Positive Charge of "Sticky" Peptides and Proteins Impedes Release From Negatively Charged PLGA Matrices.

The influence of electrostatic interactions and/or acylation on release of charged ("sticky") agents from biodegradable polymer matrices was systematically characterized. We hypothesized that release of peptides with positive charge would be hindered from negatively charged poly(lactic-co-glycolic acid) (PLGA) microparticles. Thus, we investigated release of peptides with different degrees of positive charge from several PLGA microparticle formulations, with different molecular weights and/or end groups (acid- or ester-terminated). Indeed, release studies revealed distinct inverse correlations between the amount of positive charge on peptides and their release rates from each PLGA microparticle formulation. Furthermore, we examined the case of peptides with net charge that changes from negative to positive within the pH range observed in degrading microparticles. These charge changing peptides displayed counterintuitive release kinetics, initially releasing faster from slower degrading (less acidic) microparticles, and releasing slower from the faster degrading (more acidic) microparticles. Importantly, trends between agent charge and release rates for model peptides also translated to larger, therapeutically relevant proteins and oligonucleotides. The results of these studies may improve future design of controlled release systems for numerous therapeutic biomolecules exhibiting positive charge, ultimately reducing time-consuming and costly trial and error iterations of such formulations.

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.