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Updated: May 7, 2026

A High-Throughput In Situ Method for Estimation of Hepatocyte Nuclear Ploidy in Mice
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Hepatotoxicity evaluation method through multiple-factor analysis using human pluripotent stem cell derived hepatic

Dae-Seop Shin1, Jung Yoon Yang1, Ha Neul Jeong1,2

  • 1Therapeutics & Biotechnology Division, Korea Research Institute of Chemical Technology, Daejeon, 34114, Republic of Korea.

Scientific Reports
|March 29, 2025
PubMed
Summary

This study presents a novel organoid model for predicting drug-induced liver injury (DILI) early in drug development. The method accurately identifies severe DILI by measuring oxidative stress and inflammation markers.

Keywords:
Drug-induced liver injuryHepatic organoidHepatotoxicity

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Last Updated: May 7, 2026

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

Published on: January 31, 2022

Area of Science:

  • Hepatology
  • Drug Development
  • Toxicology

Background:

  • Early prediction of drug-induced liver injury (DILI) is crucial for drug development safety.
  • Existing methods for DILI prediction have limitations in accuracy and physiological relevance.

Purpose of the Study:

  • To develop and validate an organoid-based functional assay for accurate DILI prediction.
  • To mimic the human liver microenvironment for enhanced hepatotoxicity assessment.

Main Methods:

  • Hepatic organoids (HOs) from human pluripotent stem cells (hPSCs) were co-cultured with hepatic stellate cells and macrophages.
  • A panel of 12 reference compounds with varying hepatotoxicity were used for validation.
  • Key indicators including oxidative stress markers (ROS, GSSH, catalase) and inflammatory cytokines (IL-1, IL-6, IL-10), along with liver enzymes (ALT, AST) and albumin (ALB), were measured.

Main Results:

  • Severe DILI-inducing drugs significantly elevated oxidative stress and inflammation markers compared to no/mild DILI groups.
  • Mild and severe DILI-inducing drugs significantly increased ALT and AST activities and decreased ALB levels.
  • The organoid model demonstrated a clear dose-dependent response correlating with DILI severity.

Conclusions:

  • The developed organoid-based functional endpoint method is effective for predicting DILI.
  • This model offers a promising tool for early-stage drug development, improving safety assessments.
  • The method accurately reflects the complex cellular and physiological responses involved in drug-induced liver injury.