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Zoio, P.; Oliva, A. Key Requirements for the Development of Skin-on-a-Chip Devices. Encyclopedia. Available online: https://encyclopedia.pub/entry/21656 (accessed on 05 December 2025).
Zoio P, Oliva A. Key Requirements for the Development of Skin-on-a-Chip Devices. Encyclopedia. Available at: https://encyclopedia.pub/entry/21656. Accessed December 05, 2025.
Zoio, Patricia, Abel Oliva. "Key Requirements for the Development of Skin-on-a-Chip Devices" Encyclopedia, https://encyclopedia.pub/entry/21656 (accessed December 05, 2025).
Zoio, P., & Oliva, A. (2022, April 12). Key Requirements for the Development of Skin-on-a-Chip Devices. In Encyclopedia. https://encyclopedia.pub/entry/21656
Zoio, Patricia and Abel Oliva. "Key Requirements for the Development of Skin-on-a-Chip Devices." Encyclopedia. Web. 12 April, 2022.
Key Requirements for the Development of Skin-on-a-Chip Devices
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The increased demand for physiologically relevant in vitro human skin models for testing pharmaceutical drugs has led to significant advancements in skin engineering. One of the most promising approaches is the use of in vitro microfluidic systems to generate advanced skin models, commonly known as skin-on-a-chip (SoC) devices. These devices allow the simulation of key mechanical, functional and structural features of the human skin, better mimicking the native microenvironment. Importantly, contrary to conventional cell culture techniques, SoC devices can perfuse the skin tissue, either by the inclusion of perfusable lumens or by the use of microfluidic channels acting as engineered vasculature. Moreover, integrating sensors on the SoC device allows real-time, non-destructive monitoring of skin function and the effect of topically and systemically applied drugs.

Skin-on-a-Chip Devices skin Requirements

1. Introduction

Skin and subcutaneous disorders affect approximately one-third of the global population and are associated with a burden encompassing psychological, social and financial dimensions [1]. In particular, chronic skin diseases, such as psoriasis, eczema and atopic dermatitis, result in significant morbidity and affect patient quality of life [2]. On the other hand, malignant skin diseases, such as malignant melanoma, are frequently fatal [3]. The high prevalence of skin diseases combined with the emergence of new technological advancements in drug development is fueling the growth of the skin-targeted drug delivery market.
Skin-targeted drug delivery systems include topical, dermal and transdermal approaches. In topical drug delivery, the active substances are intended to remain on the skin’s surface (e.g., barrier creams, sunscreens and repellents) whereas dermal delivery targets active substances into the relevant skin layers (e.g., corticosteroids and antibiotics). In parallel, transdermal drug delivery research has also seen an upsurge in recent years. This approach could circumvent the complications of oral and intramuscular drug delivery and achieve controlled systemic delivery of drugs. Recent innovations in this field include a transdermal patch indicated against symptoms of Parkinson’s disease [4] and a skin-targeted vaccine against COVID-19 [5].
The successful development of skin-targeted drug delivery systems requires careful consideration of the human skin’s anatomy, physiology and physicochemical properties. This evaluation is important to achieve the desired drug effect and avoid adverse reactions such as skin sensitization and/or irritation. The development of new pharmaceutical drugs would greatly benefit from biomimetic in vitro skin models that could replicate the key components of the in vivo healthy and diseased human skin.
Conventional preclinical drug testing relies on in vitro cell cultures and animal models. Most commonly, in vitro cell culture relies on two-dimensional (2D) cell culture systems, typically monolayers of epidermal keratinocytes and/or dermal fibroblasts. While these models offer a rapid, reproducible system to study drug responses, they are not good predictors of the complex interactions seen in vivo [6]. The lack of a 3D physiological tissue environment greatly minimizes the models’ physiological relevance and applicability. On the other hand, in vivo animal models offer information on systemic effects but cannot replicate human skin anatomy and physiology. During the development of pharmaceutical skin-targeted formulations, mouse models are often mandatory for in vivo translational research. However, mouse skin is structurally and functionally different from human skin; it is thinner, contains more hair follicles, includes fewer keratinocyte layers, presents decreased barrier function and greater absorption [7]. Moreover, animal models suffer from low throughput and interspecies variability [8]. These flaws in the conventional testing methods result in a lack of correlation between the input (drug candidates) and output (approved drugs), contributing to the R&D decline [9].
From an ethical perspective, the replacement of animal models satisfies a growing societal concern regarding animal experimentation. Ethical guidelines dictate that, where possible, animal experimentation should be replaced, reduced, or refined (3R principle). The cosmetic industry has been greatly affected by the restrictions imposed on animal testing. Since 2009, the European Commission has been approving regulations on cosmetics, establishing a testing and marketing ban: a prohibition against testing finished cosmetic products or ingredients on animals and commercializing any cosmetic product or ingredient that has been tested on animals within the European Union [10]. The European Centre for the Validation of Alternative Methods (ECVAM) was established in 2010 as a reference laboratory for researching and validating alternative methods, following 3R principles [11]. In 2013, a full marketing ban was put in place for all human health effects tested in animals, including repeated-dose toxicity, reproductive toxicity and toxicokinetics, irrespective of the availability of alternative non-animal tests.
The combinatory effect of the high prevalence of skin diseases, R&D decline and restrictions on animal testing pressured the development of physiologically relevant skin models that could replace conventional, inefficient approaches. Recently, 3D cell culturing techniques have improved the relevance of the available models and demonstrated the synergistic effects that different cell types have on each other [12]. These models can be assembled into complex structures to simulate more physiologically relevant conditions. Both reconstructed human epidermis (RHEm) and full-thickness skin models (FTSm) have been used for many applications including basic, pharmacological and cosmetic research. Innovative techniques such as 3D printing and scaffolds are promising approaches to increase the relevance of these models. However, current tissue-engineered skin models still fall short of the desired controllability and are deficient in several essential key components of the in vivo skin. In particular, their lack of vascularization results in restricted nutrition supply, cell–cell and cell–extracellular matrix (ECM) interactions.
The need for physiologically relevant and functional tissue models led to new technologies for cell cultures such as organ-on-a-chip (OoC) or microphysiological systems. This modern technology aims to surpass the limitations of the 3D cell-based culture platforms and increase the predictive power of in vitro models[13]. These systems have the potential to achieve experimental controllability and reproducibility similar to 2D cell culture while allowing for increased physiological relevance and complexity. In the last few years, OoC technology has been used to recreate advanced biomimetic skin models, known as skin-on-a-chip (SoC) models [14].

