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J R Soc Interface. 2018 Feb;15(139). pii: 20170949. doi: 10.1098/rsif.2017.0949.

Tailoring drug release rates in hydrogel-based therapeutic delivery applications using graphene oxide.

Author information

1
Centre de Recherche en Cancérologie de Marseille, CRCM, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, Marseille, France tania.guenneau-puvirajesinghe@inserm.fr.
2
Diabetes Research Group, King's College London Faculty of Life Sciences and Medicine, Guy's Hospital Campus, London, UK.
3
Department of Mathematics, Imperial College London, London, UK.
4
CNRS-Imperial "Abraham de Moivre" Unité Mixte Internationale, London, UK.
5
Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille, France sebastien.guenneau@fresnel.fr.

Abstract

Graphene oxide (GO) is increasingly used for controlling mass diffusion in hydrogel-based drug delivery applications. On the macro-scale, the density of GO in the hydrogel is a critical parameter for modulating drug release. Here, we investigate the diffusion of a peptide drug through a network of GO membranes and GO-embedded hydrogels, modelled as porous matrices resembling both laminated and 'house of cards' structures. Our experiments use a therapeutic peptide and show a tunable nonlinear dependence of the peptide concentration upon time. We establish models using numerical simulations with a diffusion equation accounting for the photo-thermal degradation of fluorophores and an effective percolation model to simulate the experimental data. The modelling yields an interpretation of the control of drug diffusion through GO membranes, which is extended to the diffusion of the peptide in GO-embedded agarose hydrogels. Varying the density of micron-sized GO flakes allows for fine control of the drug diffusion. We further show that both GO density and size influence the drug release rate. The ability to tune the density of hydrogel-like GO membranes to control drug release rates has exciting implications to offer guidelines for tailoring drug release rates in hydrogel-based therapeutic delivery applications.

KEYWORDS:

biocompatibility; drug delivery media; effective model; graphene oxide; mass diffusion

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