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|Title: ||Microneedle assisted micro-particle delivery by gene guns: mathematical model formulation and experimental verification|
|Authors: ||Zhang, Dongwei|
Das, Diganta Bhusan
Rielly, Chris D.
|Issue Date: ||2015|
|Publisher: ||© Elsevier|
|Citation: ||ZHANG, D.-W., DAS, D.B. and RIELLY, C.D., 2015. Microneedle assisted micro-particle delivery by gene guns: mathematical model formulation and experimental verification. Chemical Engineering Science, 125, pp. 176-190.|
|Abstract: ||Gene gun is a micro-particles delivery system which accelerates DNA loaded micro-particles to a high speed so as to enable penetration of the micro-particles into deeper tissues to achieve gene transfection. Previously, microneedle (MN) assisted micro-particles delivery has been shown to achieve the purpose of enhanced penetration depth of micro-particles based on a set of laboratory experiments. In order to further understand the penetration process of micro-particles, a mathematical model for MN assisted micro-particles delivery is developed. The model mimics the acceleration, separation and deceleration stages of the operation of a gene gun (or experimental rig) aimed at delivering the micro-particles into tissues. The developed model is used to simulate the particle velocity and the trajectories of micro-particles while they penetrate into the target. The model mimics the deceleration stage to predict the linear trajectories of the micro-particles which randomly select the initial positions in the deceleration stage and enter into the target. The penetration depths of the micro-particles are analyzed in relation to a number of parameters, e.g., operating pressure, particle size, and MNs length. Results are validated with experimental results obtained from the previous work. The results also show that the particle penetration depth is increased from an increase of operating pressure, particle size and MN length. The presence of the pierced holes causes a surge in penetration distance. © 2014 Elsevier Ltd. All rights reserved.|
|Description: ||This is the author’s version of a work that was accepted for publication in Chemical Engineering Science. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Chemical Engineering Science, vol. 125, March 2015, DOI: 10.1016/j.ces.2014.06.031|
|Sponsor: ||Loughborough University (UK) is acknowledged for providing a PhD studentship to Dongwei Zhang which made this work possible.|
|Version: ||Accepted for publication|
|Publisher Link: ||http://dx.doi.org/10.1016/j.ces.2014.06.031|
|Appears in Collections:||Published Articles (Chemical Engineering)|
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