3D printing of multi-material and multifunctional contact lenses

Abstract

3D printing plays a crucial role in medical engineering and has seen continuous growth recently. It provides significant benefits across various applications, from prostheses and soft implants to tissue-engineering matrices. Hydrogel-based soft contact lenses are common products used for cosmetic purposes or vision correction, usually made from customized hydrogel composites that offer high water content for comfort, softness, and oxygen permeability. A popular research area involves functionalizing contact lens surfaces with dyes, coatings, and nanoparticles to improve optical filtering, enable self-hydration, and enhance antioxidant, antibacterial, and drug delivery functions.

Additive manufacturing (also called 3D printing) allows for versatile production of custom contact lenses with specific shapes, sizes, and spectral features [1, 2]. Successful 3D printing of contact lenses depends on carefully optimizing many parameters, such as exposure time, layer thickness, resin composition, and post-processing. To aid this process, AI models were trained to inversely design the lenses' optical properties by linking resin types, dye levels, lens geometry, and optical transmission spectra. The Multilayer Perceptron outperformed other models in predicting resin compositions from optical spectra, while the Random Forest model excelled at reconstructing spectra from known resin inputs.

The optical transmission characteristics of the AI-engineered 3D-printed contact lenses matched the predictions from the machine learning models. This research shows that combining machine learning with material analysis allows for data-driven design of 3D-printed wearable photonic devices, providing both mechanical stability and customizable spectral features. It opens the door for future digital manufacturing of personalized wearable devices.