3D bioprinted organ‐on‐chips

AggregateEarly View e197 REVIEWOpen Access 3D bioprinted organ-on-chips Sajjad Rahmani Dabbagh, Sajjad Rahmani Dabbagh orcid.org/0000-0001-8888-6106 Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, Turkey Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Sariyer, Istanbul, Turkey Koc University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul, TurkeySearch for more papers by this authorMisagh Rezapour Sarabi, Misagh Rezapour Sarabi Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, TurkeySearch for more papers by this authorMehmet Tugrul Birtek, Mehmet Tugrul Birtek Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, TurkeySearch for more papers by this authorNur Mustafaoglu, Nur Mustafaoglu Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Istanbul, TurkeySearch for more papers by this authorYu Shrike Zhang, Corresponding Author Yu Shrike Zhang yszhang@research.bwh.harvard.edu orcid.org/0000-0002-0045-0808 Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, Massachusetts, USA Correspondence Savas Tasoglu, Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey. Email: stasoglu@ku.edu.tr Yu Shrike Zhang, Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA. Email: yszhang@research.bwh.harvard.eduSearch for more papers by this authorSavas Tasoglu, Corresponding Author Savas Tasoglu stasoglu@ku.edu.tr orcid.org/0000-0003-4604-217X Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, Turkey Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Sariyer, Istanbul, Turkey Koc University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul, Turkey Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany Correspondence Savas Tasoglu, Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey. Email: stasoglu@ku.edu.tr Yu Shrike Zhang, Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA. Email: yszhang@research.bwh.harvard.eduSearch for more papers by this author Sajjad Rahmani Dabbagh, Sajjad Rahmani Dabbagh orcid.org/0000-0001-8888-6106 Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, Turkey Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Sariyer, Istanbul, Turkey Koc University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul, TurkeySearch for more papers by this authorMisagh Rezapour Sarabi, Misagh Rezapour Sarabi Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, TurkeySearch for more papers by this authorMehmet Tugrul Birtek, Mehmet Tugrul Birtek Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, TurkeySearch for more papers by this authorNur Mustafaoglu, Nur Mustafaoglu Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Istanbul, TurkeySearch for more papers by this authorYu Shrike Zhang, Corresponding Author Yu Shrike Zhang yszhang@research.bwh.harvard.edu orcid.org/0000-0002-0045-0808 Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, Massachusetts, USA Correspondence Savas Tasoglu, Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey. Email: stasoglu@ku.edu.tr Yu Shrike Zhang, Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA. Email: yszhang@research.bwh.harvard.eduSearch for more papers by this authorSavas Tasoglu, Corresponding Author Savas Tasoglu stasoglu@ku.edu.tr orcid.org/0000-0003-4604-217X Department of Mechanical Engineering, Koç University, Sariyer, Istanbul, Turkey Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Sariyer, Istanbul, Turkey Koc University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul, Turkey Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany Correspondence Savas Tasoglu, Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey. Email: stasoglu@ku.edu.tr Yu Shrike Zhang, Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA 02139, USA. Email: yszhang@research.bwh.harvard.eduSearch for more papers by this author First published: 01 May 2022 https://doi.org/10.1002/agt2.197AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Organ-on-a-chip (OOC) platforms recapitulate human in vivo-like conditions more realistically compared to many animal models and conventional two-dimensional cell cultures. OOC setups benefit from continuous perfusion of cell cultures through microfluidic channels, which promotes cell viability and activities. Moreover, microfluidic chips allow the integration of biosensors for real-time monitoring and analysis of cell interactions and responses to administered drugs. Three-dimensional (3D) bioprinting enables the fabrication of multicell OOC platforms with sophisticated 3D structures that more closely mimic human tissues. 