2. Cell Sourcing

One of the determinant factors for developing a SoC device is cell selection and sourcing. When choosing the ideal cell types for integration in the SoC platform, the context of use needs to be considered and the key aspects and components needed for function identified.
Multiple in-house culture protocols have been developed and optimized over the last decades to incorporate different cell types and biological sources on human skin models. Conventional FTSms are constructed using primary human skin cells. These cells are isolated from healthy human skin obtained from standard surgical procedures. The clear advantage of using primary cells from human donors is capturing the in vivo phenotype [15]. The most common FTSms consist of an epidermis generated from primary keratinocytes and a dermal compartment populated by primary fibroblasts. These models allow cross-talk between keratinocytes and fibroblasts, increasing physiological relevance compared to RHEms. More complex in house models report adding other cell types into the epidermal (e.g., melanocytes and Langerhans cells) or the dermal compartment (e.g., fibroblasts and lymphocytes) [16]. Zoio et al. generated a pigmented FTSm for long-term studies using primary fibroblasts, keratinocytes and melanocytes [17]. The group reported the formation of a mature dermis and a terminally differentiated epidermis that could maintain its architecture for up to 50 days. Primary cells can also be successfully used to model pathologies when sourced from donors with the disease being studied. For example, in vitro RHEms displaying characteristics of psoriatic epidermis were successfully developed using keratinocytes from patients with psoriasis [18]. Recently, Rioux et al. successfully generated a 3D psoriatic skin model using patient-derived skin cells [19]. Moreover, activated T cells, isolated from human whole blood, were incorporated to develop an immunocompetent model reflecting the psoriatic inflammatory environment. Overall, primary cells present a unique set of advantages. However, these cells also include important drawbacks such as the limited availability of donor skin, donor variation that may hamper experimental readout parameters and restricted proliferation and amplification capacity.
As an alternative, cell lines with validated purity and viability can be considered. The main advantages of cell lines are their reproducibility and the high availability of reliable protocols for cell expansion. However, cells lines are only approximations of the primary cell function and can deviate from the original phenotype. This is the case of the widely used keratinocyte cell line, HaCaT, extensively investigated for its ability to undergo differentiation. Although epidermal tissue formation is possible using HaCaT cells, its low differentiation potential compared to primary keratinocytes makes it difficult to generate a functional stratum corneum [20]. Therefore, the use of the HaCaT keratinocyte cell line is unsuitable for the development of physiologically relevant SoC models as it fails to develop a fully stratified epidermis [21].
Alternatively, hTERT-immortalized keratinocyte cell lines have been proved to develop high-quality epidermal and skin equivalents. These cells faithfully mimic primary keratinocyte proliferation, differentiation, skin barrier function and inflammatory responses. Reijnders et al. developed a fully differentiated FTSm generated from hTERT-immortalized keratinocytes and fibroblasts [22]. The group reported the successful production of a FTSm with a fully differentiated epidermis and a fibroblast-populated dermis comparable to a FTSm originating from primary cells. Models including hTERT-immortalized cells can provide higher throughput screening of new products and drugs and should be considered for incorporating into reproducible SoC platforms. However, depending on the context of use, donor variation can be an important feature to resemble the population accurately. Cell lines lack patient-specificity, which is particularly relevant for disease modeling studies. Furthermore, studies point to cell lines having induced overexpression of proteins involved in toxicity-related pathways [23]. Therefore, these cells can limit the use of the models for toxicity testing.
Induced pluripotent stem cells (iPSC) are a promising cell source for tissue engineering. These cells are derived from adult somatic cells via reprogramming with ectopic expression factors (Oct3/4, Sox2, c-Myc and Klf4) [24]. The expression of these factors results in the suppression of genes responsible for differentiation, reverting the cells to a pluripotent state. The use of iPSC could circumvent the current limitations of FTSms due to their unlimited growth and ability to differentiate into multiple cell types. Furthermore, cells differentiated from iPSC retain characteristics of the original donor, such as disease phenotype, offering an alternative source for modeling skin diseases [25]. Gledhill et al. generated a functional FTSm from iPSC-derived keratinocytes, melanocytes and fibroblasts containing a functional epidermal-melanin unit [26]. This model showed similar morphology and functionality to a healthy skin model. However, many factors need to be addressed before iPSC-derived FTSm can be a viable option. These factors include the high cost, retention of epigenetic memory and genomic instability.
Finally, the cell source could affect how the cells are able to sense the mechanical forces acting on them. Sivarapatna et al. showed differences in response to shear stress in microvessels generated using iPSC but not in microvessels generated using primary human umbilical vein endothelial cells (HUVECs) [27]. The group concluded that iPSC-derived endothelial cells are more plastic in modulating their phenotype under flow than HUVECs. The different cell plasticity in response to shear stress could be a determinant factor in the production of a physiologically relevant SoC model. Overall, the development of a physiologically relevant SoC device requires an understanding of the impact of cell source and type on the models’ architecture and physiology. Each cell type has its own set of advantages and drawbacks that will need to be considered according to the specific application.

