349745 Understanding the Flow Dynamics of Nanoparticles for Improved Cancer Therapy

Monday, November 4, 2013
Grand Ballroom B (Hilton)
Meaghan Sullivan1, Vinit Patel1, Michael Ward2, Diva Evans2, Erik Carboni2, Grant Bouchillon2, Leslie Shor2,3, Suzy Torti4 and Anson W. K. Ma2,5, (1)Department of Chemical and Biomolecular Engineering, Universtiy of Connecticut, Storrs, CT, (2)Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT, (3)Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, (4)University of Connecticut Health Center, University of Connecticut, Storrs, CT, (5)Institute of Materials Science, University of Connecticut, Storrs, CT

The use of nanoparticles for medical diagnosis and treatment has been a growing field of study and, more recently, their use as drug carriers has been proposed for cancer treatment.  In order to determine the effectiveness of this form of treatment, the flow dynamics of these nanoparticles must first be understood.  Recent studies have shown that the interaction between red blood cells and nanoparticles may lead to a “margination” phenomenon, wherein the nanoparticles of an appropriate size and shape trend toward the periphery of blood vessels. Consequently, margination of the nanoparticles may facilitate the delivery of anti-cancer drugs to tumors through the leaky vasculature, which is typically found in blood vessels near a tumor site. In the preliminary stages of this research, the flow dynamics of nanoparticles in blood has been studied using fluorescent polystyrene nanoparticles as a model system.  Aqueous dispersions of these spherical polystyrene nanoparticles are pumped through a microfluidic device, which was created to mimic blood vessel bifurcations, and the concentration profile of the nanoparticles is studied. Further studies will be conducted by examining the flow dynamics of two sets of differently sized polystyrene spheres, with diameters of 500 nm and 750 nm, in water and also in blood. This project is partially supported by the National Science Foundation Grant No. 1250661 and National Science Foundation Graduate Research Fellowship Award No. DGE-1247393.

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