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West Sahara. Currently, cluster analysis of differently expressed genes is being used to define the patient subgroups as well as to discover the underlying pathological mechanism and a potential target for therapeutic development. Nonetheless, this technique requires full data sets on the genetic, clinical, phenotypic, psychosocial idiosyncrasies of the patients, which are not always obtainable Kaur and Chupp, Moreover, handling the out-of-range data that are below or above the detection or threshold limits also restricts the success of cluster analysis.

The second aspect to be improved consists of how well the patient subgroups respond to the proposed treatment. Longitudinal assessments—i. Since there is a gap between the data collection and establishing the clinical translation of the targeted treatments, 3D engineered tissue models, and disease-on-a-chip platforms have been proposed to bridge this gap.

The use of engineered tissues and disease-on-a-chip can offer new platforms that can model the molecular and cellular disease phenotypes, develop correlated data for the cluster analysis and present longitudinal assessments of therapeutic responses on the bench for clinical translation. Cancer is an epigenetic disease caused by mutations to genes that control the way our cells function, especially how they grow and divide.

Over the years, the clinical findings have indicated genetic differences among cancer patients with the same diagnosis. Thus, precision medicine has gained increasing interest, potentially being the next frontier in cancer research Friedman et al. Up to date, patient subgroups with non-small cell lung cancers due to the mutation in the anaplastic lymphoma kinase ALK , BRCA mutant-ovary cancer, breast cancer with human epidermal growth factor receptor 2 HER2 overexpression have already benefited from precision medicine with targeted therapies Vogel et al.

Nevertheless, clinical translation of precision medicine in cancer research is often hampered due to the cost of genomic testing, inadequate phenotypic and psychosocial patient information, and lack of longitudinal assessment of therapeutic responses. In this frame, biofabricated 3D models and tumor-on-a-chip platforms have been proposed for understanding the cancer progression and efficient bench-to-bed translation of precision medicine. Whereas 3D biofabrication strategies have been able to recapitulate the tumor microenvironment complexity by patterning tissue-specific bioinks and fabricate physiologically relevant tissue constructs with high spatiotemporal control over the 3D structures, tumor-on-a-chip platforms mostly aim to recreate significant features of the tumor physiology at molecular and cellular levels Yesil-Celiktas et al.

For instance, tumor-on-a-chip platforms have provided unique microenvironments to simulate the overall tumor pathologies Wang Z. In this scenario, single-cell tumor-on-a-chip platforms have been employed to study the complex composition of tumors. These platforms have been used to visualize rare cancer cells in bulk tumors, with the final aim to interpret tumor heterogeneity comprehensively, detect circulating molecules, and widen the current know-how of cancer genomics Saadatpour et al.

Conversely, multiple-cell-type tumor-on-a-chip platforms e. Alternatively, 3D-bioprinted compartmented multiple-cell constructs have been used to create paracrine loops for studying cancer cell extravasation into the bloodstream and analyze metastatic progression through trans-endothelial migration Kolesky et al.

Without a doubt, both the 3D biofabrication and the tumor-on-a-chip platforms have advanced the in vitro cancer research up to a new level by providing stable longitudinal real-time monitoring, as well as dynamic microenvironment to discover cancer and metastasis mechanisms which can be used in precision medicine for stratifying sub-groups and planning safe therapeutic strategies for patients. Most likely, these platforms will progressively become key tools for precision medicine application in cancer research in the near future, possibly with the convergence of the inputs from other fields, such as omics, systems biology, and bioinformatics.

A rare disease is defined as a condition that affects fewer than , people globally. The major problems associated with rare diseases are the lack of understanding of the disease mechanisms and the very small patient population that prohibits efficient clinical trials to identify effective therapeutic approaches. These issues make rare diseases a focus point of precision medicine. Recently, with the development of iPSCs and CRISPR technologies, establishing relevant mutations on patient-specific cells has become a common practice that could be helpful to understand rare disease mechanisms in 2D cell culture.

These results should then be translated into suitable biofabricated or disease-on-a-chip systems to further increase their accuracy and reliability. Although the research in engineered models of rare diseases is at its preliminary state, there have already been successful pilot studies. For instance, various multi-organ-on-a-chip platforms based on iPSCs and CRISPR technology have been proposed to induce specific mutations in an engineered cell population to study the autoimmune response and to understand the complex mechanism of autoimmune diseases, such as type I diabetes, rheumatoid arthritis, and celiac disease de Mello et al.