3D-bioprinted OOC platforms are promising tools for understanding the functions of organs, disruptive influences of diseases on organ functionality, and screening the efficacy as well as toxicity of drugs on organs. Here, common 3D bioprinting techniques, advantages, and limitations of each method are reviewed. Additionally, recent advances, applications, and potentials of 3D-bioprinted OOC platforms for emulating various human organs are presented. Last, current challenges and future perspectives of OOC platforms are discussed. 1 INTRODUCTION One of the great constraints toward therapeutical practices is that most of the available reported approaches for medical trials have been performed in animal models (e.g., mice) or static two-dimensional (2D) cell-culture phantoms. However, animal testing faces challenges due to its low throughput, lack of cost-effectiveness (feeding, housing, and animal care costs), ethical concerns, differences in target homology, and dissimilarities in physiology, resulting in therapeutic strategies with affirmative effects in animal models while oftentimes not achieving the same outcome in humans.[1-5] For instance, the majority of mouse models studied for the treatment of coronavirus disease 2019 (COVID-19), a worldwide pandemic, failed to illuminate all facets in humans, particularly unfamiliar futures such as pulmonary vascular disease and hyperinflammatory syndromes.[6] On the other hand, despite their simplicity in culture, effectiveness, and widespread use in research, 2D cell cultures face challenges in controlling cell culture structure, in mimicking cell–cell interactions and biochemical signals, as well as in modeling mechanical microenvironments of real tissues and cell polarity, since the 2D microenvironment has limitations in representing the physiological conditions of the human body in most cases.[2, 7-11] Recent studies have attempted to address a number of the above challenges such as shape control using microwells[12] as well as micropillars,[13] and cell polarization effects using a sandwich culture method[11, 14-16] (i.e., adding an extracellular matrix (ECM) layer over cells to eliminate apical-basal polarity).[11] Nevertheless, 2D cultures are generally considered to be limited in sufficiently mimicking in vivo conditions. Compared with 2D cultures, 3D cell cultures more realistically recapitulate the complex structures of human tissues by allowing cells to cluster, migrate, polarize, and expand, while regenerating in vivo-like cell signaling pathways, functions, and drug responses by simulating the hindering effect of ECM and/or outer layer of cells on the diffusion of drug molecules in vivo.[17-21] However, conventional 3D cultures cannot replicate the dynamic microenvironment of the human body, such as biofluid flow (e.g., blood and lymphatic fluid for waste removal, nutrient supply, and drug transport), spatiotemporal oxygen distribution, and mechanical stresses experienced by cells during respiration and heartbeat.[18, 22]. An alternative perspective to overcome these challenges can be demonstrated by the use of organ-on-a-chip (OOC) platforms based on human cells.[23] This eccentric approach, with its innovative ability to provide insights into real-world human organ functionality and disease pathophysiology, along with a more accurate prediction of efficacy and potential side effects of a new drug or therapeutic practice, offers valuable integration into translational science and regenerative medicine.[11] The use of cell culture for disease studies in vitro dates back to 1991, when one of the first papers in this context was published discussing organized cell culture for the construction of ventricular myocardium, which allowed the biophysical elucidation of conduction block in the heart.[24, 25] In 2004, the concept of mimicking human physiology on a microfluidic chip was introduced to study the systemic interaction between liver and lung on a silicon chip.[26, 27] The term “organ-on-chip” was first coined in 2010 for a microfluidic chip used to study the human lung at the organ level.[28] OOC systems are convenient, versatile means of mimicking the functions of various organs of the human body with the ability to be seeded with human cells to create patient-specific, multicellular setups for conducting personalized medicine research and an environment for studying realistic organ interactions with proposed therapeutic approaches.