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Toxicokinetics: Overview

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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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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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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...

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Assessment of Chemical Toxicity in Adult Drosophila Melanogaster

Assessment of Chemical Toxicity in Adult Drosophila Melanogaster

Published on: March 24, 2023

Toxicology ontology perspectives.

Barry Hardy¹, Gordana Apic, Philip Carthew

¹Douglas Connect and OpenTox, Zeiningen, Switzerland. Barry.Hardy@douglasconnect.com

|May 8, 2012

Summary

This summary is machine-generated.

Developing standardized, computable toxicology ontologies is crucial for advancing predictive toxicology research. Current initiatives show promise, but international collaboration is needed for a unified framework.

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Area of Science:

Toxicology
Bioinformatics
Computational Biology

Background:

Predictive toxicology relies on computable, standardized vocabularies and ontologies.
These are essential for in silico, in vitro, and in vivo toxicology methods, analysis, and reporting.

Purpose of the Study:

To review current ontology developments and their applications in predictive toxicology.
To identify existing resources and neighboring field developments that can form an ontological framework.
To highlight the need for international coordination in developing a unified toxicology ontology.

Main Methods:

Review of ontology developments and initiatives (OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, Bioclipse).
Assessment of ontologies from biological, chemical, and biomedical fields.
Evaluation of semantic web frameworks and interoperability examples (OpenTox, Bioclipse).

Main Results:

A significant set of resources exists to foundation an ontological framework for mechanistic toxicology.
Ontologies like ToxWiz are applicable to toxicology investigations.
OpenTox provides a semantic web framework, and Bioclipse demonstrates interoperability benefits.

Conclusions:

Existing resources provide a foundation for predictive toxicology ontologies.
Interoperability is achievable through semantic web technologies and ontologies.
Increased international coordination is essential for a unified, standardized, and open toxicology ontology framework.