Since the severity of autoimmune diseases varies considerably amongst individuals, the potential to model combinations of genetic, environmental, and cellular components makes multi-organ-on-a-chip platforms uniquely able to determine the most relevant factors in disease progression for specific patients. Along with the multi-organ-on-a-chip studies for autoimmune diseases, rare multifocal motor neuropathies have also been recently studied to understand the disease mechanisms at the cellular level.

Hence, a human-based neuromuscular junction NMJ model has been suggested for congenital myasthenic syndrome, which commonly arises from mutations in one of the acetylcholine receptors encoding genes. The described 3D co-culture model provided a robust method to investigate adult human NMJ development and, for the first time, the adult forms of neuromuscular diseases in vitro Bakooshli et al.

Indeed, the use of engineered rare disease models is still in its infancy; nevertheless, the premise of these platforms has already started to play a pivotal role in streamlining the precision medicine processes. Neurodegeneration, the slow and progressive dysfunction and loss of neurons and axons in the central nervous system, is the primary pathological feature of acute and chronic neurodegenerative conditions.

As neurodegeneration may occur due to genetic or phenotypic idiosyncrasies, it is of great interest in precision medicine. Although the neurodegenerative diseases may vary significantly in their clinical and pathological characteristics, at the molecular level, they share a fundamental pathogenic mechanism termed the seeded aggregation of disease-specific proteins.

Alongside identifying disease-related protein accumulation, the interaction between the neurons and vascular cells has been established as a critical player in regulating the neuronal function and fate of neurodegenerative disease. Despite the recent progress—i. Thus, 3D-biofabricated and disease-on-a-chip systems have been proposed as alternatives to create more realistic human neurodegenerative disease models.

Recent studies have shown that by employing these systems, it is possible to obtain results comparable with the current gold-standard in vivo and 2D in vitro disease models. In few cases, these new platforms have even outperformed such standards, identifying the synergetic effects of genetic and environmental factors, neuroinflammation, and production of proinflammatory cytokines.

Without a doubt, these platforms cannot recreate the higher-level cognitive processing of a human brain or the full impact of neurodegeneration on the body. Yet, these tunable platforms hold great potential in precision medicine for deciphering the molecular and cellular neuro-pathologies by integrating genetic and phenotypic idiosyncrasies into the disease models. The s can be considered a golden era in the pharmaceutical industry as the discovery of several blockbuster drugs generated maximal profits for the pharmaceutical sector.

However, in the last two decades, the increased regulatory scrutiny in drug safety has decelerated the fast growth resulting in reduced revenues Krumholz et al. Moreover, key patent expirations between and caused a further decline in product proceeds, which reduced the budget spent on drug development Khanna, Hence, the pharmaceutical industry has taken significant measures to increase the bench-to-market turnover of phase I drugs. Low bench-to-market turnover and high cost of the clinical trials have diverted pharmaceutical research into a more precise and accurate assessment of new drugs at the pre-clinical stage Paul et al.

Therefore, extensive efforts have been put into developing new screening methodologies for the pre-clinical stage, mimicking the reality of clinical trials alongside drug discovery. Thus, only the safest and most efficient new drugs will be qualified for clinical trials in a fast and financially feasible manner. Drug safety is the primary concern of clinical drug attrition.

At the clinical trial period of a new drug, ADME absorption, distribution, metabolism, and excretion profiles, dosing, side effects, toxicity, and interaction with different drugs should be evaluated considering the population variability. Alongside their use in toxicity testing, the pharmaceutical industry, ethics committees, and lawmakers have also started to debate whether these systems can be better predictive models to explore therapeutic efficiency Ingber, Whereas 3D biofabrication approaches aim to contribute to drug testing research, up to date, organ-on-a-chip technologies have been mostly applied and even commercialized for toxicology testing at the pre-clinical level.