[29-34] The main advantages offered by microchannels, chambers, valves, and pumps, for cell culture, may include perfusability and possible gas permeability (which increase cell viability and metabolic rate), transparency (which enables microscopic imaging),[35, 36] integrability with sensors (which allows real-time screening of culture, biomarkers, and responses to stimuli),[37, 38] gradient generation as a result of laminar flow in microchannels (which enables the study of differentiation and directed cell migration), porous membranes (modeling tissue barrier functions, transcellular transport, secretion, and absorption), cost-efficiency (lower volume of expensive samples/reagents due to microscale channels), sophisticated structures (wide range of manufacturable geometries on microfluidic chips), mimicking of dynamic in vivo conditions (emulating cyclic mechanical stress and strain experienced by cells during peristalsis, respiration, and cardiovascular cycling), and/or single-cell analysis.[5, 10, 29] Conventional OOC fabrication approaches (e.g., soft lithography, microcontact printing, and replica molding[39, 40]) usually require cleanrooms, a high level of microfabrication expertise,[41, 42] a secondary cell-seeding step (resulting in intense protein absorption), and have problems implementing cell–cell and cell–ECM interactions to emulate spatial heterogeneity.[8] Among the various approaches for fabrication of OOCs, 3D (bio)printing has the potential to provide a fabrication method for simultaneous/consecutive generation of sophisticated structures of ECMs and cells (e.g., patient-derived cells) with a fast turn-around time as well as great freedom to modify the chip design.[2, 43] It is expected that the 3D bioprinting market for the medical and healthcare sectors will increase at a compound annual growth rate (CAGR) of 14.5% from 2021 to 2028, reaching revenue of up to $4.4 billion in 2028.[44] Bioprinting is a branch of the well-known 3D printing process in which a computer-aided design (CAD) is processed, typically in a layer-by-layer manner, to complete the structure of the product using solidifiable biomaterial, including but not limited to ion-crosslinkable, temperature-sensitive, and photopolymer bioinks.[45, 46] Valve-based[47] and inkjet-based,[48-50] acoustic,[51, 52] microextrusion,[53-55] and light-enabled[56-58] bioprinting are commonly used technologies.[59] Over the years, 3D printing has successfully contributed to the fabrication of medical devices,[60-64] sensors,[65] tissue scaffolds,[66] and microfluidic chips[67-69] for sensing, gradient generation, chemical mixing, tissue engineering, and OOC applications.[8] Although cells are not usually present in 3D printing, the use of cytocompatible biomaterials enables 3D bioprinters to directly print with cells; alternatively, cells can be bioprinted without additional biomaterials.[70] Integrating the advantages of microfluidic chips (e.g., gas permeability, perfusion, and single-cell analysis) with 3D bioprinting can lead to automated bioprinting of reproducible, precisely positioned, and perfused multicell cultures, with customized structure/features (e.g., pore size and morphology), for physiological studies as well as drug analysis at the organ level,[71] such as kidney-,[72, 73] heart/vasculature-,[74-76] liver-,[77] brain/blood–brain barrier (BBB)-,[78-81] bone/cartilage-,[82, 83] cancer/tumor-,[84, 85] placenta-,[86] gut-,[87] and lung-[88] on-chips. Here, we review recent advances in 3D-bioprinted OOCs. First, the different bioprinting technologies are presented, as well as the advantages and disadvantages of each process. In addition, bioinks and cell sources used in these methods are discussed. Subsequently, examples of 3D-bioprinted OOCs are reviewed, as shown in Figure 1, including applications of OOCs in the cardiovascular system, brain and BBB, lung and respiratory system, liver, gut, renal system, breast, bone and cartilage system, and skin studies, highlighting the design features, advantages, and limitations of the cases studied. Finally, challenges and future research areas are presented. FIGURE 1Open in figure viewerPowerPoint Organ-on-chip (OOC) systems are convenient, versatile means for mimicking the functions of different organs of the human body. Human cells from various organs of the body can be isolated to create cell encapsulated bioinks for 3D bioprinting of OOCs. This procedure leads to patient-specific, multicell setups for conducting personalized medicine research and an environment to study realistic organ interactions with the proposed therapy approaches, which enables the required beforehand tests for clinical practice. Various applications of 3D-bioprinted OOCs are reported, including heart and vascular system, brain and blood–brain barrier (BBB), lung and airways, liver, gut, renal system, bone and cartilage, skin, and breast 2 FABRICATION 2.1 Bioprinting The conventional fabrication techniques of OOCs include photolithography, soft lithography,[89-91] replica molding,[92] capillary molding,[89] microcontact printing,[92] microtransfer molding,[89] and injection molding.