The laws of physics replace trial and error in new approaches to bioimpression

3D printers can be used to create a variety of useful objects by creating a layer-by-layer shape. Scientists have used this same technique to "bioprint" living tissue, including muscles and bones.

Bio-printing is a relatively new technology that has progressed mainly through trial and error. Scientists are now using the laws of physics and predictive computer modeling to improve these techniques and optimize the bio-printing process. These new developments are discussed in the June 4 issue of Applied Physics Reviews.

The most widely used bioprinters are extrusion, jet and laser printers. Each type involves a slightly different physics, and each has its own advantages and disadvantages.

Ashkan Shafiee, co-author, "The only way to achieve a meaningful transition from the trial and error phase to the" predict and control "phase of bio-printing is to understand and apply the underlying physics. core. "

An extrusion printer loads a material, called bioink, into a syringe and prints it by forcing the ink with a plunger or pneumatic pressure. The bioink can be a set of pure living cells or a cell suspension in a hydrogel or a polymer. Inkjet bioprinters work the same way, but they use either a piezoelectric crystal or a heater to create droplets from a small aperture. Laser printers focus a laser beam on a ribbon, in which a thin layer of bioink is extended, allowing for high cell viability.

Organic products created by bio-printing are not usually immediately usable. Although the printer can create an initial configuration of cells, they multiply and reassemble in a new configuration. The process is similar to what happens when an embryo develops, and the cells fuse with other cells and sort themselves into new regions.

Computer modeling techniques were developed in the mid-2010s to optimize the self-assembly stage of bio-printing after printing, during which small tissue fragments are introduced. in a support material having the desired shape of the biological structure, such as an organ, with bioink. The small fragments then develop and automatically assemble into the final biological structure.

The model includes equations describing the forces of attraction and repulsion between cells. The authors have shown that simulations using this method, known as cellular particle dynamics or CPD, correctly predict the assembly pattern of a group of cells after the step of. initial impression.