3D-printed organs are a biopunk’s dream and which may soon come true thanks to researchers from the University of California, San Diego.
Led by Shaochen Chen, the team of nanoengineers developed a new method for 3D printing biomimetic blood vessel networks, which may help lay the foundation for functioning lab-grown tissue and organs.
Artificial blood vessel networks — which help transport nutrients, blood, and waste — have been 3D printed by other researcher labs in the past, though these methods have proven to be time-consuming and expensive. In his research, Chen sought to make the process faster and cheaper and to develop a network sophisticated enough to be integrated with the human body.
“We used hydrogel biomaterials that are biocompatible for potential clinical uses,” he told Digital Trends.
To make the vessels more efficiently, Chen and his team used multiple cell types and a new 3D-printing method they developed themselves.
Their first steps were to develop a 3D model of the blood vessel network on a computer, which then converts the model into a series of 2D images and transfers these images to millions of microscopic mirrors. The mirrors use ultraviolet (UV) light to reflect the images onto a mixture of live cells and polymers that solidify upon contact with the UV light. As the 2D images are solidified, one after another, the 3D structure begins to take shape.
While traditional techniques may take hours to complete, the UC San Diego lab can complete the task in just a few seconds, according to the researchers, who published a paper detailing their study in the journal Biomaterials.
So far, the researchers have been able to graft the 3D-printed tissue into the skin wounds of mice. After two weeks, they analyzed the wounds again and saw that the lab-grown tissue had successfully integrated into the host’s blood vessel network.
A startup called Allegro 3D is working to commercialize this technique, while Chen and his team are looking to optimize the conditions for growing fully functioning blood vessel networks for clinical applications.
