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in-silico Design of Nanoparticles for Transdermal Drug Delivery Application


Nanoparticles are used in the medical field for the various applications like cell imaging, drug delivery, gene and si-RNA delivery, to name few. Designing nanoparticle for a given application, purely based on the trial and error experimentation, requires lots of time and efforts. In this study we show that computer simulations could help in designing the nanoparticles for drug delivery thus reducing the time and cost associated with their design, development and deployment. The permeation of nanoparticles, having various surface chemistry and pattern, through skin lipid bilayer were studied using constrained and unconstrained molecular dynamics simulation. Interestingly, the permeation mechanism of nanoparticle having same surface chemistry but different pattern was found to be completely different. The nanoparticles (NPs) were screened based on the free energy of permeation through skin lipid bilayer. These behavior of screened NPs was further validated with the unconstrained simulations using skin lipid bilayer. Nanoparticles thus screened through both of the techniques were further used for the co-delivery of a model protein into skin lipid bilayer. It was observed that the nanoparticle having 2:1 homogenous ratio of hydrophobic to hydrophilic regions was the most promising in transdermal delivery of proteins. The obtained results are in line with the results of recent permeation experiments on cell and plasma membrane. Our study could help in in-silico design of nanoparticles for delivery of actives through skin. These in-silico experiments thus could help speed up the development process by guiding the formulation chemists.

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Publication details

The article was received on 24 Oct 2017, accepted on 03 Feb 2018 and first published on 05 Feb 2018

Article type: Paper
DOI: 10.1039/C7NR07898F
Citation: Nanoscale, 2018, Accepted Manuscript
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    in-silico Design of Nanoparticles for Transdermal Drug Delivery Application

    R. Gupta and B. Rai, Nanoscale, 2018, Accepted Manuscript , DOI: 10.1039/C7NR07898F

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