3. Cell Scaffolds

One of the major challenges for producing a biomimetic skin model is the development of a dermal matrix with in vivo-like composition and mechanical environment while assuring its stability and reproducibility. The in vivo dermis is an integrated system of fibrous, filamentous and amorphous connective tissue, responsible for the elasticity and tensile strength of the skin. The dermal fibroblasts are surrounded by the ECM composed of various proteins, including collagens, glycosaminoglycans, proteoglycans and adhesive proteins such as fibronectin and laminin[28].
The dermal components are secreted and reorganized by the fibroblasts, resulting in an organized meshwork that provides a soft and elastic environment for cellular growth and interactions. Dermal fibroblasts communicate extensively with the keratinocytes within the epidermis, located on top of this elastic dermal layer. The top of the dermal layer acts as a soft substrate for keratinocyte adherence and the formation of an extracellular basement membrane. The correct development of a SoC model requires an understanding of the interplay between different cell types and the effect of the ECM on cellular function and architecture. The ECM composition and 3D arrangement affect cell morphology, polarity and survival and must be carefully engineered to promote the formation of appropriate tissue architecture and physiology [29].
Conventional methods to develop the dermal compartment involve using natural hydrogels, typically animal-derived collagen, to create an environment conducive to cell adhesion and growth. However, as fibroblasts proliferate, the ECM contracts, limiting their lifespan and application [30]. This also frequently results in a reduction of volume and detachment of the compartment from the support membrane leading to leakage problems. The use of conventional hydrogel materials constitutes a relevant limitation for the standardization of FTSm and their reliable application, making them unsuitable for integration on SoC devices. To overcome these problems, various groups proposed chemical and physical modifications of the matrix. Lotz et al. were able to generate cross-linked collagen hydrogels that were more mechanically stable and less prone to enzymatic degradation when compared with non-cross-linked collagen hydrogels [31]. The produced dermal compartments could support a fully differentiated epidermis on top. Overall, these stable structures are more suitable for integrating a SoC device. However, they typically comprise of one ECM component (e.g., collagen type I) which does not represent the complex in vivo dermal composition. Alternative polymers or hydrogels should be considered to recreate the biophysical properties of the skin. One possibility is to generate a fibroblast-derived matrix in which fibroblasts are stimulated to synthesize the different components of the in vivo ECM [32]. This strategy can be combined with a scaffold of high porosity to achieve good mechanical stability [17][33].
Combining an in vivo-like ECM with a perfusion system makes it is possible to recreate physiological interstitial flow. This flow refers to the fluid movement through the ECM or interstitium of a tissue and constitutes an essential component of microcirculation (Figure 3b). These forces provide the convection necessary for the transport of molecules and provide a specific mechanical environment to cells [34]. A biomimetic skin model should recreate interstitial flow. This is possible by generating a pressure gradient across the SoC through fluidic flow in the basal chamber, especially during culture at ALI, which increases interstitial flow in the FTSm. This enhances the transport of nutrients and induces morphogenic effects in both fibroblasts and keratinocytes. In particular, in vitro studies showed that interstitial flow affects human fibroblasts’ alignment and differentiation [35]. A careful consideration of the interstitial flow and how it is sensed by cells to drive morphogenic responses and other biological responses is relevant for developing a SoC platform, with important implications on the delivery of drugs and therapeutics.

4. Vascularization

The vasculature of the skin is located within the dermis and serves essential functions, delivering nutrients to the cells and removing unwanted metabolic waste products. Furthermore, it acts as a conduit for elements of the immune system and plays a role in thermoregulation [36]. The cutaneous vasculature is also involved in various pathological conditions, including acute and chronic inflammatory conditions, tumor growth, metastasis of malignant melanoma and wound healing [37][38][39]. Moreover, it has been shown that the vasculature impacts the transdermal penetration of substances and the response to irritants [40]. Therefore, the generation of cutaneous vasculature is important to model physiological in vitro skin and pathophysiological conditions.
Conventional reconstructed skin models do not include vascularization, which limits their ability to reflect the function of in vivo human skin. Moreover, the lack of vascularization greatly reduces the supply of oxygen and nutrients in 3D skin tissues, reducing cell viability in thick (millimeter-sized) skin constructs [41]. In particular, the diffusion limit of oxygen in cell-rich tissues is ~200 µm. This value is used to determine the smallest cubic voxel of cells that can survive without vasculature (functional unit). Therefore, the culture of thicker skin constructs (>200 µm) can undergo hypoxia and apoptosis. The importance of vascularization, in particular for implanted skin grafts, pressured the development of innovative approaches to recreate in vivo-like vasculature. One popular strategy to generate vascularization in skin grafts relies on the host vessels’ ability to invade the implanted engineered tissue [42]. Alternative approaches to induce vasculogenesis in vitro include cell seeding onto scaffolds or hydrogels, cell sheeting engineering and cell encapsulation [43]. However, most of these approaches involve complex and slow processes to induce vascularization, not suited for high-throughput applications. Furthermore, the vascular channels formed in these studies have a random formation and are inaccessible to external pumps. Consequently, these models do not have functional perfusable vascular channels, limiting their applicability.
Advances in microfluidics, 3D printing and micro-molding have enabled the development of perfusable vascular networks [44]. Prevascularized patterning methods used to create vascular-like networks on-chip can be divided into soft lithography techniques and 3D patterning methods. Soft lithography typically results in square or rectangular cross-sectioned channels, which do not represent the in vivo 3D geometry. To reproduce 3D barrier tissues on-chip, the most common approach is the integration of a porous membrane between two-channel, polydimethylsiloxane (PDMS) layers.
However, membrane-based models prevent direct cell-to-cell interaction between the vascular and parenchymal components. Alternatively, microfabrication techniques can be adapted to embed hydrogels in the PDMS device. These devices allow direct contact between the vascular component and the parenchyma. Furthermore, vasculogenesis can be induced in these models to create a vascular network in the central hydrogel.
Sophisticated 3D patterning methods can be used to reproduce more physiologically representative vascular networks on-chip. These methods include templating techniques, layer-by-layer manufacturing and 3D bioprinting. Templating techniques are a subtractive strategy in which a material with a specific geometry is embedded in a hydrogel and subsequently removed/dissolved. Although templating offers a simple method to reproduce hollow channels on a matrix, it is typically limited to simple geometries. Moreover, this technique is unable to reproduce dimensions relevant to model capillaries as seen in skin models fabricated angiogenically. Layer-by-layer techniques could be used to generate more versatile perfusable vascular networks via multilayer assembling. This bottom-up technique consists of assembling 2D prepatterned gel layers into multi-layered 3D geometries. Finally, combining 3D printing with microfluidics could generate complex structures mimicking the native skin due to its precision and versatility. Three-dimensional printing facilitates the precise extrusion and localization of multiple cell types and biomaterials. Importantly, the bioengineered vascular network should be perfused to achieve adequate tissue function.

