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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...
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...
Drug Toxicity: Dose-Dependent Reactions01:24

Drug Toxicity: Dose-Dependent Reactions

Drug toxicities can be stratified into pharmacological, pathological, or genotoxic based on their mechanisms. The incidence and severity of these toxicities generally increase with the drug's concentration in the body and exposure time.Pharmacological toxicity is evident when the therapeutic effects of drugs overshoot into adverse reactions in a predictable, dose-dependent manner. Central nervous system (CNS) depression from barbiturates is a classic example, with effects escalating from...
Mutagenicity and Carcinogenicity01:25

Mutagenicity and Carcinogenicity

Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
Drug Toxicity: Overview01:00

Drug Toxicity: Overview

Drug toxicity quantifies the harm a compound causes to an organism, varying by dose and potentially impacting whole systems or specific organs like the liver. Toxic reactions may arise from venomous insect or spider bites, with effects ranging from mild symptoms to severe outcomes such as brain damage or death. Common forms of acute poisoning include ethanol intoxication and overdose of pain or fever medications, with substances like GHB and heroin being particularly lethal at doses close to...
Drug toxicity: Drug–Drug Interaction01:30

Drug toxicity: Drug–Drug Interaction

Drug–drug interactions can precipitate toxicity through multiple mechanisms. Absorption interactions alter how drugs enter the body, exemplified when ranitidine increases the absorption of basic drugs, while cholestyramine decreases the levels of propranolol. Protein binding interactions occur when drugs share the same binding sites on plasma proteins. Drugs like aspirin and warfarin, when bound in excess, can lead to increased free drug concentrations, enhancing the potential for...

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Related Experiment Video

Updated: Jul 6, 2026

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

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Computational toxicology in drug development.

Wolfgang Muster1, Alexander Breidenbach, Holger Fischer

  • 1F. Hoffmann-La Roche Ltd., Non-Clinical Drug Safety, Basel CH-4070, Switzerland. wolfgang.muster@roche.com

Drug Discovery Today
|April 15, 2008
PubMed
Summary

Computational tools predict drug toxicity, reducing development costs and improving patient safety. Future efforts focus on predicting human disease-related toxicity for enhanced drug discovery.

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Area of Science:

  • Pharmacology and Toxicology
  • Computational Chemistry
  • Drug Discovery and Development

Background:

  • Computational tools are crucial for predicting compound toxicity in drug discovery.
  • These in silico methods can significantly reduce drug development costs by identifying adverse drug reactions early.
  • Existing systems are successfully used in the pharmaceutical industry.

Purpose of the Study:

  • To highlight the impact of computational toxicity prediction tools on drug discovery.
  • To discuss the role of in silico techniques in reducing drug development costs.
  • To outline future directions for improving toxicity prediction models for human diseases.

Main Methods:

  • Utilizing knowledge-based expert systems.
  • Employing quantitative structure-activity relationship (QSAR) tools.
  • Applying various modeling approaches for toxicity prediction.

Main Results:

  • In silico methods have demonstrated success in predicting early safety-relevant endpoints like genotoxicity.
  • Commercial and proprietary systems are effectively applied in the pharmaceutical sector.
  • Optimization for early endpoints has been achieved.

Conclusions:

  • Computational toxicity prediction is vital for efficient drug discovery and development.
  • In silico tools offer significant cost-saving potential by predicting adverse drug reactions.
  • Future research will focus on enhancing model relevance for predicting human disease-related toxicity.