[93-95] One of the limitations of the above methods is the limited fabrication capability for forming the complex structures of organs and tissues.[96, 97] On the other hand, these methods usually require multistep production protocols. In particular, lithographic techniques need to be carried out through several lithographic processes and masks.[29, 96, 98] This leads to experiments that are time consuming and expensive. In addition, the traditional methods require a secondary organization for the cell seeding process, which oftentimes drives up the overall cost, as well as poor selectivity of different cell types. The adoption of 3D printing and 3D bioprinting in medical and biomedical applications has resulted in cost efficiency, rapid turnaround times, and a wide range of materials.[99-103] Moreover, prototyping of OOCs with 3D bioprinting requires minimal microfabrication skills and enables simultaneous/consecutive (bio)printing of polymers, hydrogels, and multiple cell types to produce customized, reproducible, perfusable, and complex patient-specific 3D biomimetic tissue constructs with high precision in the placement of cells,[8, 29, 43, 96] which is hardly achievable with the conventional techniques. 3D bioprinting techniques can be primarily divided into two categories (Figure 2): (i) nozzle-based (e.g., inkjet-based (droplet-based) and extrusion-based bioprinting) and (ii) light-enabled bioprinting (e.g., stereolithography apparatus (SLA)-/digital light processing (DLP)-based bioprinting, two-photon polymerization (TPP)-based bioprinting, laser-assisted bioprinting, and computed axial lithography).[104-106] A summary of the advantages, limitations, and important properties of the commonly used 3D bioprinting methods is shown in Table 1. FIGURE 2Open in figure viewerPowerPoint Schematic illustrations of common 3D bioprinting strategies. (A) Extrusion-based bioprinting. (B) Inkjet-based bioprinting. (C) Digital light processing (DLP)-based bioprinting. (D) Two-photon polymerization (TPP)-based bioprinting. (E) Laser-assisted bioprinting.[104] Reproduced with permission from Ref. [104] TABLE 1. Summary of properties of commonly used 3D bioprinting methods for OOC applications. Descriptions are general and may not speak to all specific bioprinter and bioprinting configurations Method Extrusion-based bioprinting Inkjet bioprinting Stereolithography-based bioprinting (SLA, DLP) Multiphoton-based bioprinting Laser-based bioprinting Working principle Pneumatic, mechanical, microfluidics-assisted Thermal, piezoelectric, electrostatic Point-by-point exposure (SLA), layer-by-layer exposure (DLP) Point-by-point exposure by a light beam Laser-induced Printable viscosity 30 to 6 × 107 mPa · s[104] 3–12 mPa · s[104] 1-1,000 mPa · s[333] – 1–300 mPa · s[71, 334] Cell density High[334] Low[334] Medium[334] Medium Medium[334] Print speed Medium[72, 335] High[335] Medium to high[71] High High Resolution >100 μm[118] >10 μm[141] >6–10 μm[71] >100 nm[336] >50–100 μm[337] Cell viability >90%[115] >85%[338] ∼80%[144] >90%[152] >90%[58, 154] Advantages Affordability, large deposition rate, bioprintability of high viscosity bioinks with high cell concentration, simultaneous bioprinting, scalability[72, 118] Affordability, good resolution, fast bioprinting, the ability to generate a cell concentration gradient[71, 334] High resolution, oftentimes high speed, no clogging problem, bioinks with high cell concentration can be bioprinted[71, 334] High resolution, multidirectional bioprinting, good viability[336] High resolution (single cell per droplet), high cell viability, no clogging, ability to bioprint low-viscosity bioinks with high cell density[334, 337] Limitations High shear stress, nozzle clogging, low resolution, low structural fidelity, limited material choice (only materials with shear-thinning property)[72, 118] High-viscosity bioink cannot be bioprinted, limited vertical bioprinting, clogging, shear stress, additional cross-linking step is required for low viscosity bioinks[71, 334] Limited choice of photosensitive material, Possibility of cell lysis or DNA damage, expensive equipment[71, 334] High cost, limited biomaterial choice, near-infrared transparency requirement, low bioprinting speed[336] High cost, cytotoxicity induced by metallic nanoparticles, photonic cell damage, complex control of laser pulses[334, 337] 2.1.1 Nozzle-based methods The working principle of nozzle-based bioprinting is based on the ejection of bioink through a nozzle by applying a force field.[107] As one of the most studied and available types of bioprinting, nozzle-based bioprinting is a low-cost method with a moderate resolution and longer processing times compared with optical methods.