Recent advances of microfluidic organ-on-a-chip monitoring strategies
Electrospun Nanofibers, Elsevier, ss.415-468, 2025
- Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
- Basım Tarihi: 2025
- Doi Numarası: 10.1016/b978-0-443-21519-3.00029-7
- Yayınevi: Elsevier
- Sayfa Sayıları: ss.415-468
- Anahtar Kelimeler: chip integrated monitoring systems, deep learning in organ chip models, diseases-on-a-chip, multi-organ-chip, organ-chip simulation, Organ-on-a-chip
- Eskişehir Osmangazi Üniversitesi Adresli: Evet
Özet
In the drug discovery process and study of disease, there has been a fundamental change towards physiologically appropriate and short response time in vitro models in recent years. The constraints of standard cell culture techniques, which frequently fail to replicate the complex microenvironment and dynamic interactions of human organs, have mainly promoted to work on novel models. As a result, the development of organ-on-a-chip systems (OoCs) has transformed the landscape of in vitro experimentation. They are biomimetic in vitro systems that can be customised to investigate organ-specific physiology, pathology or pharmacology. Thanks to this ground-breaking technology, researchers may now analyse organ-level reactions to stimuli, drug interactions and disease progression with unparalleled fidelity. Furthermore, introducing integrated monitoring systems (IMS) has expanded the potential of OoC systems. IMS uses cutting-edge sensor technology and analytical tools to provide real-time, continuous monitoring of cellular behaviour, tissue shape, metabolic indicators, fluid pressure, cell migration, tissue barrier integrity, glucose, lactate, oxygen and pH, with other key characteristics in the OoC environment, computational modelling of cell behaviour and the clinical applications in drug screening and disease modelling. Continuous monitoring of quality parameters is critical for assessing conditions and generating relevant analytical data. OoC systems and IMS have developed as crucial tools for drug development, toxicological assessments, disease modelling and personalised medicine initiatives in this quickly evolving sector. Their ability to speed up research, minimise reliance on animal models and improve the predictiveness of preclinical investigations offers enormous promise for biomedical science and medicinal development in the future. This chapter will look at the principles, applications and most recent breakthroughs in OoCs and IMS, emphasising their transformational impact on numerous aspects of biomedical research and their potential to improve healthcare practices. The last part of this chapter provides insights into the diverse applications of deep learning within OoCs, including image and video data synthesis, prediction, segmentation, tracking and recognition. The convergence of artificial intelligence’s deep learning and the innovative realm of OoC technologies holds great promise for advancing disease modelling and personalised medicine.