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Toxicity Testing in Animals

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...

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Related Experiment Video

Updated: May 22, 2026

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

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Published on: August 28, 2019

Web tools for predictive toxicology model building.

Nina Jeliazkova¹

¹IdeaConsult Ltd., 4 A.Kanchev str., Sofia 1000, Bulgaria. jeliazkova.nina@gmail.com

Expert Opinion on Drug Metabolism & Toxicology

|May 15, 2012

Summary

Web tools for predictive toxicology model building are advancing, integrating cheminformatics and data analysis. Future tools will offer enhanced flexibility, scalability, and collaborative features for improved drug discovery and safety assessment.

Area of Science:

* Computational chemistry and cheminformatics
* Predictive toxicology and drug discovery

Background:

* Web tools in chemistry have over 15 years of history, evolving with internet technologies.
* Modern web platforms integrate data storage, cheminformatics, and data analysis.
* Ease of use and collaboration are key drivers, despite technical challenges.

Purpose of the Study:

* Review recently published web tools for predictive toxicology model building.
* Focus on chemical structure-based methods accessible via web platforms.
* Assess tools based on workflows, descriptor calculations, visualization, modeling, data management, and access.

Main Methods:

* Literature review of contemporary web-based predictive toxicology tools.
* Analysis of software platforms offering chemical structure-based modeling.

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* Evaluation of features including workflow support, descriptor calculations, visualization, and modeling algorithms.

Main Results:

* Identified web tools facilitate predictive toxicology model building.
* Assessed tools on criteria such as data management, sharing, GUI/programmatic access, and implementation.
* Highlighted the integration of cheminformatics and data analysis functionalities.

Conclusions:

* Web's success relies on decentralized, interoperable information access.
* Convergence of cheminformatics and bioinformatics presents data management challenges.
* Future web tools will prioritize flexibility, performance, scalability, interoperability, user-friendliness, and collaborative features.