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Updated: Dec 24, 2025

3D Cell-Printed Hypoxic Cancer-on-a-Chip for Recapitulating Pathologic Progression of Solid Cancer
Published on: January 5, 2021
Engineering Patient-on-a-Chip Models for Personalized Cancer Medicine
David Caballero1,2, Rui L Reis3,4,5, Subhas C Kundu3,4
13B's Research Group, I3Bs - Research Institute on Biomaterials, Biodegradables and Biomimetics, University of Minho, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, Barco, Guimarães, Portugal. dcaballero@i3bs.uminho.pt.
Abstract:
Traditional in vitro and in vivo models typically used in cancer research have demonstrated a low predictive power for human response. This leads to high attrition rates of new drugs in clinical trials, which threaten cancer patient prognosis. Tremendous efforts have been directed towards the development of a new generation of highly predictable pre-clinical models capable to reproduce in vitro the biological complexity of the human body. Recent advances in nanotechnology and tissue engineering have enabled the development of predictive organs-on-a-chip models of cancer with advanced capabilities. These models can reproduce in vitro the complex three-dimensional physiology and interactions that occur between organs and tissues in vivo, offering multiple advantages when compared to traditional models. Importantly, these models can be tailored to the biological complexity of individual cancer patients resulting into biomimetic and personalized cancer patient-on-a-chip platforms. The individualized models provide a more accurate and physiological environment to predict tumor progression on patients and their response to drugs. In this chapter, we describe the latest advances in the field of cancer patient-on-a-chip, and discuss about their main applications and current challenges. Overall, we anticipate that this new paradigm in cancer in vitro models may open up new avenues in the field of personalized - cancer - medicine, which may allow pharmaceutical companies to develop more efficient drugs, and clinicians to apply patient-specific therapies.
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