Recreating Human Lung Function on a Chip: Progress in Biomaterials, Cellular Models, and Environmental Signals

Introduction

Recreating Human Lung Function on a Chip: Progress in Biomaterials, Cellular Models, and Environmental Signals Introduction Respiratory diseases impose a massive global health burden, with conditions such as COPD, lung cancer, and infections (e.g. influenza, COVID-19) contributing to respiratory failure as one of the leading causes of mortality worldwide (Soriano et al.). Thus, the rapid discovery of effective new therapeutics for lung diseases is an urgent priority. However, drug development in the respiratory field remains hindered by the difficulty of accurately modeling lung physiology in the preclinical system. Conventional preclinical models, such as 2D, 3D and animal models, often do not represent the cellular architecture, mechanical stressors, and physiological responses of the human lung, leading to poor predictive power for human outcomes (Jensen and Teng).

In the past decade, organ-on-a-chip (OOC) technology has emerged as a promising solution to address these limitations by recreating human organ physiology within microengineered devices. An organ-on-a-chip is essentially a microfluidic cell culture device containing tiny, continuously perfused chambers lined with living cells that replicates key aspects of an organ’s structural and functional environment (Bhatia and Ingber). First conceptualized and demonstrated in the early 2000s, OOCs employ microfabrication techniques to reproduce physiological interactions among multiple cell types, perfusion of fluids, mechanical stimuli, and relevant extracellular matrix components, providing realistic in vitro microenvironments (Huh et al.).

Specifically, lung-on-a-chip (LOC) devices have been extensively developed to address respiratory research gaps. The LOC system by Huh et al in 2010 replicated the human alveolar-capillary interface through microfluidic channels separated by a flexible, porous membrane lined by alveolar epithelial and pulmonary endothelial cells (Huh et al.). This system uniquely incorporated cyclic mechanical strain to simulate breathing motions, resulting in physiological responses such as surfactant production, barrier integrity, and inflammatory reactions similar to in vivo conditions. Since then, numerous advancements in LOC technology have incorporated diverse cell types, patient-specific cells (including induced pluripotent stem cells), improved biomimetic materials (such as biological membranes and hydrogels), and more sophisticated stimuli and signals (O. Stucki et al.)(Zamprogno et al.).

Given these advantages, LOC technology represents a shift in preclinical research, promising enhanced accuracy, higher predictive value for clinical outcomes, reduction in animal experimentation, and substantial acceleration of the drug development process (Francis et al.). However, ongoing efforts are required to address current challenges such as standardization, integration with other organ systems, optimising the biomaterials that are used, and physiological relevance of these systems, paving the way for widespread adoption of LOC platforms in biomedical research. This paper will focus on evaluating the core components of the tissue engineering triad within lung-on-a-chip systems: cells, biomaterials, and signals, with an emphasis on how each contributes to physiological relevance of LOC systems. By analyzing these three pillars, it will highlight the strengths and limitations of current models.

Types of Cells

Primary Cells

Primary lung cells originate from human lung tissue that obtains its cells from donor lungs and surgical resections. The relevant primary cells for lung-on-chip research consist of alveolar epithelial cells (type I and II pneumocytes) and airway epithelial cells (bronchial or small airway cells) along with lung microvascular endothelial cells and fibroblasts (Campillo et al.). Several lung-on-chip systems employ primary human cells to establish the alveolar-capillary barrier structure (Stucki et al.). The majority of current research involving microfluidic alveolar-on-chip systems depends on primary human lung cells as their epithelial source (owing to their superior physiological relevance) (Wang et al.). The specialized traits of native tissue remain present in primary lung cells. Comparisons between A549 cell lines against primary cells show that cells from cell lines are far less sensitive to cyclic strain compared to primary cells, suggesting that they do not accurately represent the response to mechanical cues seen in native cells of the lung (Lagowala et al.). Furthermore, primary cells can also be used to create personalized OOCs.

