Modelling of coupled diffusion-deformation for swelling-assisted drug delivery mechanism in hydroxypropyl methylcellulose-controlled release tablet

Abstract

Predicting drug delivery mechanism from swelling device has gained significant importance due to the massive global health burden to obtain the safe and effective delivery of therapeutics at the target site of action. Hydroxypropyl methylcellulose is a promising material for controlled drug delivery due to its ability to swell and release entrapped medicines in response to physiological stimuli. In the present work, finite element method (FEM) has been employed in conjunction with hygroscopic swelling material model to thoroughly understand and investigate the complex mechanisms that govern the hydroxypropyl methylcellulose-controlled release (HPMC-CR) tablet. The computational method via FEM provides numerical solutions for mathematical modelling of complex physical phenomena that evolves during swelling-assisted drug delivery from HPMC-CR tablet. This paper addresses the mathematical formulation of coupled diffusion-deformation to simulate the swelling mechanisms of HPMC-CR tablet. The modelling of water diffusion in stressed tablet matrix is derived from Fick’s second law and coupled with solid mechanics model. COMSOL Multiphysics® software is utilized to solve the initial-boundary value problems for evaluating water concentration, and displacement of HPMC-CR tablet. The implementation of a deformable mesh to model the change in diffusion length due to swelling is the novelty of this work. The effect of water concentration on swelling properties of HPMC-CR tablet is investigated via three tablet structure designs: (1) non-swellable single-layer, (2) swellable single-layer and (3) swellable three-layer tablets. The simulation results obtained from the numerical model are comparable to the experimental data where R2 = 0.979. This study finds that the rate of water diffusion significantly decreases as the HPMC-CR tablets swell. Tablet expansion causes a reduction in water diffusivity. The results obtained demonstrate that computational predictive model can effectively envisage the drug delivery mechanism in preclinical phases, which can decrease drug failure rates, reduce the time and cost of development, thus giving patients more effective and secure therapeutic options.