Automatic Photo-Cross-Linking System for Robotic-Based In Situ Bioprinting.

Journal: ACS biomaterials science & engineering
PMID:

Abstract

This work reports the design and validation of an innovative automatic photo-cross-linking device for robotic-based in situ bioprinting. Photo-cross-linking is the most promising polymerization technique when considering biomaterial deposition directly inside a physiological environment, typical of the in situ bioprinting approach. The photo-cross-linking device was designed for the IMAGObot platform, a 5-degree-of-freedom robot re-engineered for in situ bioprinting applications. The system consists of a syringe pump extrusion module equipped with eight light-emitting diodes (LEDs) with a 405 nm wavelength. The hardware and software of the robot were purposely designed to manage the LEDs switching on and off during printing. To minimize the light exposure of the needle, thus avoiding its clogging, only the LEDs opposite the printing direction are switched on to irradiate the newly deposited filament. Moreover, the LED system can be adjusted in height to modulate substrate exposure. Different scaffolds were bioprinted using a GelMA-based hydrogel, varying the printing speed and light distance from the bed, and were characterized in terms of swelling and mechanical properties, proving the robustness of the photo-cross-linking system in various configurations. The system was finally validated onto anthropomorphic phantoms (i.e., a human humerus head and a human hand with defects) featuring complex nonplanar surfaces. The designed system was successfully used to fill these anatomical defects, thus resulting in a promising solution for in situ bioprinting applications.

Authors

  • Gabriele Maria Fortunato
    Department of Information Engineering and Research Centre "E. Piaggio", University of Pisa, 56122 Pisa, Italy.
  • Elisa Batoni
    Department of Information Engineering and Research Centre "E. Piaggio", University of Pisa, 56122 Pisa, Italy.
  • Ilenia Pasqua
    Department of Information Engineering and Research Centre "E. Piaggio", University of Pisa, 56122 Pisa, Italy.
  • Matteo Nicoletta
    Department of Information Engineering and Research Centre "E. Piaggio", University of Pisa, 56122 Pisa, Italy.
  • Giovanni Vozzi
    Department of Information Engineering and Research Centre "E. Piaggio", University of Pisa, 56122 Pisa, Italy.
  • Carmelo De Maria
    Department of Information Engineering and Research Centre "E. Piaggio", University of Pisa, 56122 Pisa, Italy.