Bioimpacts. 2013;3(2): 75-81.
doi: 10.5681/bi.2013.016
PMID: 23878790
PMCID: PMC3713873
Scopus ID: 84881500267
  Abstract View: 1812
  PDF Download: 1676

Original Research

Application of Response Surface Methodology in Development of Sirolimus Liposomes Prepared by Thin Film Hydration Technique

Saeed Ghanbarzadeh, Hadi Valizadeh*, Parvin Zakeri-Milani


Introduction: The present investigation was aimed to optimize the formulating process of sirolimus liposomes by thin film hydration method. Methods: In this study, a 32 factorial design method was used to investigate the influence of two independent variables in the preparation of sirolimus liposomes. The dipalmitoylphosphatidylcholine (DPPC) /Cholesterol (Chol) and dioleoyl phosphoethanolamine(DOPE) /DPPC molar ratios were selected as the independent variables. Particle size (PS) and Encapsulation Efficiency (EE %) were selected as the dependent variables. To separate the un-encapsulated drug, dialysis method was used. Drug analysis was performed with a validated RP-HPLC method. Results: Using response surface methodology and based on the coefficient values obtained for independent variables in the regression equations, it was clear that the DPPC/Chol molar ratio was the major contributing variable in particle size and EE %. The use of a statistical approach allowed us to see individual and/or interaction effects of influencing parameters in order to obtain liposomes with desired properties and to determine the optimum experimental conditions that lead to the enhancement of characteristics. In the prediction of PS and EE % values, the average percent errors are found to be as 3.59 and 4.09%. This value is sufficiently low to confirm the high predictive power of model. Conclusion: Experimental results show that the observed responses were in close agreement with the predicted values and this demonstrates the reliability of the optimization procedure in prediction of PS and EE % in sirolimus liposomes preparation.
Keywords: Liposome, Sirolimus, Central Composite Design, Response Surface Methodology
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Submitted: 01 Dec 2012
Revision: 12 Feb 2013
ePublished: 30 Apr 2013
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