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Related Concept Videos

Toxicokinetics: Overview01:21

Toxicokinetics: Overview

Studies that assess how a drug is absorbed, distributed, metabolized, and excreted (ADME) at toxic doses are termed toxicokinetics. Understanding toxicokinetics helps predict adverse drug reactions (ADRs) and manage toxicity in humans.Toxicokinetics differs from pharmacokinetics mainly in the dose levels studied, with toxicokinetics focusing on higher toxic doses. The kinetics at these levels can be non-linear due to altered physiological processes. Toxicodynamics examines the relationship...

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ToxMet: a web tool for toxicogenomic data analysis using genome-scale metabolic modeling.

Archana Hari1,2, Zhen Xu1,2, Zachary Smith1,2

  • 1Department of Defense Biotechnology High Performance Computing Software Applications Institute, Defense Health Agency Research & Development, Medical Research and Development Command, Fort Detrick, MD 21702, United States.

Toxicological Sciences : an Official Journal of the Society of Toxicology
|June 29, 2026
PubMed
Summary

ToxMet is a user-friendly web tool that integrates gene expression data with rat metabolic models to predict chemical toxicity mechanisms. It aids in discovering biomarkers and therapeutics by analyzing metabolic perturbations in tissues.

Keywords:
biomarker predictioncomputational toxicologygenome-scale metabolic modelingmetabolismweb application

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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

Area of Science:

  • Toxicology
  • Metabolomics
  • Bioinformatics

Background:

  • Chemical toxicity assessment relies on in vivo rat studies and gene expression analysis.
  • Genome-scale metabolic models (GSMs) offer systems-level insights but often require programming expertise.
  • Existing computational tools for integrating gene expression with GSMs have accessibility limitations for non-computational users.

Purpose of the Study:

  • To introduce ToxMet, an open-access web application for predicting chemical-induced metabolic perturbations in rat tissues.
  • To provide a user-friendly platform for integrating toxicogenomic data with a rat GSM (iRno v4.2).
  • To facilitate the discovery of toxicity mechanisms, biomarkers, and therapeutics.

Main Methods:

  • Developed ToxMet, a web application utilizing the latest rat GSM (iRno v4.2).
  • Integrated two validated algorithms, TIMBR and Pheflux, for predicting metabolic perturbations.
  • Visualized results using interactive tables, scatter plots, and network views.

Main Results:

  • ToxMet successfully predicted known toxicity mechanisms for gentamicin (kidney injury) and thioacetamide (liver injury) using public toxicogenomic data.
  • The tool provides tabular and graph-based network views for visualizing metabolic network data.
  • Results are presented as interactive and downloadable tables, scatter plots, and network visualizations.

Conclusions:

  • ToxMet demonstrates the ability to provide novel insights into the metabolic mechanisms of chemical-induced toxicity.
  • The web tool aids in the discovery of biomarkers and therapeutics by analyzing gene expression data.
  • ToxMet enhances accessibility to computational methods for toxicity mechanism inference.