Translational Application of 3D Bioprinting for Cartilage Tissue Engineering
TL;DR: In this paper, the authors provide an insight into the current developments in 3D bioprinting for cartilage tissue engineering, highlighting the bioink and construct properties required for successful application in cartilage repair applications.
Abstract: Cartilage is an avascular tissue with extremely limited self-regeneration capabilities. At present, there are no existing treatments that effectively stop the deterioration of cartilage or reverse its effects; current treatments merely relieve its symptoms and surgical intervention is required when the condition aggravates. Thus, cartilage damage remains an ongoing challenge in orthopaedics with an urgent need for improved treatment options. In recent years, major advances have been made in the development of three-dimensional (3D) bioprinted constructs for cartilage repair applications. 3D bioprinting is an evolutionary additive manufacturing technique that enables the precisely controlled deposition of a combination of biomaterials, cells, and bioactive molecules, collectively known as bioink, layer-by-layer to produce constructs that simulate the structure and function of native cartilage tissue. This review provides an insight into the current developments in 3D bioprinting for cartilage tissue engineering. The bioink and construct properties required for successful application in cartilage repair applications are highlighted. Furthermore, the potential for translation of 3D bioprinted constructs to the clinic is discussed. Overall, 3D bioprinting demonstrates great potential as a novel technique for the fabrication of tissue engineered constructs for cartilage regeneration, with distinct advantages over conventional techniques.
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TL;DR: In this paper , a review of different machine learning algorithms for tissue engineering applications is presented, with a particular focus on their use in optimising 3D bioprinting processes for tissue-engineered construct fabrication.
Abstract: Optimisation of tissue engineering (TE) processes requires models that can identify relationships between the parameters to be optimised and predict structural and performance outcomes from both physical and chemical processes. Currently, Design of Experiments (DoE) methods are commonly used for optimisation purposes in addition to playing an important role in statistical quality control and systematic randomisation for experiment planning. DoE is only used for the analysis and optimisation of quantitative data (i.e., number-based, countable or measurable), while it lacks the suitability for imaging and high dimensional data analysis. Machine learning (ML) offers considerable potential for data analysis, providing a greater flexibility in terms of data that can be used for optimisation and predictions. Its application within the fields of biomaterials and TE has recently been explored. This review presents the different types of DoE methodologies and the appropriate methods that have been used in TE applications. Next, ML algorithms that are widely used for optimisation and predictions are introduced and their advantages and disadvantages are presented. The use of different ML algorithms for TE applications is reviewed, with a particular focus on their use in optimising 3D bioprinting processes for tissue-engineered construct fabrication. Finally, the review discusses the future perspectives and presents the possibility of integrating DoE and ML in one system that would provide opportunities for researchers to achieve greater improvements in the TE field.
10 citations
TL;DR: In this paper , the influence of nanoparticles on the biological and mechanical performances of 3D-printed tissue scaffolds has been analyzed in functional clinical settings including wound dressing, drug delivery systems, medical implants and tissue engineering.
8 citations
TL;DR: An extracellular matrix particle-based biomaterial ink is developed which can be extruded, polymerizes via disulfide bonding, and restores layered tissue structure and surface lubrication and shows that two inks can be co-printed to create a layered cartilage scaffold with bulk compressive and surface mechanics approaching values measured on native cartilage.
Abstract: Articular cartilage is a layered tissue with a complex, heterogeneous structure and lubricated surface which is challenging to reproduce using traditional tissue engineering methods. Three-dimensional printing techniques have enabled engineering of complex scaffolds for cartilage regeneration, but constructs fail to replicate the unique zonal layers, and limited cytocompatible crosslinkers exist. To address the need for mechanically robust, layered scaffolds, we developed an extracellular matrix particle-based biomaterial ink (pECM biomaterial ink) which can be extruded, polymerizes via disulfide bonding, and restores layered tissue structure and surface lubrication. Our cartilage pECM biomaterial ink utilizes functionalized hyaluronan (HA), a naturally occurring glycosaminoglycan, crosslinked directly to decellularized tissue particles (ø40–100 µm). We experimentally determined that HA functionalized with thiol groups (t-HA) forms disulfide bonds with the ECM particles to form a 3D network. We show that two inks can be co-printed to create a layered cartilage scaffold with bulk compressive and surface (friction coefficient, adhesion, and roughness) mechanics approaching values measured on native cartilage. We demonstrate that our printing process enables the addition of macropores throughout the construct, increasing the viability of introduced cells by 10%. The delivery of these 3D printed scaffolds to a defect is straightforward, customizable to any shape, and adheres to surrounding tissue.
