A systems approach to modeling drug release from polymer microspheres to accelerate in vitro to in vivo translation

Mathematical models of controlled release that span the in vitro to in vivo transition are needed to speed the development and translation of clinically-relevant controlled release drug delivery systems. Fully mechanistic approaches are often challenged due to the use of highly-parameterized mathematically complex structures to capture the release mechanism. The simultaneous scarcity of in vivo data to inform these models and parameters leads to a situation where overfitting to capture observed phenomena is common. A data-driven approach to model development for controlled drug release from polymeric microspheres is taken herein, where physiological mechanisms impacting controlled release are incorporated to capture observed changes between in vitro release profiles and in vivo device dynamics. The model is generalizable, using non-specific binding to capture drug-polymer interactions via charge and molecular structure, and it has the ability to describe both inhibited (slowed) and accelerated release resulting from electrostatic or steric interactions. Reactive oxygen species (ROS)-induced degradation of biodegradable polymers was incorporated via a reaction-diffusion formalism, and this suggests that ROS may be the primary effector of the oft-observed accelerated in vivo release of polymeric drug delivery systems. Model performance is assessed through comparisons between model predictions and controlled release of several drugs from various-sized microparticles in vitro and in vivo.