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Microfluidic Organ-on-a-Chip Models: Replicating Human Physiology for Drug Testing and Disease Study

EasyChair Preprint 11473

8 pagesDate: December 7, 2023

Abstract

Microfluidic Organ-on-a-Chip (OOC) models have emerged as innovative platforms that mimic human physiology at a microscale level, offering promising opportunities for drug testing and disease modeling. These biomimetic systems integrate microengineering, cell biology, and biochemistry to replicate the functionalities of human organs in vitro. By recapitulating key aspects of organ physiology, such as tissue architecture, cellular interactions, and organ-specific functions, OOC models provide a more accurate representation of human biology compared to conventional cell cultures and animal models. This review outlines the recent advancements in the development and application of Microfluidic Organ-on-a-Chip models for drug screening and disease studies. The miniaturized nature of these platforms allows for precise control over cellular microenvironments, enabling the simulation of physiological conditions and disease states. Consequently, OOC models offer a platform for investigating drug efficacy, toxicity, and pharmacokinetics with higher relevance to human responses. Furthermore, the ability to create multi-organ systems interconnected through microfluidic channels facilitates the study of organ crosstalk and systemic effects, enabling a more comprehensive understanding of drug metabolism and disease mechanisms. Moreover, these platforms hold promise for personalized medicine by utilizing patient-derived cells to create organ models tailored to individual responses and pathologies.

Keyphrases: Drug testing, Microfluidics, Organ-on-a-chip

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:11473,
  author    = {Smith Milson and Ayaan Rio},
  title     = {Microfluidic Organ-on-a-Chip Models: Replicating Human Physiology for Drug Testing and Disease Study},
  howpublished = {EasyChair Preprint 11473},
  year      = {EasyChair, 2023}}
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