The main disadvantages of primary cells include their brief lifespan as well as donor-specific characteristics. The specialized nature of lung epithelial cells leads to cultured cells losing their ability to reproduce (Min et al.) The use of primary cells in experiments results in inconsistent outcomes because different donors exhibit different phenotypes. Furthermore, when available, yields are low and the cells usually cannot be expanded long-term – most primary lung cells have a finite number of population (Ronaldson-Bouchard and Vunjak-Novakovic). Another challenge specific to pneumocytes found in the lung is that in culture, primary ATII cells quickly differentiate into ATI cells after a couple days, making it harder to study ATII cells and more importantly, accurately model the alveolar epithelium in LOC models (Lagowala et al.).

Immortalized Cell Lines

Immortalized Cell Lines are continuously propagating cells often derived from tumors (e.g. A549 alveolar carcinoma cells) or engineered by viral genes (e.g. SV40-transformed bronchial cells) (Campillo et al.)(Min et al.). They proliferate indefinitely and form relatively homogeneous populations (Min et al.). This allows them to be more cost-effective as they do not require an ongoing donor tissue supply, thus avoiding the ethical and economic hurdles of using animal or human tissue. Furthermore, because cell lines can be reproduced endlessly, they are ideal for high-throughput studies (Kaur and Dufour). For instance, A549 and H441 cell lines have been widely used to model alveolar epithelium in lung-on-chip studies, showing robust growth and injury-response profiles (Campillo et al.). Despite not being native to human tissue, studies have shown that they can be manipulated to accurately mimic in-vivo conditions. Cell lines such as NCI-H441 (alveolar type II cells) and NCI-H1703 (alveolar type I cells) have been used in alveolus-on-a-chip technology to successfully form a tight epithelium that secretes surfactant (Kang et al.). Such models, if using native tissue, do not last a long time due to the fact that ACII cells easily differentiate into ACI cells, making it harder to observe the effect of surfactant on alveolus-on-a-chip systems (Lagowala et al.).

However, their physiological relevance is limited. Being cancer-derived or genetically altered, they often fail to fully perform specialized functions of normal lung cells. Prolonged culturing can further drift their phenotype, compounding reproducibility issues (Kaur and Dufour). During immortalization, cells undergo genetic changes that can alter their native physiology. Thus, while immortalized lines are convenient and economical, their divergence from in vivo cell behavior is a significant drawback. An example of this is seen in A549 cell lines which demonstrate alveolar-like characteristics but they fail to produce sufficient phosphatidylglycerol which is a crucial surfactant lipid and they show different ion transport patterns than actual alveolar type II cells (Lagowala et al.). Furthermore, as explained before, they are not as sensitive to biomechanical cues as primary cells. Lastly, immortalised cells lines may also drift genetically over time and are far more prone to contamination (Kaur and Dufour).

Stem Cells

Stem cell technologies offer human cells as an alternative resource for constructing organ-on-chip models. The reprogramming of adult cells into embryonic-like cells through induced pluripotent stem cells (iPSCs) enables unlimited expansion followed by differentiation into multiple lung cell types (Ronaldson-Bouchard and Vunjak-Novakovic). Scientists use developmental growth factors (as demonstrated by Takahashi and Yamanaka in 2006) to transform iPSCs into specialised cells, for example in LOCs, iPSCs can differentiate into alveolar type II–like cells and airway epithelial cells which mimic lung organogenesis (Takahashi and Yamanaka).

A key advantage of iPSC technology is that it avoids the continuous need for donor tissue. Like immortalised cell lines, it can be virtually expanded without limit (Kaur and Dufour). In addition, iPSCs can be differentiated into multiple cell types. The lung is composed of approximately 40 different cell types, thus allowing iPSCs to conveniently allow the assembly of complex co-culture chips where all cell types share the same genetic source (Calvert and Ryan (Firth)). Biologically, stem cell-derived lung cells can capture certain developmental or disease-relevant states that primary cells do not. For example, iPSC-derived alveolar cells can represent neonatal lung cells or an intermediate “transitional” phenotype implicated in lung fibrosis (Tamai et al.).

