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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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In Silico Models for Acute Systemic Toxicity.

Julien Burton1, Andrew P Worth2, Ivanka Tsakovska3

  • 1Systems Toxicology Unit and EURL ECVAM, Institute for Health and Consumer Protection, Joint Research Centre, European Commission, Ispra, Varese, Italy.

Methods in Molecular Biology (Clifton, N.J.)
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Summary
This summary is machine-generated.

This chapter reviews European Union regulatory needs for acute systemic toxicity data. It also explores available structure-based computational models and recent literature for toxicity assessment and future development.

Keywords:
Acute systemic toxicityIn silico modelOrgan-specific toxicityRegulation

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Area of Science:

  • Toxicology
  • Computational Chemistry
  • Regulatory Science

Background:

  • Regulatory requirements for acute systemic toxicity data in the European Union are complex.
  • Assessing acute systemic toxicity is crucial for chemical safety and regulatory compliance.
  • Structure-based computational models offer potential for efficient toxicity assessment.

Purpose of the Study:

  • To provide an overview of European Union regulatory requirements for acute systemic toxicity data.
  • To review existing structure-based computational models for acute systemic toxicity assessment.
  • To discuss recent literature models and future perspectives in the field.

Main Methods:

  • Literature review of regulatory guidelines for acute systemic toxicity.
  • Survey of available structure-based computational models in toxicology.
  • Analysis of recently published computational models for acute systemic toxicity.

Main Results:

  • The European Union has specific regulatory demands for acute systemic toxicity information.
  • Several structure-based computational models show potential utility in toxicity assessments.
  • Recent literature highlights advancements in predictive toxicology models.

Conclusions:

  • Understanding regulatory requirements is key for data generation.
  • Structure-based computational models are valuable tools for predicting acute systemic toxicity.
  • Continued development in computational toxicology is expected to enhance safety assessments.