Parallel to the benchwork, these systems have also been proposed for designing precise and accurate data sets for in silico libraries as machine learning became widely used in the field of computer-aided drug discovery and development of new drugs Rifaioglu et al. The current pre-clinical in vivo testing is inadequate to satisfy population diversity in the majority of the cases, and often the absence of toxicity in animal models, do not correlate with a similar lack of toxicity in humans Bailey and Balls, Up to date, different organ-on-a-chip devices and 3D-biofabricated tissue models such as blood vessels Grigoryan et al.

One of the main advantages of organ-on-a-chip systems is the possibility of using human cells derived from different donors to attain toxicity information related to diverse human populations. Thanks to such developments, some commercialized tissue-specific organ-on-a-chip devices have even started to become a standardized procedure for toxicity testing for several research groups.

Indeed, designing functional tissue models to investigate organ-specific toxicity of drugs is beneficial; nonetheless, organ-specific requirements are not sufficient to provide a full understanding of drug safety. Thus, the proposed systems should enable the incorporation of fundamental physiological responses regarding ADME profiles, immunity, endocrinal effects, gut-microbiome interactions, effects on reproductive organs, and real-world multi pathology.

Therefore, multi-organ-on-a-chip systems have been widely investigated, aiming at validating the functionality of each organ in the multi-organ-on-a-chip separately. Without a doubt, up to date, these studies have demonstrated, on the one hand, a high potential for the use of functionally coupled multi-organ-on-a-chip for drug assessments and, on the other hand, that highlighting the pertinent need to overcome existing challenges.

First, these systems cannot be considered as an exact mimic of the entire in vivo effects but as a more predictive and biologically relevant assay for the drug discovery cascade. The main challenges in integrating organ-on-a-chips into multi-organ-on-a-chips are the optimization of custom cell culture medium formulations for each organ and developing of perfusion of the nutrients and the oxygen throughout the overall multi-organ-on-a-chip.

Concurrently, thorough assessments in proper scaling of organ-on-a-chip models, implementation of real-time evaluation, acquiring renewable cell sources, developing chemical, mechanical, and electrical cues for missing organ systems, structural and functional validation of multi-organ-on-a-chip platforms required for the translation of these systems.

Despite the in vivo testing is currently the gold standard to explore therapeutic efficiency, qualitative and quantitative high-resolution analysis of diverse biological processes has not been possible in animal models.

Thus, the demand for 3D-biofabricated tissues and organ-on-a-chip devices is significantly increasing thanks to their key advantages of enabling direct real-time or end-point analysis. However, small culture volumes and low cell numbers in these platforms often give rise to technical issues associated with detection sensitivity and specificity.

Research in the field is trying to overcome these technical issues by finding a focal point between what needs to be measured—the biomarkers—and which analytical method should be used in the detection limits for high specificity and sensitivity Li and Tian, Biomarkers are specific molecules that can be objectively measured and evaluated as an indicator of a normal biological process, a pathological process, or a biological response to a therapeutic intervention.

Precise identification of application-specific biomarkers is crucially important; hence, the collection and handling of all samples and all test performance should be conducted in a standardized manner. Since the quantitative structure-activity relationship QSAR concept has been proposed back in the s, QSAR-based models have been used in the lead-optimization step of drug discovery to assess various drug properties such as enzymatic reactions of drugs, drug-target interactions, and drug toxicity Marx et al.

Prospering and clinically coherent predictions of in silico tools have substantially contributed to drug screening and identifying potential new drug leads. Moreover, recently, with the integration of machine learning methods to develop QSAR models, extraction of non-parametric and non-linear relationships from datasets has been expedited. Consequently, these developments have accelerated the analysis of ineffective compounds and enabled the development of in silico models with better predictive performance.

Indeed, the increased predictive values will serve for patient benefit and the reduction of in vivo testing. Ultimately, these systems are envisioned to create in silico libraries and a new level of bio-virtuality by bridging human in vitro and in silico models. Omic sciences attempt to comprehensively study the complex interactions between molecules in the different systems biology layers. With the progress and development of new postgenomic technologies, omics studies are becoming increasingly prevalent and more accessible to diverse disciplines.

In order to succeed in the omic investigation, the correct design of the experimental part is crucial. Omic approaches, based on a holistic view of molecules, can improve the validity of preclinical predictions for drug response, which is essential to patient survival, and at the same time would reduce the cost of clinical practices. The existing technologies are differentiated by the specific target they will detect, and the leading omic techniques can be classified as genomics, transcriptomics, proteomics, and metabolomics.