[108, 109] In nozzle-based bioprinting, the amount of shear stress experienced by the bioink, along with temperature, are the major factors that threaten cell viability and limit the applicability of nozzle-based bioprinting for cell/tissue bioprinting.[110, 111] Nozzle-based bioprinting methods can be classified into extrusion-based and droplet-based methods. Droplet-based methods can be further divided into microvalve-based bioprinting, acoustic droplet bioprinting, inkjet bioprinting (continuous inkjet (CIJ), drop-on-demand (DoD) (thermal, piezoelectric, and electrostatic)), and electrohydrodynamic jetting.[71] 2.1.1.1 Extrusion-based bioprinting In extrusion-based 3D bioprinting, the bioink is typically placed in a syringe-like tool that uses a controlled force—pneumatic pressure or mechanical force generated by a piston or screw—to propel the bioink through the nozzle[112-114] (Figure 2A). This bioprinting technique can deposit highly viscous bioinks with high cell concentrations at a large deposition rate. Moreover, multinozzle extrusion bioprinters enable the simultaneous deposition of heterogeneous structures. However, the resolution of this method is usually limited. In extrusion bioprinting, the main factor affecting cell viability is the shear stress acting on the bioink, which depends on the viscosity of the bioink, nozzle dimension, and printing pressure.[115] Although printing resolution can be increased by smaller nozzles, a decrease in nozzle diameter results in higher shear stress (i.e., lower cell viability) and nozzle clogging. Besides, the use of highly viscous bioinks or a high flow rate of bioink in the nozzle can also increase shear stress. Another limitation is that the bioink used in extrusion-based bioprinters should ideally have a shear-thinning property, which limits the choice of bioink.[109, 116] Furthermore, depending on the used bioink, the constructs bioprinted by extrusion-based methods may suffer from low structural fidelity and undesirable deformation in long-term cultures due to the junctional seams and voids created by line-by-line deposition of the cylindrical filaments.[117] A multihead extrusion bioprinting system, with a resolution of 50 μm, was developed for bioprinting human tissues using cell-loaded hydrogels through a 300-μm Teflon nozzle at a pressure of 50–80 kPa, yielding >90% cell viability for bioprinting bone, cartilage, and muscle tissues.[118] In another experiment, using four autonomously addressable printheads (with diameters of 100–410 μm), a perfusable tissue (with >95% cell viability) was bioprinted on a chip at printing speeds ranging from 1 mm/s to 5 cm/s respective to air pressures ranging from 10 to 140 psi.[119] To study the effects of bioink viscosity on bioprinted tissue, a bioprinter with a painting needle was designed to bioprint cardiac tissue on a chip with ∼92% cell viability using bioinks with viscosities ranging from 1 to 1 × 105 mPa · s. The setup was fast (extruding up to once every 0.1 s) with precise control over the volume of extruded bioink (several hundred nl to several pl). By controlling the number of ladened cells by altering the time and diameter of the painting needle, a high-density (3.5 × 108 cells/cm3) 3D cardiac tissue was bioprinted.[120] Integration of microfluidic printheads with extrusion-based bioprinters can miniaturize shear stress and promote cell viability.[111] The microfluidic printhead enables simultaneous extrusion of bioink and crosslinker, while sheathing cells by crosslinker on either side, creating a shear stress-protective layer between the nozzle wall and cells during the extrusion process.[111] In another study, neural constructs were coaxially bioprinted by separate micropumping of crosslinker and bioink. Using 3–5 μl of bioink, cell layers of 100 μl were bioprinted at a speed of 240 mm/min.[121] Extrusion-based bioprinting represents a convenient, intensively explored rapid prototyping platform with reasonable resolutions and costs (in the abovementioned studies, although cells were not necessarily bioprinted on a chip, the achieved bioprinting resolution demonstrates the potency of these methods for the fabrication of 3D-bioprinted OOC platforms in the future). 2.1.1.2 Inkjet bioprinting Inkjet bioprinting has been largely adapted from commercial inkjet printers, making it available in affordable price ranges. The bioink is filled into a chamber that has a nozzle (inkjet heads) and an actuation mechanism, which can be a thermal,[122] piezoelectric,[123] or electrostatic,[124] mechanism (Figure 2B). Two main categories of inkjet bioprinters are CJI and DoD. Although both deposit droplets of bioink on the surface, CIJ creates a stream of bioink droplets by forming Rayleigh-Plateau instability,[125] which limits the precise control of droplet position.