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Optimising distribution of hollow microneedle in arrays for transdermal drug delivery considering effects of tissue compression on drug permeability

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posted on 2025-05-28, 12:48 authored by Rahul NaddaRahul Nadda, Diganta DasDiganta Das

Hollow microneedles (HMNs) are advanced transdermal drug delivery (TDD) devices that can create micro-perforations in the skin, enabling high molecular weight drugs to bypass the resistance of the skin’s top layer, the stratum corneum. These MNs have been shown to enhance drug permeability (K) in skin with minimal or no discomfort. It is recognised that the variability and interplay of different MN parameters, including the MN distribution within an array, can significantly influence the HMN-based TDD rate. However, optimising these parameters can achieve consistent MN performance. In recognising this, our paper aims to develop a theoretical framework for optimising the HMN distribution in the arrays. The methodology involves formulating an optimisation function (g) based on different geometrical and physical properties of the MN and skin and associating this with the skin permeability (K) of drugs delivered via the HMNs. The methodology has been established to quantitatively assess the impact of MN design parameters on drug diffusion through the skin, including the effects of compressive strain caused by HMN insertion. The study shows that an elevated value of g is associated with increased drug K in the skin. The results from the established framework have enabled us to determine the optimal design for various HMN configurations. The data generated from this optimisation technique is subsequently utilised to estimate the skin K of several high molecular weight drugs delivered through an HMN system.

Funding

Micron-scale, chemically-controlled, auto-injection systems for at-home drug delivery

Engineering and Physical Sciences Research Council

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History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Published in

International Journal of Pharmaceutics

Volume

673

Publisher

Elsevier B.V.

Version

  • VoR (Version of Record)

Rights holder

©The Author(s)

Publisher statement

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Acceptance date

2025-02-21

Publication date

2025-02-24

Copyright date

2025

ISSN

0378-5173

eISSN

1873-3476

Language

  • en

Depositor

Dr Diganta Das. Deposit date: 28 February 2025

Article number

125386

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