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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...
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: 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...
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...
Toxic Reactions: Overview01:26

Toxic Reactions: Overview

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.
Toxicity falls into two primary categories: local and systemic.
Local toxicity appears at the exposure site, such as protein denaturation caused by caustic substances.
In contrast, systemic toxicity requires the toxic agent's absorption and distribution,...

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Related Experiment Video

Updated: Jun 19, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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Computational toxicology--a tool for early safety evaluation.

Cédric Merlot1

  • 1Genyotex SA, Chemin des Aulx 14, 1228 Plan les Ouates, Geneva, Switzerland. cedric.merlot@genkyotex.com

Drug Discovery Today
|October 20, 2009
PubMed
Summary

Computational toxicology aids drug discovery by predicting safety issues early. Focusing on simpler, mechanism-based predictions improves accuracy and reduces drug candidate failures.

Area of Science:

  • Pharmacology
  • Toxicology
  • Drug Discovery

Background:

  • Safety issues are the primary reason for drug candidate failure, surpassing pharmacokinetic problems seen in the 1990s.
  • Integrating predictive toxicology early in drug discovery is crucial for mitigating safety concerns.

Purpose of the Study:

  • To review recent advancements in computational toxicology for predicting drug safety.
  • To highlight the shift from direct toxic endpoint modeling to simpler, mechanism-based predictions.

Main Methods:

  • Review of recent developments in computational toxicology.
  • Analysis of trends in predictive modeling for drug safety.

Main Results:

  • Direct modeling of toxic endpoints has faced challenges in acceptance and effectiveness.

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Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation
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  • A current trend favors simpler, mechanism-oriented predictions.

    • Conclusions:

    • Computational toxicology, when applied early with a balanced approach (in vivo, in vitro, computational), can reduce drug candidate attrition due to safety issues.
    • Simpler, mechanism-based computational predictions, followed by experimental validation, represent a promising direction for improving drug safety assessment.