5. Mechanical Stimulus

OoC technology can be used to introduce mechanical stimulus similar to what organs and tissues experience in vivo and, simultaneously, continuously deliver cell culture media and removal of cell metabolites. Cellular mechanotransduction is a well-known phenomenon, with various studies describing the cellular mechanisms where mechanical forces are transduced into biochemical signals [45]. These responses are integral parts of the cellular microenvironment that modulate various processes in health and disease states. Relevant in vivo-like biomechanical forces include shear stress, tensile and compressive forces. Shear stress refers to the force created when a tangential force acts on an object. This force can be imparted by fluid flowing over an object and is prevalent throughout the human body. This effect is more pronounced on the endothelial cells, which are sensitive to changes in fluid flow [46].
Agarwall et al. showed that epidermal keratinocytes are sensitive to microflow-induced shear stress [47]. These cells exhibited mechanoresponsive structural reorganization under the influence of shear stresses of magnitude 0.06 dyne/cm2 and cellular damage under shear stresses of magnitude 6 dyne/cm2. The group also showed that shear stress increased the cell colony area and expression of E-cadherin and Zonula occludens-1 at the cell–cell junction. These observations point to an improvement in the epithelial phenotype. However, the positive effect of the shear stress on keratinocytes is not expected to play a major role in 3D FTSms developed on-chip. Skin differentiation requires culture at the air–liquid interface, which means that keratinocytes are not exposed to fluid flow induced shear stress at the apical side, except for an initial period of approximately 24–48 h. At the basal side, keratinocytes are typically protected from the effect of shear by a membrane or dermal compartment.
Studies also have shown that shear stress affects fibroblasts’ behavior including their orientation, migration and adhesion [48]. However, in an in vivo-like engineered dermal compartment, the ECM matrix’s pores impede the fluid’s momentum transport outside the individual pores. Therefore, shear stresses acting on dermal fibroblasts are often negligible. Arguably, in a 3D SoC model with vascularization, the most important role of fluid-induced shear stress is on endothelial cells. Several studies described the importance of endothelial cell sensitivity to shear stress and the involvement of these forces on multiple physiological vascular processes [49]. In particular, Tsvirkun et al. developed a microvasculature-on-chip and showed that endothelial cells submitted to physiological levels of flow-induced shear stress demonstrate strong similarities with in vivo capillaries [50].
Various approaches have been explored for perfusing culture media, categorized into pump- or gravity-driven solutions [51]. The most common methods for generating fluid flow are external pumps, including a syringe pump or peristaltic pump. These systems deliver accurate, fine-tuned fluid flow but are typically time-consuming. Furthermore, tubing and connections can increase the risk of contamination. To overcome some of the limitations of external pumping, pumps have been integrated within microfluidic chips to miniaturize the systems. While internal on-chip pumping makes it possible to reduce the setup footprint, integrating these systems is typically complicated regarding fabrication and operation. Alternatively, passive flow, typically gravity driven, has recently emerged as an alternative [52]. For this, rocking platforms are custom-built to recirculate culture media through the microfluidic channels. These approaches exclude tubing and complex setups with a big footprint. However, these methods typically lack fine control of flow rate, are prone to changes in hydrostatic pressure over time and do not include fresh media perfusion and waste removal.
In addition to the shear stress induced by perfusion, tissues in the body are continuously subjected to other forces, including tensile and compressive forces. The tensile forces applied to the cellular microenvironment result in tissue stretching. The human skin is exposed to various types of mechanical stimuli including cyclic stretch. This is a result of environmental effects, growth and various internal processes. Various experiments investigated the effects of stretch stimuli on 2D skin cells including epidermal keratinocytes and dermal fibroblasts. According to the reports, applying tensile forces to dermal fibroblasts triggers signal transduction from ECM into cells, resulting in increased synthesis of collagen I, collagen III and elastin [53]. Furthermore, increased production of protease inhibitors such as tissue inhibitor of metalloproteinase was reported [54]. In epidermal keratinocytes, stretch stimulation promoted cellular adhesiveness, proliferation and protein synthesis [55].
Given the complex interactions between keratinocytes and fibroblasts, other groups have studied the importance of these forces and the effect on skin models containing both cells. Lü et al. developed an in vitro tensile device to study the mechanisms regulating keratinocyte migration under application of mechanical stretch [56]. Their results showed that, when exposed to these forces, dermal fibroblasts increase secretion of epidermal growth factor, promoting an asymmetric keratinocyte migration. This phenomenon results in accelerated wound repair. Tokuyama et al. designed an experimental system wherein stretch was applied during the formation of an FTSm [55]. The group analyzed the effects of these stimuli on keratinization of epidermal keratinocytes and formation of a basement membrane. Cyclic stretch resulted in an increase in the synthesis of basement membrane proteins and a thicker epidermal layer.
Various actuation approaches have been developed to induce cyclic stretch on cells [57]. Researchers either use their stretching platforms, typically employing pneumatic approaches, or use commercially available systems [Flexcell (Burlington, NC, USA), StretxCell (San Diego, CA, USA)]. Although multiple solutions exist to apply cyclic stretch, OoC technology presents a unique opportunity to create customizable solutions and combine them with other relevant forces such as shear stress. Various OoC platforms have reproduced different types of mechanical strains including cyclic stretch. Huh et al. reported a lung-on-a-chip made of a central chamber divided by an elastic porous membrane that could be stretched unidirectionally by providing a vacuum in two adjacent chambers [58][59]. This platform was used to study inflammatory responses and recreate drug toxicity-induced pulmonary edema. Other groups improved on this model by generating a 3D mechanical strain, better simulating the in vivo forces [60].

