(344g) Mathematical Model for Microencapsulation of Cells within Biofunctional PEG Hydrogel | AIChE

(344g) Mathematical Model for Microencapsulation of Cells within Biofunctional PEG Hydrogel


Kizilel, S. - Presenter, Koç University

PEG hydrogels are an important class of biomaterials, specifically for microencapsulation of insulin-producing pancreatic islets, providing an ?immunoisolation-barrier? between the host tissue and encapsulated islets. The coating must exclude the large molecular components of the immune system, but still maintain islet viability and permit diffusion of nutrients. However, a previously un-addressed problem is the inability of highly permissive hydrogels to improve insulin secretion capability of microencapsulated islets or reduce the requirement of high transplantation volume. Here, a general mathematical model has been developed to describe microencapsulation of islets within an insulinotropic peptide functionalized PEG hydrogels. Experimental measurements of the thickness and swelling of peptide functionalized hydrogel membranes compare well with the model. The model is developed by using the pseudo-kinetic approach and the method of moments, and is capable of predicting the crosslink density, thickness of a biofunctional hydrogel membrane, as well as the level of peptide incorporation within the membrane. Parametric sensitivity for the effects of PEG-DA, VP concentration towards the crosslink density, thickness, and peptide incorporation of the hydrogel is also investigated. The results obtained for different PEG-DA and VP concentrations suggest that the concentration of VP and PEG-DA monomers are critical in controlling the gel thickness, permeability and biomolecules incorporation. This model should be considered in the design of future biofunctional PEG hydrogel systems where drugs, proteins or cells are microencapsulated within biofunctional PEG hydrogel to predict the growth, crosslink density profiles, and the level of peptide incorporation. This study also demonstrates the possibility of predicting the concentration of biological cues in highly permissive PEG hydrogels.