Whereas the analysis of gene expressions is the primary concern of genomics, the entire set of transcripts, including coding and non-coding RNAs, are the subjects of transcriptomics. Additionally, proteomics and metabolomics are involved in investigating the whole set of proteins and the large-scale study of metabolites of a cell, tissue, or organ. The modern evolution of omic practices has brought the resolution of analysis at the single-cell level. The refinement of technologies has moved the challenge towards studying small quantities of molecules contained in each cell Chappell et al.

To date, omic analyses have allowed us to reconstruct networks and pathways that have been used to extrapolate the functional interactions between genes, proteins, and metabolites. Furthermore, single-cell approaches have highlighted the heterogeneity among cells within populations previously considered homogeneous Vemuri and Aristidou, ; Bodein et al. Unfortunately, many preclinical omic data were generated within 2D biological systems and thus are affected by the lack of contribution of the extracellular microenvironment, the parenchymal and vascular compartments, and the tissue-tissue interface.

Therefore, only a few of them have generated new algorithms with an adequate prognostic capacity to be used in medical practices Sontheimer-Phelps et al. Consequently, the combined use of high-throughput omic methods with 3D biofabrication or organ-on-a-chip technologies could represent an opportunity to validate new drug targets and develop new personalized therapeutic strategies.

As mentioned above, several in vitro organ and 3D tumor models have already been generated, and their deep characterizations are progressively implemented by emerging multi-omic technologies Agarwal et al. However, to date, mostly microtissues cultured within OOC systems have been used as inputs for omic analyses—which are generally performed off-chip—while no significant steps have been reported in the integration of biofabricated samples and omics approaches.

In particular, OOCs coupled with omics have been developed based on the profiling of the metabolome in microfluidic bioartificial organs with the ability to identify toxicity markers in vitro Shintu et al. For example, Wang and colleagues created an excellent human organ-on-a-chip system integrating, for the first time, cell engineering as well as drug metabolism and metabolomics to imitate complex human physiology and multi-organ interconnections Wang X.

More recently, Ndiaye et al. This system allows the combination of a molecular filtration membrane in PDMS microchip, using soft lithography and replica molding, promoting efficient protein retention and proteolysis on the membrane, and reducing significantly the time for proteome analysis and the amount of the samples if compared with membrane-based commercial ultracentrifugation cartridges Ndiaye et al. Furthermore, integration with microfluidic platforms could further allow the assessment of in situ cytotoxicity and the dynamic drug-transport and -delivery behavior from nanocarriers in the same system Zhang et al.

The dizzying expansion of these technologies has, however, seen the need to re-isolate the cells once they have done their job within a complex bioprinted or microfluidic system. To date, methods for isolating single-cells in a format compatible with single-cell omic experiments include laser acquisition microdissection Emmert-Buck et al.

However, the high amount of work does not guarantee a high percentage of isolated cells used in the experimental system, sometimes tens and sometimes hundreds per study. Therefore, increasing the number of cells profiled is the right strategy for overcoming the noise that is intrinsic in single-cell measurements.

In the past few years, microfluidics-based chips have been established to increase the number of cells profiled, reducing the experimental costs and coupling the tissue engineering approaches to the next-generation sequencing, a currently preferred method for omics analyses. To date, several microfluidic devices have been adapted to address concerns of productivity and cost in single-cell preparation and analysis.

The main method couples microfluidic channels with pressure-control valves Whitesides, ; Fan et al. Other innovative techniques for detecting single-cells and their components are based on using a microfluidic apparatus that is able to capture them in an inert carrier oil or using arrays of nanoliter-scale wells nano-wells in which, by gravity, cells or cellular components are seeded at low densities to reach a single element per well Prakadan et al.

Each of these approaches can be used to establish the interconnection between single cells, capture their specific products, and retain their components upon lysis. Importantly, given their small size, these features can be used to process many single cells in a compact physical space, reducing reagent requirements and thus costs and increasing analyte concentrations and thus assay efficiency when limited kinetically or by background.

