3D Bioprinting of Cornea Mimetic Lenticules: Comparing pneumatic extrusion and digital light processing (DLP) methods

Abstract

Purpose : Worldwide 28 million people are affected by corneal blindness and there is only 1 donor cornea tissue available among 70 in the waiting list. The disadvantages of corneal transplantation have necessitated development of engineered cornea, where the three-dimensional (3D) bioprinted products hold immense potential. The advancement in 3D-bioprinting field has led to multiple techniques which provide different levels of success in producing a cornea lenticule mimicking several aspects of native cornea.

Methods : We produced cornea lenticule using two unique bioprinting techniques, extrusion and digital light processing (DLP). The study covers a comparative evaluation of the bioink, process parameters and properties of the bioprinted lenticule. The bioprinted cornea lenticules were evaluated via various physico-chemical characterization involving light transmittance, mechanical stability, and in-vitro studies like epithelialization support, viability and phenotypic evaluation with human corneal stromal cells.

Results : Viscosity of the bioink played a pivotal role in printability of the lenticules in extrusion based bioprinting, whereas in DLP, the process parameters like layer height, exposure time and photo-crosslinker were the key factors. Extrusion based printing required a support bed for printing and resolution of 200 µm, while the DLP provided better resolution (50 µm precision). Optimizing various parameters, we obtained lenticules with cornea mimetic properties, with 85% or more transparency, less than 30% swelling and modulus matching the native cornea stroma. The bioinks and bioprinting process were also compatible with corneal epithelial and stromal cells.

Conclusions : We studied extrusion and DLP techniques to bioprint human cornea mimetic lenticule, which can be applied in sutureless manner. The overall resolution of DLP printed lenticules were better, yet the technique requires more comprehensive hold over the parameters.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.