An important challenge in the design and analysis of event-related or single-trial functional magnetic resonance imaging (fMRI) experiments is to optimize statistical efficiency, i.e., the accuracy with which the event-related hemodynamic response to different stimuli can be estimated for a given am
Experimental design for the optimization of lipid nanoparticles
β Scribed by J. Zhang; Y. Fan; E. Smith
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 192 KB
- Volume
- 98
- Category
- Article
- ISSN
- 0022-3549
No coin nor oath required. For personal study only.
β¦ Synopsis
Solid lipid nanoparticles (SLN) have been extensively investigated as a promising drug delivery system for controlling the release of therapeutic agents. Currently, there are many manufacturing methods available for SLN, including the high pressure homogenization method and the microemulsion technique. In addition, the solvent diffusion method has been discussed as an alternative technique in the literature, and has attracted great interest due to its simplicity and ease of handling. In order to gain a deeper understanding of this method, a statistical central composite design was applied in this study to examine how the physicochemical properties of the SLN were influenced by the variation of process parameters, including injected solvent, lipid concentration, surfactant concentration, temperature, and stirring speed. Our study showed that lipid concentration and temperature seemed to be the crucial parameters for the particle size of the monostearin SLN prepared by the solvent diffusion method. However, neither of these factors had a significant quadratic relationship with the zeta potential.
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