These innovative systems that focus on cellular output once intercellular dynamics are exhausted, have significantly improved the performance of single-cell omic studies, enabling the parallel processing of thousands of cells.

In the last two decades, biomedical research has greatly benefited from introducing highly sophisticated methods to fabricate more advanced in vitro models of tissues and organs. Organ-on-chips and biofabrication technologies are two great examples of them. These technologies are effectively driving a revolution in several areas of biomedical research. In this review, we have initially provided a brief overview of the broad set of available biofabrication and organ-on-a-chip technologies.

As described in the text, the progress made is relevant; however, we are still far from translating these solutions into actual clinical scenarios due to unmet technical challenges and lack of fundamental knowledge of the biological processes involved Hoffman et al. In the context of tissue engineering and regenerative medicine, biofabrication technologies have affirmed themselves as the gold standard enabling to recapitulate architectural complexity and dimensions of human organs.

The advantages offered by these technologies are numerous, including automated generation of 3D, biologically relevant tissues with high precision and repeatability. The 3D structures biofabricated so far, despite their realistic shapes and dimensions, still exhibit limited functionalities, thus being unsuitable directly for clinical applications. Typical current approximations entail the number and type of cells, their 3D spatial distribution, and the presence of a functional vasculature and innervation.

The latter features are required to supply nutrients to each cell in the construct and, depending on the target tissue, support a proper integration with the host nervous system upon construct grafting in vivo. Among the possible challenges, those connected with the scaling-up processes to manufacture an idoneous number of cells will most likely need in the future a thorough revision and improvement to fulfil the stringent requirements of GMP production.

Additionally, researchers will need to understand better the relations between bioink properties and the fate of embedded cells. So far, in fact, the focus has been mainly directed to formulate bioinks that would enable high printing resolution and support preliminary tissue maturation. Last but not least, on the bench to clinical translation side, designing mechanically stable, biocompatible, and financially feasible constructs can be considered the utmost concern.

Regarding the complex field of disease modelling, biofabricated constructs and OOC platforms significantly complement each other to develop an understanding of disease mechanisms and precision medicine. Indeed, biofabricated and OOC disease models are not a need or a unique tool for all diseases, and currently, these platforms are finding promising applications in some medical fields, such as cancer, neurodegenerative and rare diseases, to assure effective treatments and bench-to-bedside transition of these treatments for patient subgroups with similar epigenetic profiles.

For instance, tumor-on-chip platforms have taken particular attention in pediatric oncology, where they could be used to test tissues harvested from patients as an alternative to risky first-in-human studies within pediatric populations. Alternatively, on the rare disease front, pioneering models for rare disorders, e. Moreover, since the outbreak of the COVID pandemic, such platforms have also been exploited to understand the effects of the SARS-CoV-2 virus on respiratory tissues, underlining once again their great potential Si et al.

Overall, biofabricated and OOC disease modeling platforms are still facing some challenges with their integration into clinical applications. From the biomimicry perspective, embodying immune and endocrine responses in such platforms is still a significantly complex and daunting task. Moreover, physiochemically relevant disease modeling platforms that are standardized and user-friendly have not been fully achieved yet, apart from few commercialized examples Nawroth et al. In drug development, surely, OOC platforms and biofabricated tissues cannot be considered as an exact mimic of the entire in vivo effects but as a more predictive and biologically relevant assay for the drug discovery cascade.

More specifically, to understand and evaluate the efficacy of the drugs and their ADME profile, developing multi-organ systems—i. Additionally, to achieve a structurally and functionally validated multi-organ-on-a-chips, a thorough assessments in proper scaling of organ-on-a-chip models, implementation of real-time evaluation, and development of chemical, mechanical, and electrical cues for missing organ systems stand as crucial requirements.

These innovative systems that focus on cellular output have significantly improved the performance of single-cell omic studies, enabling the parallel processing of thousands of cells cultured in such a tailored microenvironments. While these first successes are a matter of fact, it is not trivial to foresee how these technologies will further develop over the next one or two decades and how their outputs will be eventually translated from the realm of research to meaningful clinical applications.

Nevertheless, these systems are nowadays affected by some common limitations which should be necessarily addressed in the near future. Given the inherent complexity of advanced, in vitro tissue model manufacturing, these limits do not have clear boundaries, being often intertwined one to the other. First, the variability of the experiments among different batches and systems should be drastically reduced through a thorough standardization of the whole process.

