Controlling growth factor diffusion by modulating water content in injectable hydrogels

Abstract

Recent advancements in the delivery of therapeutics for retinal diseases include the development of injectable hydrogels, networks of one or more hydrophilic polymers that contain a high-volume fraction of water. These systems are of particular interest due to their biocompatibility, permeability to water-soluble metabolites, and function as minimally invasive injectable delivery vehicles. Recently, hydrogels for ophthalmic applications have been developed that display a controlled release of factors necessary for cellular survival and proliferation. Understanding the relationship between the volume water fraction and the physical, chemical, and diffusion properties of the hydrogel scaffold could aid in the improvement of existing drug delivery treatments for retinal regeneration. In this study, we compared the diffusion and release of human epidermal growth factor (hEGF) encapsulated in different injectable homogenous and heterogenous hydrogels, namely gelatin-hydroxyphenyl propionic acid (Gtn-HPA) and hyaluronic acid-tyramine (HA-Tyr)-based hydrogels. These experimental results were compared with the measured stiffness and water content of these hydrogels and applied to different diffusion theories of polymers to determine the model of best fit. We find that the normalized diffusion and release of hEGF increases with free water content in injectable hydrogels: ranging from 0.176 at 41% free water in HA-Tyr to 0.2 at 53% free water in Gtn-HPA, whereas it decreases with hydrogel stiffness: 600 Pa for Gtn-HPA and 1440 Pa for HA-Tyr. Further, we compared our experimental data with theoretical diffusion models. We found that homogeneous theoretical models, notably the hydrodynamic model (giving a normalized diffusion close to 0.2), provide the most suitable explanation for the measured solute diffusion coefficient. Impact statement Diffusion in a three-dimensional system is a key factor in designing new hydrogel-based materials. It allows to control and predict diffusion in implants and delivery systems. However, very little is done to explore and test the diffusion since it is a complex process. Many models can predict solute diffusion; however, practical application using these models has not yet been done. We have shown the variation of these models in a practical extent, which could have a tremendous impact on designing biomaterial for biological application as it allows one to understand the diffusion of injected drugs and growth factors.