Differentiating iPSCs into adult, functional lung cells is a time-consuming and complex process as it requires step-by-step exposure to multiple growth factors (activin A, BMP/Wnt inhibitors, FGF10, dexamethasone, etc.) which can take 4-8 weeks to fully recapitulate embryonic lung development in a dish (Lagowala et al.). Even after this effort, the resulting cells often resemble fetal or immature lung cells rather than fully mature adult cells. For instance, iPSC-derived cells typically exhibit an incomplete functional maturation compared to primary ATII cells. They also tend to lose some epigenetic marks of the donor’s age and environment during reprogramming, which could erase certain disease-related signatures (Ronaldson-Bouchard and Vunjak-Novakovic).

Materials

Polydimethylsiloxane (PDMS)

Lab-on-a-chip prototyping standardizes PDMS, silicone elastomer material, because of its low fabrication costs and easy manufacturing process (Elveflow). Soft lithography techniques create precise replicas of micron-scale features by casting PDMS into microfluidic channels . PDMS devices have become fundamental tools for cell biology and organ-on-chip research because they include thin PDMS membranes which duplicate breathing motions. (Carvell et al.) In fact, the first lung-on-a-chip developed by Huh et al. (2010) used a 10 μm porous PDMS membrane to recreate breathing motions, enabling co-culture of alveolar and endothelial layers at an air–liquid interface with cyclic strain that reproduced lung physiology (Huh et al.). PDMS-based chips become suitable for cell culture through surface treatments like plasma oxidation and protein coatings that create conditions for robust cell growth similar to traditional cultureware (Tanyeri and Tay).

The optical transparency of PDMS allows direct observation of cells and fluids and it possesses elastic properties with a large Young’s modulus which enables flexible microvalve and peristaltic pump integration (Elveflow). Stucki et al. (2018) demonstrated how PDMS’s elasticity and transparency enabled the fabrication of an ultrathin 3.5 μm PDMS membrane that supported primary alveolar cells under strain while preserving physiological functions (Stucki et al.). PDMS enables gas exchange between cell chambers and their environment because oxygen and CO₂ pass through the material with high permeability (O₂ permeability ~3.4×10^ –6 cm^2/s) (Tanyeri and Tay). The oxygen reservoir properties of thick PDMS walls sustain cellular oxygenation during extended perfusion operations, as shown in long-term lung-on-chip cultures where PDMS supported weeks of epithelial–endothelial co-culture under cyclic stretch. It exhibits minimal curing shrinkage while forming permanent bonds to glass substrates and itself which facilitates multi-layer device assembly (Tanyeri and Tay). The material exhibits biocompatibility and allows surface modification through plasma oxidation to create temporary hydrophilic surfaces that enhance cell attachment (Cao et al.). The combination of PDMS properties with quick prototyping workflows creates a versatile material for designing microfluidic systems through multiple iterations.

The material remains popular despite several significant drawbacks. The inherent hydrophobic nature of PDMS makes it absorb small hydrophobic molecules present in aqueous solutions (Alghannam et al.). Zamprogno et al. (2021) reported that PDMS absorbed drugs and fluorescent dyes in lung-chip experiments, altering effective concentrations and skewing pharmacological readouts (Zamprogno et al.). Experimental results become biased because PDMS absorbs or adsorbs drug compounds and signaling molecules that are present in media. PDMS exhibits natural protein binding behavior that may lead to surface fouling unless surface treatment or lipophilic coating methods are applied (Alghannam et al.).Flow pressure causes soft PDMS channels to deform because of their elastic properties which results in dimensional changes (Cao et al.). For example, Stucki et al. (2018) noted that cyclic strain on thin PDMS membranes risked mechanical fatigue and buckling when pressure was not carefully controlled (Stucki et al.). The material properties of PDMS make it difficult to perform applications that require precise fluid control because channel deformation occurs under flow pressure conditions. Most organic solvents damage or swell PDMS which restricts its compatibility with solvent-based reagents. The combination of permeability and flexibility in PDMS leads to negative effects in certain situations since evaporation creates bubbles and flexible walls produce inconsistent results (Elveflow). Zamprogno et al. (2021) further highlighted that the stiffness of PDMS is non-physiological compared to the compliant alveolar basement membrane, which in some cases induced fibrotic-like responses in cultured lung cells (Zamprogno et al.). The need for additional materials arose due to the development of advanced solutions for applications that require more complex solutions.

