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Research Papers

Simulation of Drug-Loaded Nanoparticles Transport Through Drug Delivery Microchannels

[+] Author and Article Information
Yongting Ma

Department of Mechanical
and Nuclear Engineering,
Virginia Commonwealth University,
Richmond, VA 23284

Ramana M. Pidaparti

College of Engineering,
University of Georgia,
Athens, GA 30602
e-mail: rmparti@uga.edu

1Corresponding author.

Manuscript received October 22, 2013; final manuscript received September 30, 2014; published online November 11, 2014. Assoc. Editor: Malisa Sarntinoranont.

J. Nanotechnol. Eng. Med 5(3), 031002 (Aug 01, 2014) (7 pages) Paper No: NANO-13-1078; doi: 10.1115/1.4028732 History: Received October 22, 2013; Revised September 30, 2014; Online November 11, 2014

Ocular drug delivery is a complex and challenging process and understanding the transport characteristics of drug-loaded particles is very important for designing safe and effective ocular drug delivery devices. In this paper, we investigated the effect of the microchannel configuration of the microdevice, the size of drug-loaded nanoparticles (NPs), and the pressure gradient of fluid flow in determining the maximum number of NPs within a certain outlet region and transportation time of drug particles. We employed a hybrid computational approach that combines the lattice Boltzmann model for fluids with the Brownian dynamics model for NPs transport. This hybrid approach allows to capture the interactions among the fluids, NPs, and barriers of microchannels. Our results showed that increasing the pressure gradient of fluid flow in a specific type of microchannel configuration (tournament configuration) effectively decreased the maximum number of NPs within a certain outlet region as well as transportation time of the drug loaded NPs. These results have important implications for the design of ocular drug delivery devices. These findings may be particularly helpful in developing design and transport optimization guidelines related to creating novel microchannel configurations for ocular drug delivery devices.

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Figures

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Fig. 1

Device design concept for ocular drug delivery, adopted from Ref. [9]

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Fig. 2

Isometric microchannel configurations ((a)–(c)) and computational setups ((d)–(f)) used to examine the ocular drug delivery driven by pressure gradient of fluid flow. The geometry of the two-dimensional channel is specified by the length L and width W. Periodic boundary conditions are applied at the left and right sides as well as at the top and bottom sides. Dark and light are used to represent barriers of microchannel and fluid.

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Fig. 3

Snapshots of pressure driven fluid flow through straight microchannel with 100 NPs at: (a) t = 0.0, (b) t = 3.2 × 105, and (c) t = 6.6 × 105

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Fig. 4

Snapshots of pressure driven fluid flow through meshed microchannel with 200 NPs at: (a) t = 0.0, (b) t = 2.7 × 105, and (c) t = 4.98 × 105

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Fig. 5

Snapshots of pressure driven fluid flow through tournament microchannel with 275 NPs at: (a) t = 0.0, (b) t = 5.4 × 105, and (c) t = 1.46 × 106

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Fig. 6

Number of NPs within a certain outlet region as a function of time for pressure driven fluid flow with different microchannel configurations. Snapshots represent the maximum number of NPs at the outlet of microchannels.

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Fig. 7

(a) Maximum number of NPs within a certain outlet region as a function of size of NPs. (b) Transportation time of drug particles at the outlet of tournament microchannel as a function of size of NPs. Each bar is the average of three independent runs; the error bars are the standard deviations.

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Fig. 8

(a) Maximum number of NPs within a certain outlet region as a function of pressure gradient of fluid flow. (b) Transportation time of drug particles at the outlet of tournament microchannel as a function of pressure gradient of fluid flow. Each bar is the average of three independent runs; the error bars are the standard deviations.

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