Mathematical modeling for predicting betamethasone profile and burst release from in situ forming systems based on PLGA

This paper examines the application of mathematical modeling to a novel drug delivery system using artificial neural networks. For this purpose, a Feed-Forward back propagation network was trained by two different concepts and the behavior of this drug delivery system was analyzed based on the simulated results. The network also successfully determined the most accurate release profiles under specific formulation parameters. The simulated results showed a high correlation with the real data in this study. Furthermore, a new method was proposed in order to predict the burst release point in Poly Lactic-co-Glycolic Acid (PLGA) based drug delivery systems. This paper reveals that the mathematical modeling of novel drug delivery systems not only significantly decreases time and cost, but also facilitates the design of new pharmaceutical formulations.