A Novel Formulation of Orlistat Solid Dispersions Using Solvent Evaporation Technique

Abstract

Solubility is an important physicochemical factor affecting absorption of drug and there by its therapeutic effect. About 40% of newly discovered drugs are lipophilic and failed to reach market due to their poor water solubility. Solid dispersions proved to have tremendous potential for improving drug solubility. Orlistat is a poor water soluble substance possessing anti-obesity property; in the present study an attempt was made to increase the solubility of orlistat by preparing solid dispersions using solvent evaporation technique. Three different formulations were prepared using Hydroxy propyl methyl cellulose (HPMC), Polyethylene glycol (PEG) and Eudragit with varying ratios of drug and carrier viz. 1:1, 1:2, 1:3 and the corresponding physical mixtures were also prepared. These solid dispersions were evaluated for flowability, solubility characteristics and in-vitro drug release. The in-vitro release of the formulation OP-SD3 was found to be best among all the 9 formulations with a release of 87.2% at the end of 2 hours. Release was best fitted with Korsmeyer-peppas kinetics and it shows that the drug release may follow diffusion mechanism. In-vitro dissolution studies showed that the dispersion system containing orlistat, dissolution of orlistat was retarded which attributed to ionic interaction and gel forming respectively but the solid dispersion containing PEG as carrier gave faster dissolution rate than physical mixture. Thus the solid dispersion technique found to be effective in increasing aqueous solubility of orlistat.

Composition of Lipid Based Nanoemulsion for Oral Delivery of Orlistat

“…Computed F-value was lower than critical Fvalues, which denotes non significance with regard to lack of fit [Tables 3 and 4]. For lack of fit P values, we obtained are not showed for response Y1 and Y2, and hence, the current model provided a satisfactory fit to the data and had no lack of fit [11][12][13][14][15]. The statistical nonsignificance of each effect was tested by comparing the mean square against and estimates of the experimental error.…”