6. Design and Fabrication

For FTSm generation, the apical chamber must ensure the correct formation of stratified epithelium and air circulation. The lower chamber must ensure correct medium perfusion. Typically, at the end of an experiment, the tissue should be retrieved to perform an analysis of its architecture and physiology. Conventional methods for developing biological barriers, including skin, typically involve using permeable supports (e.g., transwell), establishing two chambers that separate the apical and basal surfaces of the tissue. This correct compartmentalization is crucial for forming 3D skin models with an in vivo-like barrier. It allows a leakage-free separation between the apical and basal surfaces of the skin, allowing the correct establishment of the ALI.
Advances in biomaterials and microfabrication have allowed researchers to integrate compartmentalization inside OoC platforms to develop innovative barrier models. The most common approach for creating separated domains inside an OoC is integrating a semipermeable membrane between two elastomeric microfluidic channels. This model was first envisioned by Huh et al. to reproduce the ALI of the lung [61]. Since then, this approach has been used to recreate multiple tissues, including the blood-brain barrier, gut and liver [62]. The use of membranes separating the tissue from the fluidic compartment limits mass transport and reduces the prediction of transdermal skin absorption into the circulatory system. Moreover, this approach typically relies on the irreversible bonding between the apical and basal culture environments, using adhesive glues or oxygen plasma treatment [63]. For the generation of FTSms, this strategy presents several limitations, including difficulties related to the introduction of a dermal matrix on top of the membrane, culture maintenance and challenges accessing the tissue for end-point analysis.
A fully realized SoC model with the potential to replace animal experiments needs to replicate the structure and function of the in vivo skin at a relatively low cost and be compatible with high-throughput studies. In the academic field, most OoCs are fabricated from PDMS using soft lithography techniques. This material has been commonly used due to its biocompatibility, gas permeability and rapid prototyping capabilities. However, PDMS is well known for its tendency to absorb small hydrophobic molecules and other organic compounds and drugs, limiting its applicability [64]. Moreover, large-scale production and commercialization of PDMS-based devices have been a challenge due to the high cost of the current fabrication strategies. Novel low-cost methods for the fabrication of PDMS devices, including mask-free procedures and alternatives to plasma treatment, could expand their applicability and commercialization [65].
Thermoplastics are gaining more attention since they offer several advantages compared to PDMS: they are cheaper, present less absorption and evaporation and provide higher chemical resistivity. The use of thermoplastics can lead to an easier transition from academia to industry since they can be fabricated both by rapid prototyping and industrial-scale fabrication techniques. Integration of membranes on thermoplastics can be performed using various techniques such as thermal bonding, ultrasonic welding, laser welding, solvent bonding and surface functionalization [66]. Alternatively, these materials can be reversible sealed using clamps or magnets, providing minimal requirements for membrane materials. This technique is compatible with the development of modular microfluidic circuits, a concept several research groups have explored. Abhyankar et al. developed a module-based approach in which magnetic latching allows culture membranes to be sandwiched between fluidic channels and sealed in place to support compartmentalized cultures [67]. The flexibility of this design could be interesting for a future SoC, allowing easy removal of the skin tissue for histological and immunohistochemistry analysis and allowing direct cell seeding and introduction of the hydrogel mixture for dermis formation onto the membrane. Furthermore, different modules could be developed, enabling the user to select the modules that meet their requirements. For example, a dedicated apical module with integrated microneedles could be developed to study the effect of these devices on the delivery of pharmacologically active ingredients. Microneedle devices are increasing in popularity due to their potential for transdermal delivery, disease treatment and diagnosis [68][69]. Finally, a user-friendly interface is also an important consideration when designing a SoC device. This could streamline experimental procedures and encourage adoption in laboratories unfamiliar with OoC technology.
Experimental studies can be complemented with numerical simulations to assess the viability of the SoC devices and optimize their design. These tools can be used to predict critical parameters such as oxygen concentration, fluid velocity, shear stress and diffusion processes. Consequently, it is possible to better determine the required chip materials, chamber/channel geometry and dimensions, fluid properties and testing conditions to develop physiologically relevant models.
Hernando et al. showed the importance of performing in silico studies for design optimization by modeling cell behaviors in OoC devices with different channel geometries. The group reported that the cell culture time required to fully exploit their OoC could be reduced by redesigning the chip’s inlet channel and chamber network [70]. Zahorodny-Burke et al. used numerical simulations to evaluate the impact of the chip’s materials on the oxygen concentration in cell culture. The group reported that OoC devices fabricated using PMMA and cyclic olefin copolymer (COC) resulted in a low oxygen supply to the cells. They concluded that flow rates should be optimized to increase oxygen supply when using materials with low oxygen diffusion [71]. More recently, Kheiri et al. used computational modeling to simulate multiple device designs and flow conditions for reproducing tumor spheroid-on-a-chip [72]. The group concluded that computational modeling is an efficient strategy to optimize microfluidic device designs, providing insightful information on the drug transport phenomena in these models.
Similarly, numerical simulations can be used to simulate the microenvironments of SoC devices, towards developing models of greater accuracy. The adequate simulation of flow and drug transport in these models requires an understanding of the key physical properties of the skin. Narasimhan et al. described a detailed numerical model for transdermal drug delivery by considering the skin as a composite, porous material [73].

7. Sensor Integration

Conventional analyses of tissue function mainly depend on endpoint assessment techniques. In particular, for 3D cell culture using scaffolds or membranes, the monitoring cannot be done using conventional microscopy techniques due to the limited light penetration and scattering effects [74]. The conventional process usually includes the removal of the tissue from the wells, chemical fixing, and labelling. Alternatively, assays based on the transport of tracer compounds (e.g., fluorescein isothiocyanate-labelled dextran) are performed. However, these compounds can affect the tissue’s integrity and lack the sensitivity to detect subtle changes in their function [75]. With OoC systems, it is possible to surpass this limitation by integrating microsensors for measuring relevant physical/chemical parameters in situ.
Integrated sensors can characterize the engineered tissue and tissue interactions with different stimulants, giving prompt insight. First attempts to integrate sensors inside the OoC systems have shown the relevance of monitoring in real-time to capture changes in the properties of living cells to obtain complete information about what is happening inside the OoC. An example is the work of Zhang et al. of an automated multi-tissue organ system that integrates an array of on-chip sensors, including electrochemically activated immune biosensors attached to physical microelectrodes, mini microscopes and optical pH, oxygen and temperature monitors [76]. This technical feat highlights the ongoing engineering advances that are enabling real-time non-invasive monitoring of OoC microenvironments.
In the context of SoC platforms, the integration of sensors would be extremely relevant. Growing a FTSm inside a platform is a very long process ranging from 2 weeks to 1.5 months. Using conventional endpoint assays, no information is acquired during the period necessary for skin formation, resulting in low experiment reproducibility. An ideal future SoC platform should integrate physical sensors for monitoring relevant cell culture parameters (e.g., pH, O2, temperature), electrochemical sensors for measuring soluble protein biomarkers as well as transepithelial electrical resistance (TEER) sensors to measure the skin barrier function.

