Precision coating of ocular devices/contact lenses by nanoelectrospray additive printing

Tam, Chak Hin ORCID: https://orcid.org/0000-0001-7380-856X, Alexander, Matthew S. and Qi, Sheng ORCID: https://orcid.org/0000-0003-1872-9572 (2022) Precision coating of ocular devices/contact lenses by nanoelectrospray additive printing. Materials and Design, 219. ISSN 0261-3069

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Abstract

Eye drops are widely used for treating ocular diseases, but with poor bioavailability less than 5%. Drug-eluting contact lenses (DECLs) have been proven to improve the efficacy of treatment. For the manufacturing of DECLs, no method can directly deposit drug formulation on commercial lenses. In this work, a novel additive manufacturing approach, nanoelectrospray (nES), and a custom-built nES printing system was developed to directly deposit drug formulations on the surfaces of commercial contact lenses. As a demonstration, nES was used to coat the model biopolymer, zein, onto commercial lenses. Precise deposition of a ring-shaped polymer layer only on the peripheral region was achieved. For printing optimisation, the spraying width is primarily controlled by the nozzle substrate distance. The coating thickness, which can be used to directly control the drug dose, is subject to the polymer concentration in the formulation, dosing speed and the number of rotations. By using the spray current transient and established scaling law, the predicted spray volume is highly correlated to the experimental results. This study built a firm technological foundation for using nES as a novel additive manufacturing method to produce DECLs with drug coating at the surfaces of contact lenses in pre-defined patterns and locations.

Item Type: Article
Faculty \ School: Faculty of Science > School of Pharmacy
Faculty of Science > School of Engineering
UEA Research Groups: Faculty of Science > Research Groups > Pharmaceutical Materials and Soft Matter
Depositing User: LivePure Connector
Date Deposited: 24 May 2022 15:03
Last Modified: 02 Sep 2023 01:17
URI: https://ueaeprints.uea.ac.uk/id/eprint/85119
DOI: 10.1016/j.matdes.2022.110782

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