ECM-Derived materials

The terms “ECM-derived” describe biomaterials which originate from tissue extracellular matrix (ECM) and include both structural proteins along with other macromolecules where cells naturally reside. Materials in this class include collagen (particularly Type I collagen), fibrin derived from fibrinogen blood protein, laminin-rich Matrigel (a basement membrane extract from murine tumors), gelatin (denatured collagen) and decellularized tissue matrices converted into hydrogels (Kim et al.). To duplicate the basement membrane cells naturally adhere to in vivo, researchers apply a thin layer of Matrigel or collagen onto porous membranes or channel surfaces. The use of ECM-derived materials stems from the need to replicate the natural biochemical signals and tissue-like environments which synthetic plastics do not offer (Cao et al.). Zamprogno et al. (2021) demonstrated this by engineering a collagen–elastin (CE) membrane that replaced PDMS in a lung-on-chip, enabling cyclic breathing strains with native-like elasticity and providing a more biomimetic surface for alveolar–endothelial co-culture (Zamprogno et al.).

The main advantages of ECM-derived hydrogels include their high biocompatibility and bioactivity which enables cell attachment, differentiation, and function. The natural composition of proteins and glycoproteins within these matrices makes cells recognize them so they display in vivo-like characteristics including morphology, polarity, and gene expression during culture (Cao et al.). For example, Huang et al. (2021) created a GelMA hydrogel scaffold with alveolus-sized pores in a lung chip, showing that alveolar epithelial cells formed tight junctions and maintained physiological phenotypes far better than on flat PDMS membranes (Huang et al.). The binding sites found in collagen function as a cell adhesion pathway that triggers signaling processes while influencing both cell morphology and developmental fate in ways that match actual connective tissue (Osório et al.) . These ECM hydrogels are also biodegradable, which enables dynamic remodeling (Cao et al.); Shen et al. (2023) used an F127-diacrylate hydrogel membrane that degraded under cell-driven remodeling but still maintained barrier function during breathing motions. Such features enabled the chip to distinguish between physiological strain (which preserved cell health) and pathological strain (which triggered fibrosis), a nuance lost with PDMS substrates (Shen et al.).

The primary disadvantage of utilizing native ECM materials is their weak mechanical properties and short-lived stability. Such hydrogels possess an extremely fragile structure because they contain mostly water, which leads them to deform or collapse under perfusion (Ho et al.). Zamprogno et al. (2021) noted that fabricating sub-10 µm collagen–elastin membranes required specialized drying and handling techniques to prevent rupture, making manufacturing difficult (Zamprogno et al.). Pure collagen gels shrink under tension, while fibrin gels degrade within days unless cross-linked, limiting their utility for long-term cultures (Sanz-Horta et al.). Matrigel poses additional problems: its tumor-derived composition is variable between batches, making reproducibility low (Kim et al.) Shen et al. (2023) reported that switching from PDMS to hydrogel membranes improved fidelity but introduced challenges in controlling thickness and uniformity at scale (Shen et al.).

Hydrogels

The water-rich polymer networks known as hydrogels duplicate both the physical structure and biochemical properties of soft tissues (Gnatowski et al.). This section includes both ECM-derived materials such as collagen or fibrin that fall under the category of hydrogels and synthetic and engineered hydrogel systems that extend past direct ECM extracts. The main application of hydrogels in OOC engineering is to create three-dimensional scaffolds that enable cells to grow naturally while interacting and responding better than they do on rigid surfaces (Carvell et al.). Huang et al. (2021) illustrated the former with a GelMA hydrogel alveolar scaffold that replicated lung alveoli geometry and improved alveolar epithelial function (Huang et al.). Shen et al. (2023) illustrated the latter with a hydrogel membrane substituting PDMS, which enabled realistic diffusive transport and preserved normal barrier responses (Shen et al.).