References

  1. Seth, D.; Cheldize, K.; Brown, D.; Freeman, E.F. Global Burden of Skin Disease: Inequities and Innovations. Curr. Dermatol. Rep. 2017, 6, 204–210.
  2. Chu, S.; Mehrmal, S.; Uppal, P.; Giesey, R.L.; Delost, M.E.; Delost, G.R. Burden of skin disease and associated socioeconomic status in Europe: An ecologic study from the Global Burden of Disease Study 2017. JAAD Int. 2020, 1, 95–103.
  3. Johansson, M.; Brodersen, J.; Gøtzsche, P.C.; Jørgensen, K.J. Screening for reducing morbidity and mortality in malignant melanoma. Cochrane Database Syst. Rev. 2019, 6, CD012352.
  4. Raeder, V.; Boura, I.; Leta, V.; Jenner, P.; Reichmann, H.; Trenkwalder, C.; Klingelhoefer, L.; Chaudhuri, K.R. Rotigotine Transdermal Patch for Motor and Non-motor Parkinson’s Disease: A Review of 12 Years’ Clinical Experience. CNS Drugs 2021, 35, 215–231.
  5. Korkmaz, E.; Balmert, S.C.; Sumpter, T.L.; Carey, C.D.; Erdos, G.; Falo, L.D., Jr. Microarray patches enable the development of skin-targeted vaccines against COVID-19. Adv. Drug Deliv. Rev. 2021, 171, 164–186.
  6. Jensen, C.; Teng, Y. Is It Time to Start Transitioning from 2D to 3D Cell Culture? Front. Mol. Biosci. 2020, 7, 33.
  7. Moniz, T.; Costa Lima, S.A.; Reis, S. Human skin models: From healthy to disease-mimetic systems; characteristics and applications. Br. J. Pharmacol. 2020, 177, 4314–4329.
  8. Yun, Y.E.; Jung, Y.J.; Choi, Y.J.; Choi, J.S.; Cho, Y.W. Artificial skin models for animal-free testing. J. Pharm. Investig. 2018, 48, 215–223.
  9. Franzen, N.; van Harten, W.H.; Retèl, V.P.; Loskill, P.; van den Eijnden-van Raaij, J.; IJzerman, M. Impact of organ-on-a-chip technology on pharmaceutical R&D costs. Drug Discov. Today 2019, 24, 1720–1724.
  10. Taylor, K.; Rego Alvarez, L. Regulatory drivers in the last 20 years towards the use of in silico techniques as replacements to animal testing for cosmetic-related substances. Comput. Toxicol. 2020, 13, 100112.
  11. Zuang, V.; Worth, A.P.; Balls, M. Chapter 2.10The Role of ECVAM. In History of Toxicology and Environmental Health; Balls, M., Combes, R., Worth, A., Eds.; Academic Press: Cambridge, MA, USA, 2019; pp. 95–107. ISBN 978-0-12-813697-3.
  12. Langhans, S.A. Three-Dimensional In Vitro Cell Culture Models in Drug Discovery and Drug Repositioning. Front. Pharmacol. 2018, 9, 6.
  13. Ma, C.; Peng, Y.; Li, H.; Chen, W. Organ-on-a-Chip: A New Paradigm for Drug Development. Trends Pharmacol. Sci. 2021, 42, 119–133.
  14. Sutterby, E.; Thurgood, P.; Baratchi, S.; Khoshmanesh, K.; Pirogova, E. Microfluidic Skin-on-a-Chip Models: Toward Biomimetic Artificial Skin. Small 2020, 16, 1–17.
  15. Van den Broek, L.J.; Bergers, L.I.J.C.; Reijnders, C.M.A.; Gibbs, S. Progress and Future Prospectives in Skin-on-Chip Development with Emphasis on the use of Different Cell Types and Technical Challenges. Stem Cell Rev. Rep. 2017, 13, 418–429.
  16. Ali, N.; Hosseini, M.; Vainio, S.; Taïeb, A.; Cario-André, M.; Rezvani, H.R. Skin equivalents: Skin from reconstructions as models to study skin development and diseases. Br. J. Dermatol. 2015, 173, 391–403.
  17. Zoio, P.; Ventura, S.; Leite, M.; Oliva, A. Pigmented full-thickness human skin model based on a fibroblast-derived matrix for long-term studies. Tissue Eng. Part C Methods 2021, 27, 433–443.
  18. Niehues, H.; van den Bogaard, E.H. Past, present and future of in vitro 3D reconstructed inflammatory skin models to study psoriasis. Exp. Dermatol. 2018, 27, 512–519.
  19. Rioux, G.; Simard, M.; Morin, S.; Lorthois, I.; Guérin, S.L.; Pouliot, R. Development of a 3D psoriatic skin model optimized for infiltration of IL-17A producing T cells: Focus on the crosstalk between T cells and psoriatic keratinocytes. Acta Biomater. 2021, 136, 210–222.
  20. Brohem, C.A.; da Silva Cardeal, L.B.; Tiago, M.; Soengas, M.S.; de Moraes Barros, S.B.; Maria-Engler, S.S. Artificial skin in perspective: Concepts and applications. Pigment Cell Melanoma Res. 2011, 24, 35–50.
  21. Jung, M.H.; Jung, S.M.; Shin, H.S. Co-stimulation of HaCaT keratinization with mechanical stress and air-exposure using a novel 3D culture device. Sci. Rep. 2016, 6, 33889.
  22. Reijnders, C.M.A.; Van Lier, A.; Roffel, S.; Kramer, D.; Scheper, R.J.; Gibbs, S. Development of a Full-Thickness Human Skin Equivalent in Vitro Model Derived from TERT-Immortalized Keratinocytes and Fibroblasts. Tissue Eng.-Part A 2015, 21, 2448–2459.
  23. Astashkina, A.; Mann, B.; Grainger, D.W. A critical evaluation of in vitro cell culture models for high-throughput drug screening and toxicity. Pharmacol. Ther. 2012, 134, 82–106.
  24. Rowe, R.G.; Daley, G.Q. Induced pluripotent stem cells in disease modelling and drug discovery. Nat. Rev. Genet. 2019, 20, 377–388.
  25. Khurana, P.; Kolundzic, N.; Flohr, C.; Ilic, D. Human pluripotent stem cells: An alternative for 3D in vitro modelling of skin disease. Exp. Dermatol. 2021, 30, 1572–1587.
