Abstract
Aims: The aim of the present study was to develop and optimize a Stealth Liposomal Drug Delivery System of microtubule inhibitor using Box–Behnken Design and Desirability function.
 Study Design: Development and Optimization of Stealth Liposomes.
 Place and Duration of Study: The study was carried out in the Department of Pharmacy, Annamalai University, between September 2020 and May 2021.
 Methodology: Stealth Liposomes were prepared by the thin-film hydration method (TFH). The formulation was optimized using Box – Behnken design to study the effect of independent variables, Amount of Egg Phosphatidylcholine (X1), Amount of Cholesterol (X2), and Amount of DSPE-PEG 2000(X3) on dependent variables Entrapment Efficiency (Y1) and In-vitro drug release (Y2).
 Results: Entrapment efficiency of the Stealth Liposomes ranges from 56.35 to 84.25%and in-vitro release ranges from 62.38 to 94.26%. The optimized formulation was found using the desirability function to get maximum entrapment with maximum drug release. The optimized formulation showed entrapment efficiency of 80.46% and in-vitro release of 90.11%.
 Conclusion: Stealth Liposomal Drug Delivery System for microtubule inhibitor was successfully developed and optimized using desirability function in Design Expert software by a three-factor, three level Box – Behnken design.
Highlights
A reasonable experimental design is very important, especially when complex formulations need to be developed, as it can save time, money and reduce experimental errors to obtain reliable experimental data
The Fourier transform infrared spectroscopy (FTIR) spectra of the drug alone and with the physical mixtures of Egg phosphatidylcholine, Cholesterol, and DSPE-PEG 2000 indicate no interaction between the drug and the excipients when compared with the infrared spectrum of the pure drug as all functional group frequencies are present
An experimental design of fifteen runs was generated for three factors at three levels to identify the optimum levels of different independent process parameters according to Box – Behnken design
Summary
A reasonable experimental design is very important, especially when complex formulations need to be developed, as it can save time, money and reduce experimental errors to obtain reliable experimental data. The multivariate strategy of experimental design allows simultaneous investigation of the effects of several variables, their actual significance on the considered response, and the possible interrelationship among them. This approach yields maximum information with a small number of experiments [1]. RSM includes central composite design (CCD), Box-Behnken design (BBD), and Doehlert design (DM). The present study used BBD since it has a high fitting correlation coefficient, good predictability, and high precision and has been considered to be a cost-effective technique compared to the other usual processes of formulation and optimization because it requires fewer experimental runs and saves time [2]
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