Hydrogels achieve native ECM simulation through their water-rich structure combined with adjustable elasticity and natural biocompatibility (Cao et al.). The elastic properties of hydrogels can be tuned to match lung tissue , supporting realistic mechanotransduction (Shen et al.). Hydrogels also provide excellent nutrient diffusion and permeability, sustaining viability during extended air–liquid interface cultures (Liu et al.). Synthetic hydrogels such as PEG offer tunable stiffness and they can guide cell adhesion (Lin et al.). Lastly, hydrogels have been shown to be more favourable for cell-attachment as compared to PDMS. Annabi et al. (2013) further showed that cardiomyocytes display higher spontaneous beating rates on tropoelastin coated surfaces compared to gelatin, supporting the claim that tropoelastin-based hydrogels are suitable for select OOC applications (Annabi et al.).

The main limitation for LOCs is mechanical fragility. Shen et al. (2023) found that hydrogel membranes tore under excessive strain, requiring careful optimization of strain magnitude (Shen et al.). Hydrogels are also prone to swelling/shrinkage, introducing variability in microchannel dimensions and diffusion gradients (Feng and Wang). Thick hydrogels also impede perfusion, sometimes leading to hypoxia in central regions (Grebenyuk et al.). Finally, while transparency usually supports imaging, some hydrogels scatter light, reducing resolution compared to PDMS or COC (Kaberova et al.).

Signalling Cues

Mechanical Cues

The lung tissue experiences mechanical cues from cyclic stretching and blood perfusion-induced shear stress during breathing operations. The alveolar walls in living organisms undergo 5–15% expansion and retraction with each breath cycle and pulmonary capillaries maintain constant blood flow (Huh et al.). The normal development of lungs and homeostasis together with proper lung function rely on mechanical forces because breathing motions activate surfactant release and sustain alveolar architecture (Huh et al.). The absence of mechanical stimulation during cell culture results in cell dedifferentiation alongside reduced barrier functionality but appropriate mechanical stretch creates behavior that resembles living tissues (Huh et al.).

Lung-on-chip systems generate breathing movements through cell-grown membrane flexing. The first lung-on-chip device from Huh et al used cyclic vacuum inside chambers to stretch an alveolar cell-covered flexible PDMS membrane which replicated inhalation and exhalation movements. The dynamic mechanical actuation process triggered the development of tight junctions and surfactant production which duplicated the natural alveolar structure (Huh et al.). Stucki et al. (2018) demonstrated that alveolar chip permeability altered significantly after applying cyclic strain with a 10% amplitude at 0.2 Hz frequency when compared to static culture conditions (Stucki et al.). The mechanical forces of stretching influence pathological processes because researchers found that cyclic strain increased inflammatory responses to inhaled particles as a lung would during breathing movements (Huh et al.). The mechanical cue of fluid shear stress functions in lung chips may also improve nutrient delivery while promoting endothelial cell alignment for better vascular modeling (Corral-Nájera et al.). Thus, the scientific consensus may indicate that mechanical stretch integration produces a more realistic model of the lung

Inflammatory Signals

The implementation of inflammatory cues follows different approaches in Lung-on-Chips research. Researchers achieve inflammatory responses by adding cytokines from outside sources to the chip system. Benam et al. (2016) studied bronchial epithelium on-chip responses to IL-13 exposure which resulted in asthmatic characteristics such as goblet cell hyperplasia together with cytokine hypersecretion and decreased ciliary function (Benam et al., “Small Airway-On-a-Chip Enables Analysis of Human Lung Inflammation and Drug Responses in Vitro”). The model developed an asthma-like state which included excessive mucus production alongside dysfunctional cilia and could be treated with pharmaceuticals during the chip experiments. The alternative method of microfluidic channel introduction includes adding immune cells to the system. Huh et al. developed the first lung-on-a-chip system by using human neutrophils to perfuse through its vascular channel. After bacterial infection of the alveolar channel neutrophils passed through the membrane to perform microbial phagocytosis exactly like a natural immune response. The model produced organ-level responses through cytokine-driven neutrophil recruitment and bacterial clearance by incorporating inflammatory signaling. The model reached this organ-level behavior by incorporating inflammatory signaling which produced cytokine-mediated neutrophil recruitment and bacterial clearance (Huh et al.).