[126] On the other hand, DoD inkjet bioprinters produce droplets only when the discharge signal is present, resulting in better resolution and effective bioink utilization, making DoD a more suitable method for OOC bioprinting.[50] Depending on the actuation mechanism, the critical parameters affecting cell viability are temperature, electric field, and shear stress.[49, 107, 127, 128] Affordability, higher printing speeds (up to 10,000 droplets per second), and higher resolutions (∼50 μm) compared with extrusion-based bioprinting are the main advantages of inkjet bioprinters.[129] A weakness of inkjet bioprinting is that bioinks with high viscosities cannot be bioprinted properly because they can cause clogging at the outlet nozzle. This leads to a lower number of cells delivered per unit time, as a result of using low-viscosity bioinks with lower cell content.[120] Furthermore, since inkjet bioprinters can only operate with low-viscosity bioinks (∼3–12 mPa · s), an additional crosslinking step is almost always required after bioprinting to achieve a stable structure.[71, 130] A DoD inkjet bioprinter (with a 300-μm microvalve and 450-μs valve opening time) was used to bioprint neural progenitor cells and spheroid breast cancer cells through a flat-tip 27 G needle at varying pressures from 0.25 to 1.5 bar. Both tissue-on-chips retained their viability for up to 14 days.[131] Another DoD bioprinter with two 300-μm microvalves and a 150-μm electromagnetic microvalve, with an opening time of 450 μs, was used to bioprint bioink, channel wall material, and crosslinker under 0.5 bar of pressure to create a perfusable vessel model with >83% cell viability.[132] Another on-demand inkjet bioprinter was developed to electrohydrodynamically bioprint tumor cell-laden hydrogel array (>90% cell viability) onto an array chip for drug screening through a 32 G nozzle at 2.7 kV and a flow rate of 10 μl/min.[17] To take advantage of both extrusion-based methods, a hybrid method was proposed that uses extrusion-based printing to print a collagen-based transwell construct and inkjet bioprinting to uniformly bioprint keratinocytes onto this structure, successfully forming a skin that recapitulates in vivo biological properties.[133] 2.1.2 Light-enabled methods SLA-based bioprinting methods are mainly adapted from lithographic methods used in semiconductor fabrication. In this bioprinting method, a photosensitive bioink is exposed to the light of a specific wavelength to polymerize (in the case of negative photoresist) or depolymerize (in the case of positive photoresist) the exposed areas.[134, 135] Although nozzle-based processes typically employ physical (e.g., heat) and chemical crosslinking, SLA uses photocrosslinking which has better spatial and temporal control with minimal heat generation and faster room-temperature progression during the polymerization process.[136] SLA printers cure photoresists in a point-by-point manner, which prolongs the printing process. Although the use of physical photomasks enables the exposure of a layer at once to increase the printing speed, preparing different photomasks is cumbersome. SLA was made more suitable for bioprinting by the adoption of DLP or liquid crystal display SLA (LCD-SLA) to eliminate the use of physical photomasks[137, 138] (Figure 2C). These methods cure the desired pattern by either using an array of several thousand independently controllable digital micromirror devices (DMDs) or using the light from an array of LEDs masked by LCD to form a 2D image of slices to perform a layer-in-once exposure, ultimately improving resolution and printing speed.[138-140] An important factor for cell viability and print resolution in SLA printing is the wavelength, which is mostly in the ultraviolet (UV) range.[141] The DLP method oftentimes uses visible light as a light source, reducing the risk of cell damage.[142] Moreover, since SLA/DLP is a nozzle-free method, bioinks can be used without clogging problems. The main challenges in using SLA/DLP are the limited choice of photopolymerizable bioinks, the possibility of deoxyribonucleic acid (DNA) damage as well as cell lysis as a consequence of UV exposure, and the expensive equipment.[134] Nonetheless, the use of visible light for bioink curation (using visible-light photoinitiators) could partially address problems that arise from UV exposure.[143] DLP-based bioprinting was used to bioprint bone-mimetic structures in vitro.[142] Using a DM