Biofabrication of the osteochondral unit and its applications: Current and future directions for 3D bioprinting. (November 2022)

• Record Type: Journal Article
• Authors: Santos-Beato, Patricia; Midha, Swati; Pitsillides, Andrew A; Miller, Aline; Torii, Ryo; Kalaskar, Deepak M
• Is Part Of: Journal of tissue engineering. Volume 13(2022)
• Publication Date: 2022-11
• Subjects: Biofabrication -- osteochondral unit -- cartilage -- bone; Tissue engineering -- Periodicals; 612.028
• DOI: 10.1177/20417314221133480
• Languages: English
• ISSNs: 2041-7314

Abstract

Multiple prevalent diseases, such as osteoarthritis (OA), for which there is no cure or full understanding, affect the osteochondral unit; a complex interface tissue whose architecture, mechanical nature and physiological characteristics are still yet to be successfully reproduced in vitro. Although there have been multiple tissue engineering-based approaches to recapitulate the three dimensional (3D) structural complexity of the osteochondral unit, there are various aspects that still need to be improved. This review presents the different pre-requisites necessary to develop a human osteochondral unit construct and focuses on 3D bioprinting as a promising manufacturing technique. Examples of 3D bioprinted osteochondral tissues are reviewed, focusing on the most used bioinks, chosen cell types and growth factors. Further information regarding the applications of these 3D bioprinted tissues in the fields of disease modelling, drug testing and implantation is presented. Finally, special attention is given to the limitations that currently hold back these 3D bioprinted tissues from being used as models to investigate diseases such as OA. Information regarding improvements needed in bioink development, bioreactor use, vascularisation and inclusion of additional tissues to further complete an OA disease model, are presented. Overall, this review gives an overview of the evolution in 3D bioprinting of the osteochondral unit and its applications, as well as further illustrating limitations and improvements that could be performed explicitly for disease modelling.