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ISSN 2063-5346
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FORMULATION AND INVITRO EVALUATION OF ORLISTAT SOLID DISPERSION

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G. Bhagya Buela1*, Amatul Noor Shaima2, Bibi Ayesha Farha2, Shareef Unnisa Begum2, Mariya Mehveen2, Mr. V. Vijaya Kumar3
» doi: 10.48047/ecb/2023.12.si10.00286

Abstract

Objectives: orlistat is used as an antiobesity drug, widely used orally in the treatment of hypercolestremia. The model drug belongs to BCS class II and undergoes extensive first‐pass metabolism with a bioavailability of only about 15%. Hence this work was planned to improve the oral bioavailability of orlistat by increasing its solubility and dissolution characteristics through the solid dispersion technique using HPMC, PEG 4000 and Eudragit L 100 as carriers. Methods: Solid binary systems of orlistat were prepared by solvent evaporation method using HPMC, PEG and Eudragit L 100 as carriers and in the ratios of drug and polymer (1:1, 1:2 and1:3). The various formulations were characterized by drug content, FT-IR, XRD and in vitro dissolution test using USP dissolution test apparatus Type I (basket method) in dissolution medium of 0.1N HCl. The in vitro dissolution results of all preparations were computed by using dissolution software PCP DISSO V3. Results: The percentage Solubility of the drug in different solvents after 24hrs Results was revealed that the pure drug Orlistat was freely soluble in chloroform and insoluble in water. Melting point of the pure drug was found to be 40- 480C. It shows that the pure drug unstable at higher temperatures. Derived properties were performed for pure drug. Results show that the drug compiles with the IP specifications. FT-IR spectra was taken for solid dispersion containing HPMC, PEG4000 and Eudragit L 100 compared with pure drug FTIR data. which reveal that there were no interaction between the pure drug and excipients. The data obtained for in-vitro release were fitted into equations for the zero order and first order, Higuchi, and Korsmeyer, release models; the interpretation of the data was based on the value of the resulting regression co-efficient.

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