6 citations
3 citations
TL;DR: The potential of biomaterials to overcome challenges associated with cell therapy, particularly cellular function and longevity, has been discussed in this article , focusing on emerging 3D bioprinting technologies.
Abstract: The promise of cell therapy has been augmented by introducing biomaterials, where intricate scaffold shapes are fabricated to accommodate the cells within. In this review, we first discuss cell encapsulation and the promising potential of biomaterials to overcome challenges associated with cell therapy, particularly cellular function and longevity. More specifically, cell therapies in the context of autoimmune disorders, neurodegenerative diseases, and cancer are reviewed from the perspectives of preclinical findings as well as available clinical data. Next, techniques to fabricate cell-biomaterials constructs, focusing on emerging 3D bioprinting technologies, will be reviewed. 3D bioprinting is an advancing field that enables fabricating complex, interconnected, and consistent cell-based constructs capable of scaling up highly reproducible cell-biomaterials platforms with high precision. It is expected that 3D bioprinting devices will expand and become more precise, scalable, and appropriate for clinical manufacturing. Rather than one printer fits all, seeing more application-specific printer types, such as a bioprinter for bone tissue fabrication, which would be different from a bioprinter for skin tissue fabrication, is anticipated in the future.
2 citations
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TL;DR: 3D bioprinting is being applied to regenerative medicine to address the need for tissues and organs suitable for transplantation and developing high-throughput 3D-bioprinted tissue models for research, drug discovery and toxicology.
Abstract: Additive manufacturing, otherwise known as three-dimensional (3D) printing, is driving major innovations in many areas, such as engineering, manufacturing, art, education and medicine. Recent advances have enabled 3D printing of biocompatible materials, cells and supporting components into complex 3D functional living tissues. 3D bioprinting is being applied to regenerative medicine to address the need for tissues and organs suitable for transplantation. Compared with non-biological printing, 3D bioprinting involves additional complexities, such as the choice of materials, cell types, growth and differentiation factors, and technical challenges related to the sensitivities of living cells and the construction of tissues. Addressing these complexities requires the integration of technologies from the fields of engineering, biomaterials science, cell biology, physics and medicine. 3D bioprinting has already been used for the generation and transplantation of several tissues, including multilayered skin, bone, vascular grafts, tracheal splints, heart tissue and cartilaginous structures. Other applications include developing high-throughput 3D-bioprinted tissue models for research, drug discovery and toxicology.
4,841 citations
TL;DR: The extracellular matrix is the non-cellular component present within all tissues and organs, and provides not only essential physical scaffolding for the cellular constituents but also initiates crucial biochemical and biomechanical cues that are required for tissue development.
Abstract: ![Figure][1]
The extracellular matrix (ECM) is the non-cellular component present within all tissues and organs, and provides not only essential physical scaffolding for the cellular constituents but also initiates crucial biochemical and biomechanical cues that are required for tissue
3,190 citations
TL;DR: The functional requirements, and types, of materials used in developing state of the art of scaffolds for tissue engineering applications are described and where future research and direction is required are described.
2,648 citations
TL;DR: The unique and complex structure of articular cartilage makes treatment and repair or restoration of the defects challenging for the patient, the surgeon, and the physical therapist.
Abstract: Articular cartilage is the highly specialized connective tissue of diarthrodial joints. Its principal function is to provide a smooth, lubricated surface for articulation and to facilitate the transmission of loads with a low frictional coefficient (Figure 1). Articular cartilage is devoid of blood vessels, lymphatics, and nerves and is subject to a harsh biomechanical environment. Most important, articular cartilage has a limited capacity for intrinsic healing and repair. In this regard, the preservation and health of articular cartilage are paramount to joint health.
Figure 1.
Gross photograph of healthy articular cartilage in an adult human knee.
Injury to articular cartilage is recognized as a cause of significant musculoskeletal morbidity. The unique and complex structure of articular cartilage makes treatment and repair or restoration of the defects challenging for the patient, the surgeon, and the physical therapist. The preservation of articular cartilage is highly dependent on maintaining its organized architecture.
1,835 citations
TL;DR: The versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function are shown.
Abstract: The ability to print and pattern all the components that make up a tissue (cells and matrix materials) in three dimensions to generate structures similar to tissues is an exciting prospect of bioprinting. However, the majority of the matrix materials used so far for bioprinting cannot represent the complexity of natural extracellular matrix (ECM) and thus are unable to reconstitute the intrinsic cellular morphologies and functions. Here, we develop a method for the bioprinting of cell-laden constructs with novel decellularized extracellular matrix (dECM) bioink capable of providing an optimized microenvironment conducive to the growth of three-dimensional structured tissue. We show the versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function. We achieve high cell viability and functionality of the printed dECM structures using our bioprinting method.
1,401 citations