Environmental Signals

The design of Lung-on-Chip systems enables researchers to simulate external environmental stimuli such as cigarette smoke, air pollution particles (PM2.5), and airborne viruses through appropriate physiological methods. Researchers Benam et al. (2016) created a smoking machine connection to small-airway-on-chip to replicate human smoker inhalation by delivering whole cigarette smoke puffs through the air–liquid interface through a smoking machine which simulated the breathing patterns of human smokers. In their study they found that when exposed to cigarette smoke, 276 genes were expressed in COPD chips which were otherwise not expressed in the absence of smoke (Benam et al.). Huang et al. devised a human 3D alveolar-chip with cyclic stretch and exposed it to whole cigarette smoke and SARS-CoV-2 pseudovirus. Smoke puff exposure (via a smoking robot) induced oxidative stress and cell death in the chip epithelium (e.g. increased 4-HNE and caspase activity), mimicking early smoke damage. In the same chip, infection with SARS-CoV-2 pseudovirus produced the expected cytopathic effects and IL‑8 induction, which could be blunted by antiviral drugs (Huang et al.). Chips have also modeled airborne pathogens: Bai et al. infected a breathing alveolus chip with influenza A (H3N2). They found that dynamic breathing strain triggered protective innate responses (reduced viral replication, cytokine release, apoptosis) that were absent in non-breathing controls (Bai et al.). A recent study employed lung-on-a-chip technology to replicate human lung exposure to environmental air pollution (fine particulate matter, PM₂.₅) in actual environmental conditions. The microfluidic 3D model contained human alveolar epithelial cells and microvascular endothelial cells which were co-cultured to establish an alveolar-capillary interface before receiving an acute PM₂.₅ exposure. The high-dose PM₂.₅ exposure caused damage to the lung barrier through adherens junction disruption while creating oxidative stress and cell death and activating inflammation through elevated cytokine/chemokine expression in both alveolar epithelium and endothelium (Xu et al.).

Conclusion

Lung-on-a-chip technology has evolved significantly as a biomimetic model of the human lung yet there are still important gaps in completely mimicking lung physiology. Two promising innovation areas are driving the field forward. The second generation of researchers is working on developing bioinspired, dynamic biomaterials to better mimic the lung’s architecture and mechanics. The traditional PDMS membranes used in lung chips have been replaced with stretchable biological scaffolds (e.g. collagen–elastin) that form in vivo-sized alveoli and mimic the native extracellular matrix. Such bioinspired membranes outperform PDMS by eliminating unwanted drug absorption and offering tunable thickness and stiffness, thereby preserving normal lung cell function over weeks (Zamprogno et al.). Indeed, replacing artificial substrates with hydrogels or elastic biomembranes and applying physiological cyclic strain yields a more lifelike alveolar microenvironment (Brandauer et al.). These material innovations greatly enhance the biological fidelity of lung-on-chips, helping cells maintain phenotypes and responses closer to those in real lung tissue, which is crucial for predictive modeling.

The integration of lung-on-a-chip systems into multi-organ platforms has emerged as a strategy to capture systemic disease interactions and whole-body drug responses. Microphysiological systems which connect the lung module with other organ models via fluid flow enable the study of organ–organ interdependence as well as the assessment of how distant tissues affect lung pathology or drug effects (Brandauer et al.). Early demonstrations have linked lung chips with liver, brain, and other organ compartments to reveal interdependent responses. For instance, a liver spheroid module in a lung-on-chip has been shown to metabolize and detoxify an inhaled toxicant and thus reduce lung tissue injury from exposure (Brandauer et al.). In another study, a four-organ platform (lung, liver, brain, bone) was used to simulate the metastatic spread of lung cancer and to allow simultaneous assessment of drug efficacy in multiple organs (Zhang et al.). These integrated systems increase model complexity by including circulation, metabolism, and multi-organ signaling which capture human pharmacokinetic and disease processes that single-organ chips cannot and thus improve the clinical relevance of the experiments. In the future, the improved physiological realism and the incorporation of inter-organ interactions in next-generation lung-on-chips will provide more reliable preclinical data that bridges the translation gap between in vitro findings and clinical outcomes (Doryab et al.). Ultimately, such innovations will bring LOC technology nearer to practical biomedical and pharmaceutical applications, helping realize the vision of human-relevant lung models for research and therapy.

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