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Park, Tae-Eun
Microtissue Engineering & Nanomedicine Lab
Research Interests
  • Drug delivery, Drug development, Tissue Engineering, Organ-on-a-chip, Stem Cell Engineering, Cell Biology, 3D printing for tissue engineering, Neurobiology, Nano Biotechnology

Integrated technologies for continuous monitoring of organs-on-chips: Current challenges and potential solutions

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Title
Integrated technologies for continuous monitoring of organs-on-chips: Current challenges and potential solutions
Author
Sabaté del Río, JonathanRo, JooyoungYoon, HeejeongPark, Tae-EunCho, Yoon-Kyoung
Issue Date
2023-03
Publisher
Pergamon Press Ltd.
Citation
BIOSENSORS & BIOELECTRONICS, v.224, pp.115057
Abstract
Organs-on-chips (OoCs) are biomimetic in vitro systems based on microfluidic cell cultures that recapitulate the in vivo physicochemical microenvironments and the physiologies and key functional units of specific human organs. These systems are versatile and can be customized to investigate organ-specific physiology, pathology, or pharmacology. They are more physiologically relevant than traditional two-dimensional cultures, can potentially replace the animal models or reduce the use of these models, and represent a unique opportunity for the development of personalized medicine when combined with human induced pluripotent stem cells. Continuous monitoring of important quality parameters of OoCs via a label-free, non-destructive, reliable, high-throughput, and multiplex method is critical for assessing the conditions of these systems and generating relevant analytical data; moreover, elaboration of quality predictive models is required for clinical trials of OoCs. Presently, these analytical data are obtained by manual or automatic sampling and analyzed using single-point, off-chip traditional methods. In this review, we describe recent efforts to integrate biosensing technologies into OoCs for monitoring the physiologies, functions, and physicochemical microenvironments of OoCs. Furthermore, we present potential alternative solutions to current challenges and future directions for the application of artificial intelligence in the development of OoCs and cyber-physical systems. These “smart” OoCs can learn and make autonomous decisions for process optimization, self-regulation, and data analysis.
URI
https://scholarworks.unist.ac.kr/handle/201301/60870
DOI
10.1016/j.bios.2022.115057
ISSN
0956-5663
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BME_Journal Papers
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