- We introduce a "hierarchical" modeling strategy designed to be systematically extensible to increase the detail of dissolution predictions from polydisperse collections of drug particles and to be placed on firm mathematical and physical foundations with diffusion-dominated dissolution at its core to predict dissolution and the evolution of particle size distribution. We assess the model with experimental data and demonstrate higher accuracy by treating the polydisperse nature of dissolution. A level in the hierarchy is applied to study elements of diffusion-driven dissolution, in particular the role of particle-size distribution width with varying dose level and the influences of "confinement" on the process of dissolution. Confinement influences surface molecular flux, directly by the increase in bulk concentration and indirectly by the relative volume of particles to container. We find that the dissolution process can be broadly categorized within three "regimes" defined by the ratio of total concentration Ctot to solubility CS . Sink conditions apply in the first regime, when C tot /CS<∼0.1. When C tot /CS>∼5 (regime 3) dissolution is dominated by confinement and normalized saturation time follows a simple power law relationship. Regime 2 is characterized by a "saturation singularity" where dissolution is sensitive to both initial particle size distribution and confinement.