The inaugural successful transplant of an artificial cornea, entirely fabricated via 3D bioprinting, took place in Israel. This procedure restored vision to a blind individual, as reported by the Rambam Eye Institute. The implant was printed using donor cells, leveraging technology developed by the American-Israeli firm Precise Bio.
This novel cornea was constructed layer by layer, meticulously replicating the natural anatomy of the human eye: the epithelium, stroma, and endothelium. The process involved a collagen gel infused with cultured cells. Following the printing stage, the implant was matured in a bioreactor, achieving the required levels of optical clarity and mechanical strength.
“The methodology employs a highly precise 3D bioprinter to sequentially construct the three-dimensional architecture of the cornea using stratified layers of collagen hydrogel containing living cells,” stated the institute’s release.
The surgery duration was between one and two hours, standard for this type of intervention. Due to the complete biocompatibility of the components, the patient’s body showed no signs of rejecting the implant, eliminating the need for immunosuppressive drugs. Visual acuity started to return within weeks following the operation, with no complications observed.
The primary benefit of this innovation lies in addressing the severe shortage of donor tissue. A single donor cornea’s cells possess the capacity to yield up to 300 new prints, offering the prospect of eradicating years-long waiting lists for transplants.
This Israeli milestone paves the way for eventual mass production not only of corneas but potentially other complex organs such as hearts, livers, and kidneys. This development builds upon foundational research originating from the UK’s Newcastle University. Earlier, “Zhukovsky.Life” covered a different high-tech venture in healthcare: Perm-based scientists engineered a simulated patient robot designed to train clinicians in hypertension diagnosis. This interactive simulator, which utilizes machine learning algorithms, has shown an 11% improvement in effectiveness over conventional medical training modalities.
About the Author
