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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...
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When toxic substances penetrate the human body, they disseminate to various tissues, undergoing metabolic changes. This process yields reactive metabolites that may covalently bind with specific target molecules, resulting in toxicity.
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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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Computer-assisted methods in chemical toxicity prediction.

C Gopi Mohan1, Tamanna Gandhi, Divita Garg

  • 1Centre for Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S.A.S. Nagar, Punjab-160 062, India. cmohan@niper.ac.in

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Summary

In silico predictive ADME/Tox screening aids drug discovery by predicting compound properties early. This computational approach reduces late-stage drug failures and associated costs.

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Area of Science:

  • Computational chemistry and drug discovery.
  • Pharmacology and toxicology.
  • Bioinformatics and cheminformatics.

Background:

  • In silico predictive ADME/Tox screening is crucial for early drug discovery.
  • Computational technologies enable rapid, high-throughput ADMET analysis.
  • Early screening minimizes costly late-stage drug failures due to poor ADME/Tox properties.

Purpose of the Study:

  • To review freely and commercially available software for toxicity predictions.
  • To guide scientists in selecting appropriate tools for in silico ADMET analysis.
  • To highlight the importance of accurate physico-chemical and toxicological property estimation.

Main Methods:

  • Review of existing literature and software databases.
  • Analysis of structure-activity relationships for toxicity prediction.
  • Categorization of computational tools based on availability and application.

Main Results:

  • Identification of various software solutions for in silico ADMET prediction.
  • Demonstration of the utility of computational methods in assessing drug-like characteristics.
  • Emphasis on the broad definition of drug toxic effects, including mutagenicity, carcinogenicity, and neurotoxicity.

Conclusions:

  • In silico ADMET screening is a vital component of modern drug discovery.
  • Accessible software tools empower researchers to perform early-stage toxicity assessments.
  • Accurate property estimation is fundamental for reliable toxicity predictions and successful drug development.