Both biofabrication and organ-on-a-chip systems, in fact, lack any specific guideline that should help researchers in developing regulatory-approvable products and, only recently have researchers started to define common roadmaps to address standardization issues Mastrangeli et al. Such standardization should affect all the aspects of these biotech strategies, including material and cell selection, isolation and purification, bio-construct manufacturing, processing and characterizations, culturing protocols, and bio-construct post-processing.

The first step towards this direction has been lately made by the United States Food and Drug Administration FDA in its predictive toxicology roadmap where organ-on-a-chip models have been identified as new promising approaches to develop innovative toxicology methods and have been adopted in FDA laboratories to assess their capacities Food and Drug Administration, As pointed out in the FDA document, the acceptance of any new methods will require sufficient convincing data as well as continuous dialogue and feedback among all relevant stakeholders from development to implementation, including, in particular, validation and acceptance by regulatory authorities.

Reasonably, the implementation of organ-on-a-chip platforms by a regulatory agency should promote and accelerate standardization of this technology at different levels. The second challenge that should be addressed in the near future consists of the increase in the reliability and robustness of the manufactured models.

These aspects represent a key point for the adoption of these technologies in clinically relevant contexts. To improve tissue model reliability and robustness, a more thorough and deeper characterization of the inputs, outputs, and models themselves and their cross-impacts will be needed. Performing data analytics of such voluminous data sets is generally complex, and new in silico tools should be specifically developed in collaboration with mathematicians, statisticians, and bioinformaticians.

Of note, generating these datasets, at least in the near future, is expected to be time-consuming and costly and, therefore, impractical at the single laboratory or small start-up levels. The third issue that affects both current biofabrication and organ-on-a-chip models is their oversimplified nature and thus poor functional behavior, primarily due to persisting technological limitations and lack of fundamental knowledge. To this end, the main focus of the research community had been to recreate static microenvironments, which are still far from dynamic native ones.

In this regard, recently, the integration of 3D printing technology and smart shape-memory materials has created a great wave of enthusiasm for developing physiologically more relevant tissue models, establishing a new research field termed 4D printing. With the introduction of a fourth dimension, i. Though this technology is still in its infancy, it has already succeeded in placing a landmark in the sphere of biomedical research, holding promising prospects for further advancements in the near future.

Besides vascularization, innervation, spatially defined cell distribution, ECM composition, biochemical and electro-mechanical stimulation, and inter-organ cross-talks still remain as pertinent challenges and are hardly observed in the currently available biofabricated or organ-on-a-chip models. In order to overcome these limits, a great deal of work will surely be needed in different research domains, ranging from biomaterials and biochemistry to bioengineering, cell and developmental biology, and bioinformatics.

Finally, it is foreseen for the near future convergence of these two sets of technologies that would eventually enable the manufacturing of cellularized OOC systems using additive manufacturing platforms Knowlton et al. To date, this research area—i.

Specifically, researchers have developed few strategies to combine OOC and 3D bioprinting: 1 the use of 3D printing systems to manufacture structures for OOC replica molding, 2 bioprinting of micro-tissues within pre-fabricated OOC, and 3 one-step fabrication of the cellularized OOC. However, there is still some work ahead—especially for the more attractive case of one-step fabrication of cellularized OOC—due to some material for instance, the optical properties of the printed OOC are still unsatisfactory and technological limitations.

In conclusion, biofabrication and organ-on-a-chip methods represent the most promising technologies nowadays available to advance biomedical research and clearly will play a key role in academic and industrial research during the next two decades. As pointed out in this review, these technologies have already found applications in almost all branches of biomedical research, being also the catalyst for the establishment of as many promising start-up companies.

Roadmaps have been set to guide the future development of both research fields, and, hopefully, regulatory agencies worldwide will soon accelerate the redaction of guidelines to implement these systems into more relevant clinical scenarios. NC, DP and MC have structured the concept of the manuscript and have investigated the related current literature discussed in this manuscript.

