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Quantifying the mechanical properties of human skin to optimise future microneedle device design

Groves, Rachel Beth, Coulman, Sion, Birchall, James Caradoc and Evans, Samuel Lewin 2012. Quantifying the mechanical properties of human skin to optimise future microneedle device design. Computer Methods in Biomechanics and Biomedical Engineering 15 (1) , pp. 73-82. 10.1080/10255842.2011.596481

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Abstract

Microneedle devices are a promising minimally invasive means of delivering drugs/vaccines across or into the skin. However, there is currently a diversity of microneedle designs and application methods that have, primarily, been intuitively developed by the research community. To enable the rational design of optimised microneedle devices, a greater understanding of human skin biomechanics under small deformations is required. This study aims to develop a representative stratified model of human skin, informed by in vivo data. A multilayer finite element model incorporating the epidermis, dermis and hypodermis was established. This was correlated with a series of in-vivo indentation measurements, and the Ogden material coefficients were optimised using a material parameter extraction algorithm. The finite element simulation was subsequently used to model microneedle application to human skin before penetration and was validated by comparing these predictions with the in-vivo measurements. Our model has provided an excellent tool to predict micron-scale human skin deformation in vivo and is currently being used to inform optimised microneedle designs.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Pharmacy
Engineering
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: R Medicine > RL Dermatology
T Technology > T Technology (General)
Uncontrolled Keywords: microneedle ; human skin ; finite element analysis ; inverse methods ; Ogden model of hyperelasticity ; multilayer
Additional Information: Special Issue: Identification of material parameters through inverse finite element modelling
Publisher: Taylor & Francis
ISSN: 1025-5842
Last Modified: 04 Nov 2017 23:59
URI: http://orca.cf.ac.uk/id/eprint/14051

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