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Quality by design: Understanding the product variability of a self-nanoemulsified drug delivery system of cyclosporine A
Faculty
Pharmacy
Year:
2007
Type of Publication:
Article
Pages:
2409-2423
Authors:
Zidan, Ahmed S, Khan, Mansoor A, Sammour, Omaima A, Megrab, Nagia A, Hammad, Muhammad A, Habib, Mohamed J
DOI:
10.1002/jps.20824
Journal:
JOURNAL OF PHARMACEUTICAL SCIENCES JOHN WILEY \& SONS INC
Volume:
96
Research Area:
Pharmacology \& Pharmacy; Chemistry
ISSN
ISI:000249183800019
Keywords :
cyclosporine, self-nanoemulsification, variability, permeability and near, infrared
Abstract:
The objective of this work was to understand the product variability due to size and other characteristics of the SNEDDS by utilizing near infrared (NIR) and chemometric analysis, as well as several other well-known procedures. Pseudo-ternary phase diagrams were constructed to identify the efficient self-emulsification region using CyA solutions in sweet orange oil (oily phase), Emulphor EL-620 (surfactant), and Capmul MCM-C8 (cosurfactant). The formulated SNEDDS were characterized by droplet size, turbidity, zeta potential, and Fourier transform infrared (FTIR) analysis. Drug release studies were performed by dissolution in conjunction with turbidimetry. Permeability studies were performed in a Franz diffusion cell assembly. The results indicated an optimum surfactant to cosurfactant ratio of 2:1. Above this ratio, the resultant nanoemulsions had a particle size of 10 nm and turbidity of 10 nephlometric units (NTU). All the prepared systems were positively charged. The FTIR spectra and the DSC thermograms obtained showed no incompatibility between the SNEDDS ingredients. Turbidity time profiles revealed three distinctive regions: lag phase, plateau, and pseudolinear phase. Emulsification rate was obtained from the corrected slope of the pseudolinear phase of the profile. Permeability data indicated that the product variability is more with smaller droplet size. The size of the droplets showed good correlation with NIR spectral data by partial least square (PLS) regression plots. In conclusion, this study demonstrated the ability to understand the impact of nanodroplets size on the SNEDDS variability by different product analyzing tools. (c) 2007 Wiley-Liss, Inc.
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