  26. Gledhill, K.; Guo, Z.; Umegaki-Arao, N.; Higgins, C.A.; Itoh, M.; Christiano, A.M. Melanin transfer in human 3D skin equivalents generated exclusively from induced pluripotent stem cells. PLoS ONE 2015, 10, e0136713.
  27. Sivarapatna, A.; Ghaedi, M.; Xiao, Y.; Han, E.; Aryal, B.; Zhou, J.; Fernandez-Hernando, C.; Qyang, Y.; Hirschi, K.K.; Niklason, L.E. Engineered Microvasculature in PDMS Networks Using Endothelial Cells Derived from Human Induced Pluripotent Stem Cells. Cell Transplant. 2017, 26, 1365–1379.
  28. Hussey, G.S.; Dziki, J.L.; Badylak, S.F. Extracellular matrix-based materials for regenerative medicine. Nat. Rev. Mater. 2018, 3, 159–173.
  29. Urbanczyk, M.; Layland, S.L.; Schenke-Layland, K. The role of extracellular matrix in biomechanics and its impact on bioengineering of cells and 3D tissues. Matrix Biol. 2020, 85–86, 1–14.
  30. Grinnell, F. Fibroblast–collagen-matrix contraction: Growth-factor signalling and mechanical loading. Trends Cell Biol. 2000, 10, 362–365.
  31. Lotz, C.; Schmid, F.F.; Oechsle, E.; Monaghan, M.G.; Walles, H.; Groeber-Becker, F. Cross-linked Collagen Hydrogel Matrix Resisting Contraction to Facilitate Full-Thickness Skin Equivalents. ACS Appl. Mater. Interfaces 2017, 9, 20417–20425.
  32. El Ghalbzouri, A.; Commandeur, S.; Rietveld, M.H.; Mulder, A.A.; Willemze, R. Replacement of animal-derived collagen matrix by human fibroblast-derived dermal matrix for human skin equivalent products. Biomaterials 2009, 30, 71–78.
  33. Roger, M.; Fullard, N.; Costello, L.; Bradbury, S.; Markiewicz, E.; O’Reilly, S.; Darling, N.; Ritchie, P.; Määttä, A.; Karakesisoglou, I.; et al. Bioengineering the microanatomy of human skin. J. Anat. 2019, 234, 438–455.
  34. Swartz, M.A.; Fleury, M.E. Interstitial Flow and Its Effects in Soft Tissues. Annu. Rev. Biomed. Eng. 2007, 9, 229–256.
  35. Ng, C.P.; Swartz, M.A. Fibroblast alignment under interstitial fluid flow using a novel 3-D tissue culture model. Am. J. Physiol. Circ. Physiol. 2003, 284, H1771–H1777.
  36. Low, D.A.; Jones, H.; Cable, N.T.; Alexander, L.M.; Kenney, W.L. Historical reviews of the assessment of human cardiovascular function: Interrogation and understanding of the control of skin blood flow. Eur. J. Appl. Physiol. 2020, 120, 1–16.
  37. Huggenberger, R.; Detmar, M. The Cutaneous Vascular System in Chronic Skin Inflammation. J. Investig. Dermatol. Symp. Proc. 2011, 15, 24–32.
  38. Foster, D.S.; Jones, R.E.; Ransom, R.C.; Longaker, M.T.; Norton, J.A. The evolving relationship of wound healing and tumor stroma. JCI Insight 2018, 3, e99911.
  39. Kashani-Sabet, M.; Sagebiel, R.W.; Ferreira, C.M.M.; Nosrati, M.; Miller III, J.R. Vascular Involvement in the Prognosis of Primary Cutaneous Melanoma. Arch. Dermatol. 2001, 137, 1169–1173.
  40. Cevc, G.; Vierl, U. Spatial distribution of cutaneous microvasculature and local drug clearance after drug application on the skin. J. Control. Release 2007, 118, 18–26.
  41. Magliaro, C.; Mattei, G.; Iacoangeli, F.; Corti, A.; Piemonte, V.; Ahluwalia, A. Oxygen Consumption Characteristics in 3D Constructs Depend on Cell Density. Front. Bioeng. Biotechnol. 2019, 7, 251.
  42. Lee, M.; Choi, J.S.; Eom, M.R.; Jeong, E.J.; Kim, J.; Park, S.A.; Kwon, S.K. Prevascularized Tracheal Scaffolds Using the Platysma Flap for Enhanced Tracheal Regeneration. Laryngoscope 2021, 131, 1732–1740.
  43. Shafiee, S.; Shariatzadeh, S.; Zafari, A.; Majd, A.; Niknejad, H. Recent Advances on Cell-Based Co-Culture Strategies for Prevascularization in Tissue Engineering. Front. Bioeng. Biotechnol. 2021, 9, 745314.
  44. Dellaquila, A.; Le Bao, C.; Letourneur, D.; Simon-Yarza, T. In Vitro Strategies to Vascularize 3D Physiologically Relevant Models. Adv. Sci. 2021, 8, 2100798.
  45. Martino, F.; Perestrelo, A.R.; Vinarský, V.; Pagliari, S.; Forte, G. Cellular Mechanotransduction: From Tension to Function. Front. Physiol. 2018, 9, 824.
  46. Silvani, G.; Romanov, V.; Cox, C.D.; Martinac, B. Biomechanical Characterization of Endothelial Cells Exposed to Shear Stress Using Acoustic Force Spectroscopy. Front. Bioeng. Biotechnol. 2021, 9, 9.
  47. Agarwal, T.; Narayana, G.H.; Banerjee, I. Keratinocytes are mechanoresponsive to the microflow-induced shear stress. Cytoskeleton 2019, 76, 209–218.
  48. Lei, X.; Liu, B.; Wu, H.; Wu, X.; Wang, X.-L.; Song, Y.; Zhang, S.-S.; Li, J.-Q.; Bi, L.; Pei, G.-X. The effect of fluid shear stress on fibroblasts and stem cells on plane and groove topographies. Cell Adh. Migr. 2020, 14, 12–23.
  49. Roux, E.; Bougaran, P.; Dufourcq, P.; Couffinhal, T. Fluid Shear Stress Sensing by the Endothelial Layer. Front. Physiol. 2020, 11, 861.
  50. Tsvirkun, D.; Grichine, A.; Duperray, A.; Misbah, C.; Bureau, L. Microvasculature on a chip: Study of the Endothelial Surface Layer and the flow structure of Red Blood Cells. Sci. Rep. 2017, 7, 45036.
  51. Kaarj, K.; Yoon, J.Y. Methods of delivering mechanical stimuli to Organ-on-a-Chip. Micromachines 2019, 10, 700.
