A Kinetic Monte Carlo algorithm for swelling drug delivery systems

A major challenge in pharmaceutical science consists in designing drug delivery systems that can maintain the concentration of active principle within a therapeutic window over a given period of time. A popular approach consists in storing the drug molecules inside an hydrogel and selecting its physical properties (such as hydrogel swelling in an aqueous environment) to control the release. The theory of swelling systems is not analytically easy because of the complexity of the evolution equations and thus requires numerical approaches. In this context, we have developed a flexible Kinetic Monte Carlo algorithm (KMCa) that can be used to study the release process for a variety of drug delivery systems. In this talk, we present this algorithm and test it for systems where one can derive an analytical solution, namely a core/shell structures and a swelling system in the adiabatic regime. We show that our KMCa correctly reproduces the analytical predictions. Finally, we introduce a semi-empirical model that captures the main features of swelling systems.