Abstract
Color vision deficiency (CVD) or color blindness is one of the ocular disorders dominated in the male population, where the CVD individual faces difficulty in distinguishing the shades of certain colors, and so far, no proper cure is available. Although efforts have been made to improve color recognition with the help of some wearables such as glasses and contact lenses (tinted with dyes to enable wavelength filtering capability), but permanent implants to correct CVD are yet to be explored. Towards providing a permanent solution to CVD patients, an effort has been made to develop 3D printed intraocular lenses (IOLs), using a vat-photopolymerization technique, tinted with Atto 565 dye (wavelength-specific filtering dye), which can be implanted in human eyes. A transparent resin was produced from the combination of poly-2-hydroxyethyl methacrylate (pHEMA), polyethylene glycol diacrylate (PEGDA), and trimethylbenzoyl diphenylphosphine oxide (TPO). While benefiting from the advantages established from the customization of the resin and the 3D printing process, IOLs were 3D printed with and without the tinting dye. The 3D printed IOLs were characterized by optical properties. The dye-tinted IOL was able to successfully block up to 50% of the unwanted wavelength (i.e., 565 nm) and exhibited high transparency for the remaining wavelengths in the visible light spectrum. The lenses also exhibited strong optical focusing property and polarization independent transmission. 3D printed intraocular lenses may be printed as per the patient's needs and requirements; with customised focal lengths and tints to contest the correct CVD type and other eye conditions.
Original language | English (US) |
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Pages (from-to) | 100129 |
Journal | Additive Manufacturing Letters |
Volume | 5 |
DOIs | |
State | Published - Feb 9 2023 |
Bibliographical note
KAUST Repository Item: Exported on 2023-07-17Acknowledgements: The authors acknowledge Sandooq Al Watan LLC and Aldar Properties for the research funding (SWARD Program—AWARD, Project code: 8434000391-EX2020-044). We also acknowledge Khalifa University for the Award No. RCII-2019-003 and KU-KAIST Joint Research Center (Project code: 8474000220-KKJRC-2019-Health1) research funding in support of this research.