  52. Wang, Y.I.; Shuler, M.L. UniChip enables long-term recirculating unidirectional perfusion with gravity-driven flow for microphysiological systems. Lab Chip 2018, 18, 2563–2574.
  53. Wang, J.H.-C.; Thampatty, B.P.; Lin, J.-S.; Im, H.-J. Mechanoregulation of gene expression in fibroblasts. Gene 2007, 391, 1–15.
  54. Shelton, L.; Rada, J.S. Effects of cyclic mechanical stretch on extracellular matrix synthesis by human scleral fibroblasts. Exp. Eye Res. 2007, 84, 314–322.
  55. Tokuyama, E.; Nagai, Y.; Takahashi, K.; Kimata, Y.; Naruse, K. Mechanical stretch on human skin equivalents increases the epidermal thickness and develops the basement membrane. PLoS ONE 2015, 10, e0141989.
  56. Lü, D.; Liu, X.; Gao, Y.; Huo, B.; Kang, Y.; Chen, J.; Sun, S.; Chen, L.; Luo, X.; Long, M. Asymmetric migration of human keratinocytes under mechanical stretch and cocultured fibroblasts in a wound repair model. PLoS ONE 2013, 8, e74563.
  57. Zhang, W.; Huang, G.; Xu, F. Engineering Biomaterials and Approaches for Mechanical Stretching of Cells in Three Dimensions. Front. Bioeng. Biotechnol. 2020, 8, 1151.
  58. Huh, D.D. A human breathing lung-on-a-chip. Ann. Am. Thorac. Soc. 2015, 12 (Suppl. S1), S42–S44.
  59. Huh, D.; Leslie, D.C.; Matthews, B.D.; Fraser, J.P.; Jurek, S.; Hamilton, G.A.; Thorneloe, K.S.; McAlexander, M.A.; Ingber, D.E. A human disease model of drug toxicity-induced pulmonary edema in a lung-on-a-chip microdevice. Sci. Transl. Med. 2012, 4, 159ra147.
  60. Zhao, Q.; Cole, T.; Zhang, Y.; Tang, S.-Y. Mechanical Strain-Enabled Reconstitution of Dynamic Environment in Organ-on-a-Chip Platforms: A Review. Micromachines 2021, 12, 765.
  61. Huh, D.; Matthews, B.D.; Mammoto, A.; Montoya-Zavala, M.; Yuan Hsin, H.; Ingber, D.E. Reconstituting organ-level lung functions on a chip. Science 2010, 328, 1662–1668.
  62. Sakolish, C.M.; Esch, M.B.; Hickman, J.J.; Shuler, M.L.; Mahler, G.J. Modeling Barrier Tissues In Vitro: Methods, Achievements, and Challenges. EBioMedicine 2016, 5, 30–39.
  63. Pasman, T.; Grijpma, D.; Stamatialis, D.; Poot, A. Flat and microstructured polymeric membranes in organs-on-chips. J. R. Soc. Interface 2018, 15, 20180351.
  64. Ramadan, Q.; Zourob, M. Organ-on-a-chip engineering: Toward bridging the gap between lab and industry. Biomicrofluidics 2020, 14, 41501.
  65. Shakeri, A.; Khan, S.; Didar, T.F. Conventional and emerging strategies for the fabrication and functionalization of PDMS-based microfluidic devices. Lab Chip 2021, 21, 3053–3075.
  66. Schneider, S.; Gruner, D.; Richter, A.; Loskill, P. Membrane integration into PDMS-free microfluidic platforms for organ-on-chip and analytical chemistry applications. Lab Chip 2021, 21, 1866–1885.
  67. Abhyankar, V.V.; Wu, M.; Koh, C.Y.; Hatch, A.V. A reversibly sealed, easy access, modular (SEAM) microfluidic architecture to establish in vitro tissue interfaces. PLoS ONE 2016, 11, e0156341.
  68. Yang, J.; Liu, X.; Fu, Y.; Song, Y. Recent advances of microneedles for biomedical applications: Drug delivery and beyond. Acta Pharm. Sin. B 2019, 9, 469–483.
  69. Kashaninejad, N.; Munaz, A.; Moghadas, H.; Yadav, S.; Umer, M.; Nguyen, N.-T. Microneedle Arrays for Sampling and Sensing Skin Interstitial Fluid. Chemosensors 2021, 9, 83.
  70. Ballesteros Hernando, J.; Ramos Gómez, M.; Díaz Lantada, A. Modeling Living Cells Within Microfluidic Systems Using Cellular Automata Models. Sci. Rep. 2019, 9, 14886.
  71. Zahorodny-Burke, M.; Nearingburg, B.; Elias, A.L. Finite element analysis of oxygen transport in microfluidic cell culture devices with varying channel architectures, perfusion rates, and materials. Chem. Eng. Sci. 2011, 66, 6244–6253.
  72. Kheiri, S.; Kumacheva, E.; Young, E.W.K. Computational Modelling and Big Data Analysis of Flow and Drug Transport in Microfluidic Systems: A Spheroid-on-a-Chip Study. Front. Bioeng. Biotechnol. 2021, 9, 781566.
  73. Narasimhan, A.; Joseph, A. Porous Medium Modeling of Combined Effects of Cell Migration and Anisotropicity of Stratum Corneum on Transdermal Drug Delivery. J. Heat Transf. 2015, 137, 121007.
  74. Graf, B.W.; Boppart, S.A. Imaging and Analysis of Three-Dimensional Cell Culture Models BT—Live Cell Imaging: Methods and Protocols; Papkovsky, D.B., Ed.; Humana Press: Totowa, NJ, USA, 2010; pp. 211–227. ISBN 978-1-60761-404-3.
  75. Arlk, Y.B.; Van Der Helm, M.W.; Odijk, M.; Segerink, L.I.; Passier, R.; Van Den Berg, A.; Van Der Meer, A.D. Barriers-on-chips: Measurement of barrier function of tissues in organs-on-chips. Biomicrofluidics 2018, 12, 042218.
  76. Zhang, Y.S.; Aleman, J.; Shin, S.R.; Kilic, T.; Kim, D.; Shaegh, S.A.M.; Massa, S.; Riahi, R.; Chae, S.; Hu, N.; et al. Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors. Proc. Natl. Acad. Sci. USA 2017, 114, E2293–E2302.
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Subjects: Engineering, Biomedical; Cell & Tissue Engineering
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : Patricia Zoio , Abel Oliva
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