent drug entrapment increases, but on further increasing the drug concentration (i.e., to 7.5 mg) no significant effect on the percent drug entrapment and particle size was observed. The 3(4) factorial design was used to derive a polynomial quadratic model and construct contour plots to predict responses. Contour plots were constructed to show the effects of A, B, C and D on the PDE and PS.

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