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Preparation and Evaluation of Rebamipide Film using Casting Technique for Local Action
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Abstract

The aim of this study was to prepare rebamipide ocular inserts in order to extend its release on the ocular surface for dry eye treatment. Solubility study was applied to the drug with or without l-arginine using different solvents. Solvent casting technique was used to prepare the inserts; l-arginine was used to solubilize the drug, hydroxypropyl methylcellulose grades (E5 and K15M) and poly ethylene glycol 200 were used as excipients. The inserts were evaluated for their physical and mechanical properties, moisture loss% and absorption %, surface pH, and in-vitro drug release. The use l-arginine exhibited an enhancement of rebamipide solubility in both deionized water and phosphate buffer (pH 7.4) by approximately 250 times and 3 times, respectively. The formulations showed uniform weight and thickness except for F1, and all showed uniform drug content. The absence of plasticizer in F1 caused haziness in its appearance and brittleness of the inserts. F3 which contain hydroxypropyl methylcellulose K15M showed good physical and mechanical properties thus was selected for in vitro release and was compared to the marketed brand Mucosta® suspension eye drop; F3 showed significant enhancement in extending the release of rebamipide compared to the reference marketed brand.

Keywords: Rebamipide, L-arginine, Ocular insert, Solvent casting technique

 

 

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Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Sun Aug 28 2016
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World Journal Of Pharmacy And Pharmaceutical Sciences
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Wed Nov 13 2019
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Publication Date
Tue Feb 06 2024
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Publication Date
Fri Jan 31 2025
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Fri Jan 11 2019
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experimental data.

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Publication Date
Fri May 01 2020
Journal Name
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Publication Date
Thu Mar 31 2016
Journal Name
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