MC and DP have equally contributed to the creation and presentation of visual art in the manuscript. All authors participated in reviewing and editing the manuscript. MC, the corresponding author, has supervised the overall work for the manuscript. NET2 project The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Front Bioeng Biotechnol. Published online Sep Author information Article notes Copyright and License information Disclaimer. This article was submitted to Tissue Engineering and Regenerative Medicine, a section of the journal Frontiers in Bioengineering and Biotechnology. Received Jun 28; Accepted Aug The use, distribution or reproduction in other forums is permitted, provided the original author s and the copyright owner s are credited and that the original publication in this journal is cited, in accordance with accepted academic practice.

No use, distribution or reproduction is permitted which does not comply with these terms. This article has been cited by other articles in PMC. Abstract In the last decades, biomedical research has significantly boomed in the academia and industrial sectors, and it is expected to continue to grow at a rapid pace in the future. Keywords: 3D biofabrication, organ-on-a-chip, tissue engineering, regenerative medicine, precision medicine, drug development. Introduction At its onset, at the end of the s, the paramount goal of tissue engineering was to manufacture ex vivo cellularized substitutes to restore, maintain, or improve tissue functions in vivo , which could, ultimately, be used as building blocks for the production of whole functional organs.

Open in a separate window. Biofabrication vs Organ-On-A-Chip: Characteristic Advantages, Limitations, and Challenges Biofabrication and organ-on-a-chip technologies have the potential to revolutionize and boost biomedical research in the next few decades, eventually enabling the development of extremely accurate and functional in vitro tissues, organs, and disease models.

Biofabrication: Building Functional Living Structures in 3D The extensive knowledge and advancements made in the medical, biological, and biotechnological fields have highlighted the limitations of conventional 2D cell cultures in the last decades. Organ-On-A-Chip: Tailoring Cell Behavior at the Microscale Recently, a wave of excitement has spread among the tissue engineering community following the development of new cell culture platforms, the so-called organ-on-a-chip.

Tackling Current Biomedical Challenges With Frontier Technologies Since their establishment, biofabrication and organ-on-a-chip technologies have evolved notably and nowadays represent the most promising approaches to overcome the restrictions of conventional biological and medical research methods.

TABLE 1 Representative studies based on biofabrication technologies reported for the selected biomedical applications. TABLE 2 Representative studies based on organ-on-a-chip technologies reported for the selected biomedical applications. Tissue Engineering and Regenerative Medicine Organ and tissue failures due to chronic or genetic diseases, trauma, or infection, represent a major medical issue worldwide, which nowadays can be effectively treated exclusively through organ transplantation.

Living Matter Matters: Towards Cell Identification and Expansion Manufacturing engineered autologous tissues require billions to trillions of cells. Deciphering Anatomical Architectural Complexity: Towards Organ Blueprints The process of designing a blueprint starts with deciphering the anatomical architectural complexity.

Post-Processing of Biofabricated Organs: From Bioreactors to Bedside Housing billions to trillions of stem cells in anatomically legit architectures and directing them into full-size, functional engineered organs require standardized differentiation protocols and dynamic microenvironments. Disease Models for Precision Medicine In medicine, signs and symptoms are the core of the diagnostic approach to specify and explain the disease state as well as to establish a prognosis and a therapeutic approach.

Cancer Cancer is an epigenetic disease caused by mutations to genes that control the way our cells function, especially how they grow and divide. Rare Diseases A rare disease is defined as a condition that affects fewer than , people globally. Neurodegenerative Diseases Neurodegeneration, the slow and progressive dysfunction and loss of neurons and axons in the central nervous system, is the primary pathological feature of acute and chronic neurodegenerative conditions.

Drug Development and Testing Drug Kinetics The s can be considered a golden era in the pharmaceutical industry as the discovery of several blockbuster drugs generated maximal profits for the pharmaceutical sector. Quasi- In Vivo Toxicity Testing The current pre-clinical in vivo testing is inadequate to satisfy population diversity in the majority of the cases, and often the absence of toxicity in animal models, do not correlate with a similar lack of toxicity in humans Bailey and Balls, A New Avenue to Explore Therapeutic Efficiency Despite the in vivo testing is currently the gold standard to explore therapeutic efficiency, qualitative and quantitative high-resolution analysis of diverse biological processes has not been possible in animal models.

