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Gross Anatomy of the Liver

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The liver, the largest gland within the human body, is a firm and reddish-brown organ. This wedge-shaped structure weighs approximately 1.5 kg and occupies a significant portion of the right hypochondriac and epigastric regions. It extends more to the right of the body's midline than to the left.
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Related Experiment Video

Updated: May 1, 2026

Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro

Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro

Published on: January 31, 2022

Engineering liver.

Linda G Griffith¹, Alan Wells, Donna B Stolz

¹Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA.

Hepatology (Baltimore, Md.)

|March 27, 2014

Summary

This summary is machine-generated.

Engineering the human liver involves experimental and computational approaches. Combining these methods offers new insights into disease and accelerates drug development by creating better liver models.

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Area of Science:

Bioengineering
Systems Biology
Drug Development

Background:

The engineering of liver models is driven by needs in therapeutic replacement, mechanistic studies, and drug testing.
Advances in microfabrication and biomaterials offer opportunities for creating microphysiological liver models.
Computational systems biology is also advancing in modeling complex diseases and interpreting drug response data.

Purpose of the Study:

To explore the interplay between experimental and computational approaches in liver engineering.
To highlight how these complementary fields can advance understanding of human disease and drug development.

Main Methods:

Review of emerging micro- and nanofabrication, biomaterials, and microfluidic technologies for liver modeling.
Discussion of computational systems biology approaches for disease modeling and data interpretation.
Analysis of the integration of experimental and computational strategies.

Main Results:

Engineering design principles for liver models are still developing.
Computational systems biology provides tools for analyzing complex disease processes and patient data.
The synergy between experimental and computational liver engineering is beginning to yield significant insights.

Conclusions:

Integrating experimental and computational liver engineering is crucial for advancing human disease research.
This combined approach promises to enhance drug efficacy and toxicology studies.
Further development of engineering design principles is needed for effective application of liver models.