480528 Nano-Hydrogel Systems for Biomolecule Targeting and Therapeutic Delivery

Monday, November 14, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Justin X. Zhong, McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, John R. Clegg, Department of Biomedical Engineering, University of Texas at Austin, Austin, TX and Nicholas A. Peppas, McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX


Introduction: Molecularly imprinted polymers (MIPs) present a stable, cost-effective alternative to current antibody-based therapies, demonstrating a capacity to recognize and bind biomolecules in porous polymer structures. In previous work, we demonstrated the use of analogue templating to increase the affinity of target biomolecules to microparticles1; however, these particles were too large to be used as an injectable drug carrier. In order to effectively design a MIP injectable drug delivery platform, which takes advantage of the enhanced permeation and retention (EPR) effect, MIPs must be less than 100 nm in diameter. In this work, we present the optimization and characterization of nanoscale MIP hydrogels. These nanoparticles present a potential novel targeted drug delivery vehicle for cancer therapy.

Materials and Methods: Hydrogel nanoparticles were synthesized through an inverse emulsion polymerization. An aqueous phase containing monomers was added to an organic phase containing surfactants to form acrylamide-co-(methacrylic acid) crosslinked nanogels. The impact of monomer concentration, surfactant ratios, and surfactant concentrations were independently quantified. Nanoparticles’ size, composition, and pH-responsive swelling behavior were characterized by dynamic light scattering and FTIR. MIP nanoparticles were then synthesized in the presence of a protein template (cytochrome c or hemoglobin), while non-imprinted polymers (NIPs) were synthesized in the absence of protein as a control. Nanoscale protein-polymer interactions were assessed through equilibrium adsorption of cytochrome c and hemoglobin to MIPs and NIPs. Additionally, the impact of NIPs modification with tyramine or N,N-dimethylethylenediamine on hydrophilic model drug loading was explored.

Results and Discussion: We successfully optimized an inverse emulsion polymerization to produce polymer nanoparticles of a desired size (75 nm). Increasing monomer concentration in the aqueous phase increased nanoparticle size until the concentration reached 7.3M, where the emulsion became unstable. As monomer concentration was decreased, nanoparticle size approached a lower threshold, determined by the surfactant micelles (60 nm). Modulation of surfactant ratio found that more charged co-surfactant (AOT) produced less stable micelles and larger particles, while more non-charged co-surfactant (Brij-30) produced smaller particles. Increasing surfactant concentration resulted in a decrease in nanoparticle size down to the previously determined lower threshold. Inclusion of a protein template during polymerization increased template protein mass binding by 15% and 30% for hemoglobin and cytochrome c, respectively, over the non-imprinted controls. Modified and unmodified NIPs loaded significant quantities (≥100 mg/g polymer) of hydrophilic (methylene blue) and hydrophobic (fluorescein) model drugs.

Conclusions: We optimized an inverse emulsion polymerization to produce poly(MAA-co-Aam) nanoparticles of a target size for injectable drug delivery. These nanoparticles are capable of recognizing proteins through molecular imprinting and efficiently loading model drugs. While further studies are needed to fully characterize this system, these nanoparticles present the foundation for an intelligent hydrogel drug delivery vehicle.

[1] Clegg, JR Zhong, JX Irani, AS Gu, J Spencer, DS and Peppas NA. Characterization of protein interactions with molecularly imprinted hydrogels that possess engineered affinity for high isoelectric point biomarkers. Journal of Biomedical Materials Research A, Under Review.


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