Mass transport analysis of the particle drifting effect in a biphasic diffusion apparatus

Formulations containing colloidal particles, such as micelles, nanocrystals, and amorphous drug nanoparticles, are widely used to enhance the oral absorption of poor soluble drugs. The underlying mechanism was proposed to be the particle drifting effect, where the particles effectively reduce the diffusional resistance of the aqueous boundary layer by releasing the free drug near the surface of the absorption site, such as a membrane, the intestinal mucosa, or an interface. However, it remains challenging to appropriately interpret experimental data or to accurately predict enhanced permeation rate provided by particle drifting effect. In this study, we developed an integrated dissolution-permeation model to quantitatively analyze the particle drifting effect. Using a biphasic experimental setup, amorphous drug nanoparticles of several poorly soluble model drugs were evaluated. The particle drifting effect was modeled by coupling the Wang-Flanagan particle dissolution model with a stagnant-film permeation model. Results suggested that drug nanoparticles at low concentrations did not alter the diffusional profile or the fitted permeability coefficient. At high particle concentrations, a flux plateau was observed, signifying non-sink dissolution of the particles. The fitted interfacial permeability coefficient increased with increasing particle concentration, confirming reduced diffusional resistance of the aqueous boundary layer by the presence of drug particles. High number of particles also altered the fitted partition coefficient of the drug due to saturation of the free drug in the aqueous boundary layer adjacent to the liquid interface. The mass transport model was able to predict the particle drifting effect for systems with high particle concentrations or extremely poorly soluble drugs where experimental evaluations become challenging. Combined with a differential equation-based pharmacokinetic model, in vivo drug absorption of a model drug enzalutamide was predicted at different doses with satisfaction. This work provides mechanistic understanding of the diffusional profiles obtained through the biphasic setup, and may contribute to more accurate oral bioavailability prediction for formulations that contain amorphous drug nanoparticles.