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Drug Toxicity: Dose-Dependent Reactions01:24

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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...
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Idiosyncratic drug reactions represent abnormal chemical responses that vary significantly among individuals, ranging from extreme sensitivity to low doses to insensitivity to high doses. These reactions often occur due to the drug's covalent binding with serum proteins, forming a foreign hapten that triggers an immunotoxicological response. The variability in drug reactions has a strong pharmacogenetic foundation, with genetic differences crucial in how individuals metabolize drugs. For...
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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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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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Drug-Path: a database for drug-induced pathways.

Hui Zeng1, Chengxiang Qiu2, Qinghua Cui2

  • 1Department of Cardiology, Peking University Third Hospital, Beijing 100191, China and.

Database : the Journal of Biological Databases and Curation
|July 2, 2015
PubMed
Summary
This summary is machine-generated.

Drug-Path is a new database that maps how drugs affect biological pathways using gene expression data. This resource aids in understanding drug mechanisms and finding new uses for existing drugs.

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Area of Science:

  • Pharmacogenomics
  • Systems Biology
  • Bioinformatics

Background:

  • Existing drug databases primarily focus on drug action or metabolism pathways.
  • High-throughput technologies generate extensive drug-induced gene expression profiles.
  • These profiles reveal distinct patterns indicating drug-specific pathway modulation.

Purpose of the Study:

  • To develop Drug-Path, a comprehensive database of drug-induced pathways.
  • To facilitate the study of drug mechanisms and drug repurposing.
  • To provide accessible tools for exploring drug-pathway interactions.

Main Methods:

  • Utilized KEGG pathway enrichment analysis on drug-induced gene expression data.
  • Integrated datasets from the Connectivity Map for gene expression profiles.
  • Organized data using SQLite and developed a web interface with Django.

Main Results:

  • Created Drug-Path, a database detailing drug-induced pathways.
  • Implemented user-friendly interfaces for data retrieval, visualization, and download.
  • Highlighted drug-deregulated genes within the pathway visualizations.

Conclusions:

  • Drug-Path provides a valuable resource for understanding drug-induced biological pathway alterations.
  • The database supports research into drug mechanisms and facilitates drug repurposing efforts.
  • Accessible visualization and data retrieval enhance its utility for the scientific community.