ArticleBiomaterials research2023
Advanced pathophysiology mimicking lung models for accelerated drug discovery.
Article in Biomaterials research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Emerging Biomaterials for Maxillary Sinus Augmentation: From In Vitro Insights to In Vivo Clinical Translation.Materials (Basel, Switzerland) · 2026Review
- Unveiling Particulate Matter-Lung Interactions from Static Models to Dynamic Lung-on-Chips.Research (Washington, D.C.) · 2026Review
- Establishing scientific confidence: human biological relevance of reconstructed human respiratory epithelium (RHRE) for assessing respiratory effects.Frontiers in toxicology · 2026Review
- Generation of Human 3D Airway Assembloids for Advanced Modeling.International journal of biological sciences · 2025Article
- Integrins as Drug Targets in Vascular and Related Diseases.International journal of drug discovery and pharmacology · 2024Article
- Particulate Matter Induces Oxidative Stress and Ferroptosis in Human Lung Epithelial Cells.Toxics · 2024Article
- Opportunities and Challenges for Inhalable Nanomedicine Formulations in Respiratory Diseases: A Review.International journal of nanomedicine · 2024Review
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Authors and funding
11 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRespiratory diseases are the 2nd leading cause of death globally. The current treatments for chronic lung diseases are only supportive. Very few new classes of therapeutics have been introduced for lung diseases in the last 40 years, due to the lack of reliable lung models that enable rapid, cost-effective, and high-throughput testing. To accelerate the development of new therapeutics for lung diseases, we established two classes of lung-mimicking models: (i) healthy, and (ii) diseased lungs - COPD.
methodsTo establish models that mimic the lung complexity to different extents, we used five design components: (i) cell type, (ii) membrane structure/constitution, (iii) environmental conditions, (iv) cellular arrangement, (v) substrate, matrix structure and composition. To determine whether the lung models are reproducible and reliable, we developed a quality control (QC) strategy, which integrated the real-time and end-point quantitative and qualitative measurements of cellular barrier function, permeability, tight junctions, tissue structure, tissue composition, and cytokine secretion.
resultsThe healthy model is characterised by (i) continuous tight junctions, (ii) physiological cellular barrier function, (iii) a full thickness epithelium composed of multiple cell layers, and (iv) the presence of ciliated cells and goblet cells. Meanwhile, the disease model emulates human COPD disease: (i) dysfunctional cellular barrier function, (ii) depletion of ciliated cells, and (ii) overproduction of goblet cells. The models developed here have multiple competitive advantages when compared with existing in vitro lung models: (i) the macroscale enables multimodal and correlative characterisation of the same model system, (ii) the use of cells derived from patients that enables the creation of individual models for each patient for personalised medicine, (iii) the use of an extracellular matrix proteins interface, which promotes physiological cell adhesion and differentiation, (iv) media microcirculation that mimics the dynamic conditions in human lungs.
conclusionOur model can be utilised to test safety, efficacy, and superiority of new therapeutics as well as to test toxicity and injury induced by inhaled pollution or pathogens. It is envisaged that these models can also be used to test the protective function of new therapeutics for high-risk patients or workers exposed to occupational hazards.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.