{"title":"Organ-on-chip technologies: Novel tools with the potential to revolutionize osteoarthritis research and clinical development","authors":"Carlo Alberto Paggi","doi":"10.1016/j.ocarto.2025.100686","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>To critically evaluate the evolution of in vitro models for osteoarthritis (OA) research, with a specific focus on organ-on-chip (OOC) technologies, and to discuss their potential to overcome the limitations of traditional 2D, 3D, and explant models in disease modelling, drug discovery, and preclinical toxicology.</div></div><div><h3>Methods</h3><div>This review synthesizes findings from recent literature regarding historical and current in vitro platforms used in OA research. It categorizes models based on biological complexity and physiological relevance, with particular emphasis on biomechanical and biochemical stimulation in OOC systems. Key examples from the literature are discussed to illustrate the utility and scalability of emerging platforms.</div></div><div><h3>Results</h3><div>Traditional 2D cultures, while widely used, lack the spatial and environmental complexity necessary to replicate native joint physiology. 3D cultures and explant models provide improved architecture and cellular context, but face challenges related to standardization, longevity, and reproducibility. OOC systems offer a dynamic and tunable microenvironment that supports real-time monitoring and integration of mechanical cues such as shear stress and compression. These platforms have been successfully employed to investigate immune cell migration, drug permeability across barriers, and cytokine-induced matrix degradation. Furthermore, their application in preclinical modelling for efficacy and safety studies highlights the potential for more predictive, human-relevant data compared to conventional methods.</div></div><div><h3>Conclusion</h3><div>OOCs technology represents a transformative advance in OA modelling, offering increased physiological relevance and experimental precision. With continued refinement and validation, OOC platforms could significantly improve the translational success of disease-modifying OA therapies.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100686"},"PeriodicalIF":2.8000,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Osteoarthritis and cartilage open","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665913125001220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective
To critically evaluate the evolution of in vitro models for osteoarthritis (OA) research, with a specific focus on organ-on-chip (OOC) technologies, and to discuss their potential to overcome the limitations of traditional 2D, 3D, and explant models in disease modelling, drug discovery, and preclinical toxicology.
Methods
This review synthesizes findings from recent literature regarding historical and current in vitro platforms used in OA research. It categorizes models based on biological complexity and physiological relevance, with particular emphasis on biomechanical and biochemical stimulation in OOC systems. Key examples from the literature are discussed to illustrate the utility and scalability of emerging platforms.
Results
Traditional 2D cultures, while widely used, lack the spatial and environmental complexity necessary to replicate native joint physiology. 3D cultures and explant models provide improved architecture and cellular context, but face challenges related to standardization, longevity, and reproducibility. OOC systems offer a dynamic and tunable microenvironment that supports real-time monitoring and integration of mechanical cues such as shear stress and compression. These platforms have been successfully employed to investigate immune cell migration, drug permeability across barriers, and cytokine-induced matrix degradation. Furthermore, their application in preclinical modelling for efficacy and safety studies highlights the potential for more predictive, human-relevant data compared to conventional methods.
Conclusion
OOCs technology represents a transformative advance in OA modelling, offering increased physiological relevance and experimental precision. With continued refinement and validation, OOC platforms could significantly improve the translational success of disease-modifying OA therapies.