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Related Concept Videos

Toxicity Testing in Animals01:23

Toxicity Testing in Animals

Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...
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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Related Experiment Video

Updated: May 31, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
05:47

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

Democratizing Artificial Intelligence in Toxicology: Real-World Applications and Automated Computational Workflows.

Kamel Mansouri1, José Teófilo Moreira-Filho1, Ricardo S Tieghi1

  • 1National Toxicology Program Interagency Center for Evaluation of Alternative Toxicological Methods (NICEATM), Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, North Carolina 27711, United States.

Chemical Research in Toxicology
|May 29, 2026
PubMed
Summary

Democratizing computational toxicology with AI is crucial for advancing chemical safety. No-code/low-code tools enable broader access to artificial intelligence (AI) methods, accelerating research and regulatory use.

Failed At:

2026-06-19T13:40:43.533643+00:00

Related Experiment Videos

Last Updated: May 31, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
05:47

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019