Research Papers

Design Optimization of an Implantable Device Concept for Passive Ocular Drug Delivery

[+] Author and Article Information
Jonathan Marsh

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

Ramana M. Pidaparti

College of Engineering,
University of Georgia,
Athens, GA 30602

1Present address: Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284.

Manuscript received October 18, 2013; final manuscript received December 17, 2013; published online March 7, 2014. Assoc. Editor: Rupak K. Banerjee.

J. Med. Devices 8(2), 021005 (Mar 07, 2014) (6 pages) Paper No: MED-13-1260; doi: 10.1115/1.4026451 History: Received October 18, 2013; Revised December 17, 2013

This paper presents an implantable device concept with applications for treating ocular diseases such as glaucoma, age-related macular degeneration (AMD), diabetic retinopathy, and retinitis pigmentosa. The design of a biodegradable drug delivery device concept consisting of a polydimethylsiloxane (PDMS) shell with a fluid reservoir and micro/nanofluidic tubes that allow the drug to be stored and delivered at a specified rate is discussed. Computational fluid dynamics simulations were conducted through various tube configurations in order to obtain the drug diffusion characteristics. The results from the simulation studies revealed information related to drug transport under varying design parameters. The design simulations were conducted with a desired rate. Based on results from several simulations, an optimization study was conducted to achieve the required dosage for about 2 years. The results obtained from the optimization study shows that the device concept can be extended for different drugs to treat ocular diseases.

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Fig. 1

Proposed device design concept for passive ocular drug delivery

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Fig. 2

An overview of the attachment of the implanted drug delivery device to the eye

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Fig. 3

Initial conditions for design simulations

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Fig. 4

Simulation results of drug concentration through a single microchannel at various times

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Fig. 5

Simulations of drug diffusion rate with time for R = 0.08 mm and L = 0.1–0.3 mm

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Fig. 6

Simulations of diffusion rate for different L with R = 0.08 mm

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Fig. 7

Sensitivity of diffusion rate for various R with L = 0.43 mm

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Fig. 8

Sensitivity of diffusion rate for various R = 0.08 mm with L = 0.37–0.45 mm

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Fig. 9

Diffusion rate for the optimized device design

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Fig. 10

Concentration change over time for the optimized device design




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