Development of controlled release dexketoprofen tablets and prediction of drug release using Artificial Neural Network (ANN) modelling

Dexketoprofen trometamol (DT) is an active S (+) enantiomer of ketoprofen, and a non-steroidal anti-inflammatory agent. DT has a short biological half-life and the dosing interval is quite short when there is a need to maintain the desirable effect for longer time periods. Consequently, a controlled release DT tablet was designed for oral administration aiming to minimize the number of doses and the possible side effects. Calculations of the parameters for controlled release DT tablets were shown clearly. Controlled release matrix-type tablet formulations were prepared using hydroxypropyl methylcellulose (HPMC) (low and high viscosity), Eudragit RS and Carbopol, and the effects of different polymers on DT release from the tablet formulations were investigated. The dissolution rate profiles were compared and analyzed kinetically. An Artificial Neural Network (ANN) model was developed to predict drug release and a successful model was obtained. Subsequently, an optimum formulation was selected and evaluated in terms of its analgesic and anti-inflammatory activity. Although the developed controlled release tablets did not have an initial dose, they were found to be as effective as commercially available tablets on the market. Dissolution and in vivo studies have shown that the prepared tablets were able to release DT for longer time periods, making the tablets more effective, convenient and more tolerable.

Bibliographic Details

Main Authors:	Saraçoğlu,Özlem Kışlal, Uludağ,Mecit Orhan, Özdemir,Elif Derya, Değim,İsmail Tuncer
Format:	Digital revista
Language:	English
Published:	Universidade de São Paulo, Faculdade de Ciências Farmacêuticas 2020
Online Access:	http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1984-82502020000100653
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