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Using a modified shepards method for optimization of a nanoparticulate cyclosporine a formulation prepared by a static mixer technique

Using a modified shepards method for optimization of a nanoparticulate cyclosporine a formulation prepared by a static mixer technique

Douroumis, Dionysios ORCID: 0000-0002-3782-0091, Scheler, Stefan and Fahr, Alfred (2008) Using a modified shepards method for optimization of a nanoparticulate cyclosporine a formulation prepared by a static mixer technique. Journal of Pharmaceutical Sciences, 97 (2). pp. 919-930. ISSN 0022-3549 1520-6017 (online) (doi:https://doi.org/10.1002/jps.21001)

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Abstract

An innovative methodology has been used for the formulation development of Cyclosporine A (CyA) nanoparticles. In the present study the static mixer technique, which is a novel method for producing nanoparticles, was employed. The formulation optimum was calculated by the modified Shepard's method (MSM), an advanced data analysis technique not adopted so far in pharmaceutical applications. Controlled precipitation was achieved injecting the organic CyA solution rapidly into an aqueous protective solution by means of a static mixer. Furthermore the computer based MSM was implemented for data analysis, visualization, and application development. For the optimization studies, the gelatin/lipoid S75 amounts and the organic/aqueous phase were selected as independent variables while the obtained particle size as a dependent variable. The optimum predicted formulation was characterized by cryo-TEM microscopy, particle size measurements, stability, and in vitro release. The produced nanoparticles contain drug in amorphous state and decreased amounts of stabilizing agents. The dissolution rate of the lyophilized powder was significantly enhanced in the first 2 h. MSM was proved capable to interpret in detail and to predict with high accuracy the optimum formulation. The mixer technique was proved capable to develop CyA nanoparticulate formulations.

Item Type: Article
Uncontrolled Keywords: mixing, mathematical model, liposomes, polymeric drug delivery systems, nanoparticles
Subjects: Q Science > QC Physics
Q Science > QD Chemistry
T Technology > TP Chemical technology
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science > School of Science (SCI)
Related URLs:
Last Modified: 11 Feb 2020 13:14
URI: http://gala.gre.ac.uk/id/eprint/2189

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