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Formulation and evaluation of anti-rheumatic dexibuprofen transdermal patches: a quality-by-design approach

Dexibuprofen (DXIBN) transdermal patches were formulated using various concentrations of selected polymeric excipients (matrix material; ethyl cellulose and polyvinylpyrrolidone, plasticizer (di-N-butyl phthalate), and a conventional permeation enhancer (almond oil)). Initial patch formulations were...

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Bibliographic Details
Published in:Journal of drug targeting 2016-08, Vol.24 (7), p.603-612
Main Authors: Akhlaq, Muhammad, Arshad, Muhammad Sohail, Mudassir, Abdul Mughees, Hussain, Amjad, Kucuk, Israfil, Haj-Ahmad, Rita, Rasekh, Manoochehr, Ahmad, Zeeshan
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Language:English
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Summary:Dexibuprofen (DXIBN) transdermal patches were formulated using various concentrations of selected polymeric excipients (matrix material; ethyl cellulose and polyvinylpyrrolidone, plasticizer (di-N-butyl phthalate), and a conventional permeation enhancer (almond oil)). Initial patch formulations were evaluated for their physiochemical properties (thickness, moisture uptake, final moisture content, and DXIBN content). Also, impact of patch components on resulting tensile strength and in vitro permeation were used to predict an optimal patch formulation using a quality-by-design (QbD) approach, which was subsequently evaluated and further compared with a commercial oral tablet dosage form for in vitro and in vivo release (rabbit model). Initially formulated patches demonstrated uniform thickness (0.44 ± 0.02 cm), relatively low moisture uptake (7.87 ± 1.11 w/w %), and highly acceptable drug loading values (100.0 ± 0.026%). The tensile strength of patches increased significantly with matrix polymer concentration and to a lesser degree with increase in plasticizer and permeation enhancer content, although these affected the permeation of DXIBN. Predicted properties (tensile strength and DXIBN steady-state flux) for the QbD-optimized formulation were in close agreement to experimental results. The QbD optimal patch formulation behavior differed significantly from the commercial tablet formulation in vivo. Such model-based predictions (QbD approach) will reduce cost and time in formulation development sciences.
ISSN:1061-186X
1029-2330
DOI:10.3109/1061186X.2015.1116538