Precise modulation of drug release from emulsions via modification of Pickering particles properties: a computational study using population balance equations

Pickering emulsions, stabilized by solid particles at the interface between continuous and disperse phase, have gained attention due to their advantages over traditional surfactant-stabilized systems. Crystalline particles are promising Pickering materials as their interfacial activity can be controlled by changing crystal properties such as size, shape and polymorphism. Pickering particles can play a crucial role in modulating the release of active ingredients (AI) encapsulated in the dispersed phase. In fact, by controlling the dissolution of Pickering particles, which act as physical barrier to the AI diffusion, it is possible to modulate the release of the AI itself. Hence, enabling stimuli-responsive and/or prolonged release. To gain deeper insight into this release mechanism, we developed a theoretical model that integrates population balance equations (PBE) to describe Pickering particle dissolution, and Fick’s law of diffusion to describe the release of AI from the disperse phase. The PBEs were solved using the High-Resolution Finite Volume method, ensuring accurate numerical representation of dissolution dynamic. Based on experimental observations reported in the literature, our model can capture the evolution of AI concentration in the dispersed and continuous phase, and it can be used to identify how particle population properties, especially particle size and shape distributions, influence release behavior, thereby supporting formulation screening toward specific AI release profiles