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Microengineering the Liver: Strategies for Constructing Functional Liver-on-a-Chip Devices.

Jie Wang1, Ziwei Liang1,2,3,4, Jiapu Wang1

  • 1Department of Biomedical Engineering Research Center for Nano-Biomaterials & Regenerative Medicine College of Artificial Intelligence Shanxi Key Laboratory of Materials Strength & Structural Impact Taiyuan University of Technology Taiyuan China.

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Summary
This summary is machine-generated.

Liver-on-a-chip (LOC) technology offers advanced in vitro models for liver research. These microfluidic devices better mimic human liver physiology, improving drug screening and disease modeling compared to traditional methods.

Keywords:
deep learningdisease modelingdrug screeningliver‐on‐a‐chipmicrophysiological systems

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Area of Science:

  • Biomedical Engineering
  • Organ-on-a-chip Technology
  • Liver Physiology Research

Background:

  • Current 2D/3D cell cultures and animal models fail to accurately replicate human liver microenvironments and in vivo conditions.
  • Limitations include impaired cellular functions, lack of tissue-like architecture, species differences, and ethical concerns with animal models.
  • There is a critical need for advanced in vitro models that recapitulate human liver pathophysiology for drug development and disease research.

Purpose of the Study:

  • To review recent advancements in Liver-on-a-chip (LOC) technologies.
  • To highlight innovative strategies in biomimetic tissue engineering, extracellular matrix construction, and microphysiological systems.
  • To discuss the integration of emerging technologies for enhanced physiological relevance and monitoring.

Main Methods:

  • Review of recent literature on microfluidic-based Liver-on-a-chip systems.
  • Analysis of strategies for biomimetic tissue construction, including 3D bioprinting, vascularization, and incorporation of liver buds/organoids.
  • Discussion of sensor integration and deep learning for real-time monitoring.

Main Results:

  • LOC technology enables the replication of liver microstructures and tissue interfaces, simulating organ-level physiological activities.
  • Advances include enhanced biomimetic designs, 3D bioprinting, vascularization, and organoid integration for greater accuracy.
  • Integration of deep learning and sensors allows for intelligent, real-time monitoring of liver functions within LOC devices.

Conclusions:

  • Liver-on-a-chip technology represents a significant breakthrough in developing physiologically relevant in vitro liver models.
  • These models show great promise for improving drug screening accuracy and advancing liver disease modeling.
  • Further development and clinical translation of LOC technology are crucial for personalized medicine and biomedical research.