Tay, J. H., Lim, Y. H., Zheng, M., Zhao, Y., Tan, W. S., Xu, C., Ramamurty, U., & Song, J. (2023). Development of hyaluronic acid-silica composites via in situ precipitation for improved penetration efficiency in fast-dissolving microneedle systems. Acta Biomaterialia, 172, 175–187. https://doi.org/10.1016/j.actbio.2023.10.016
Abstract:
Fast-dissolving microneedles (DMNs) hold significant promise for transdermal drug delivery, offering improved patient compliance, biocompatibility, and functional adaptability for various therapeutic purposes. However, the mechanical strength of the biodegradable polymers used in DMNs often proves insufficient for effective penetration into human skin, especially under high humidity conditions. While many composite strategies have been developed to reinforce polymer-based DMNs, simple mixing of the reinforcements with polymers often results in ineffective penetration due to inhomogeneous dispersion of the reinforcements and the formation of undesired micropores. In response to this challenge, this study aimed to enhance the mechanical performance of hyaluronic acid (HA)-based microneedles (MNs), one of the most commonly used DMN systems. We introduced in situ precipitation of silica nanoparticles (Si) into the HA matrix in conjunction with conventional micromolding. The precipitated silica nanoparticles were uniformly distributed, forming an interconnected network within the HA matrix. Experimental results demonstrated that the mechanical properties of the HA–Si composite MNs with up to 20 vol% Si significantly improved, leading to higher penetration efficiency compared to pure HA MNs, while maintaining structural integrity without any critical defects. The composite MNs also showed reduced degradation rates and preserved their drug delivery capabilities and biocompatibility. Thus, the developed HA–Si composite MNs present a promising solution for efficient transdermal drug delivery and address the mechanical limitations inherent in DMN systems.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the A*STAR - Advanced Manufacturing and Engineering Individual Research Grants (AME IRG)
Grant Reference no. : A1983c0031