Designing Precise and Accurate Data Sets for In Silico Libraries Since the quantitative structure-activity relationship QSAR concept has been proposed back in the s, QSAR-based models have been used in the lead-optimization step of drug discovery to assess various drug properties such as enzymatic reactions of drugs, drug-target interactions, and drug toxicity Marx et al.

The Convergence With Omic Analyses Omic sciences attempt to comprehensively study the complex interactions between molecules in the different systems biology layers. Discussion In the last two decades, biomedical research has greatly benefited from introducing highly sophisticated methods to fabricate more advanced in vitro models of tissues and organs. Conclusion In conclusion, biofabrication and organ-on-a-chip methods represent the most promising technologies nowadays available to advance biomedical research and clearly will play a key role in academic and industrial research during the next two decades.

Author Contributions NC, DP and MC have structured the concept of the manuscript and have investigated the related current literature discussed in this manuscript. Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References Achberger K. Elife 8 , e Elife 8 , 1— ACS Nano 11 , — Chip 17 , — Small 15 , Biofabrication 8 , SX 21 , — Towards Precision Medicine. Asian Pac. Cancer Prev. Aspiration-assisted Bioprinting for Precise Positioning of Biologics. Heart Valve Biomechanics and Underlying Mechanobiology. BMC Med. Ethics 20 , 1—7. Cancer Res.

Ijms 20 , Methods 13 , — Biomaterials 35 , — Chip 7 , — Microfluidic Organs-On-Chips. Cpd 19 , — Breast Cancer Res. Tissue Engineering with the Aid of Inkjet Printers. Expert Opin. Sensors 21 , Single-Cell Multi omics Technologies. Organ-on-a-chip Platforms for Accelerating the Evaluation of Nanomedicine. Bioactive Mater.

Analytica Chim. Acta , 97— Noninvasive In Vivo 3D Bioprinting. Chip 15 , — EMBO Mol. Biomaterials , 98— Biofabrication 9 , Drug Discov. Today 24 , — Nutrients 9 , Tissue Eng. Chip 11 , — Laser Capture Microdissection. Science , — Organs-on-chips at the Frontiers of Drug Discovery. Whole-genome Molecular Haplotyping of Single Cells. Acoustophoretic Printing. Blood Vessels on a Chip. Nature , — Cancer 15 , — Matter 3 , — Biomaterials 61 , — Chip 20 , — Biofabrication: Reappraising the Definition of an Evolving Field.

Methods 65 , — H , — Biomaterials , 20— Bioinks for 3D Bioprinting: an Overview. Additive Manufacturing 36 , Bioprinting Microvessels Using an Inkjet Printer. Bioprinting 7 , 14— A 25 , — Porous Scaffold Design for Tissue Engineering. Mater 4 7 , — Sensors Actuators B: Chem. PLoS One 11 , e Chip 14 , — Single Cell Isolation and Analysis. Cel Dev. Biomaterials in Tissue Engineering. ATS 12 , S42—S Organ Chips and Uses Thereof.

Part A 14 , — Chip 10 , 36— Complex 3D Bioprinting Methods. APL Bioeng. Biomaterials , 58— RSC Adv. Small 16 , B: Rev. Allergy Clin. Today 17 , — Biomaterials for Tissue Engineering. World J. USA , E7—E Acta Biomater. Trends Biotechnol. What Have We Learnt from Vioxx? BMJ , — Biomaterials 23 , — Tissue Engineering. Microdevices 19 , Biofabrication 11 , Cell Stem Cell 21 , — Small 5 , — Chip 18 , — Trends Cancer 6 9 , — Methods 10 , — Biofabrication 13 , USA , — Biomaterials 67 , — IScience 2 , — Matter 4 , — Cell Analysis on Chip-Mass Spectrometry.

Trac Trends Anal. Experience with Cultured Thymus Tissue in Children. S 21 , — Chip 16 , — ALTEX 37 3 , — Biofabrication 12 , Biomaterials , Atlex 36 4 , — Altex 36 , — Methods Enzymol. Biofabrication 10 , ACS Biomater. Biomaterials 30 , — Drug Deliv.

Biofabrication: a Guide to Technology and Terminology. Biomicrofluidics 5 , Cel Mol. Proteome Res.

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