Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Drug Toxicity: Risk factors01:24

Drug Toxicity: Risk factors

38
Adverse Drug Reactions (ADRs) are potential complications that arise during pharmacotherapy, influenced by multiple risk factors. Age plays a significant role; both neonates and the elderly are at heightened risk due to their respective immature and diminished metabolic and elimination processes. Gender also impacts ADRs, with females experiencing a 1.5 to 1.7-fold greater risk than males, which may be linked to pharmacokinetic, pharmacodynamic, and hormonal differences. Notably, neonates, the...
38
Toxicity Testing in Animals01:23

Toxicity Testing in Animals

40
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...
40
Drug Toxicity: Overview01:00

Drug Toxicity: Overview

53
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...
53
Drug Toxicity: Dose-Dependent Reactions01:24

Drug Toxicity: Dose-Dependent Reactions

35
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...
35
Toxicokinetics: Overview01:21

Toxicokinetics: Overview

41
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...
41
Drug toxicity: Idiosyncratic Reactions01:16

Drug toxicity: Idiosyncratic Reactions

45
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...
45

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Nonlinear combinatorial analysis of blood transcriptomes identifies PRKAR1A as a regulator of TDP-43 pathophysiology in amyotrophic lateral sclerosis.

Biology methods & protocols·2026
Same author

An interpretable combinatorial data-mining framework for predicting new-onset hypertension in the general population.

Hypertension research : official journal of the Japanese Society of Hypertension·2026
Same author

Data-driven simulator of multi-animal behavior with unknown dynamics via reinforcement learning.

iScience·2026
Same author

An Operator Analysis on Stochastic Differential Equation (SDE)-Based Diffusion Generative Models.

Entropy (Basel, Switzerland)·2026
Same author

Optimization of memory neurofeedback system utilizing intracranial electroencephalogram of the hippocampus.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2025
Same author

Relationship Between the Incidence of Metabolic Syndrome and Breast Cancer.

Cardiovascular drugs and therapy·2025

Related Experiment Video

Updated: Feb 22, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
09:01

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

7.7K

Toxicity prediction from toxicogenomic data based on class association rule mining.

Keisuke Nagata1, Takashi Washio2, Yoshinobu Kawahara2

  • 1Drug Safety Research Laboratories, Astellas Pharma Inc., 2-1-6 Kashima, Yodogawa-ku, Osaka 532-8514, Japan.

Toxicology Reports
|October 1, 2017
PubMed
Summary
This summary is machine-generated.

Classification Based on Association (CBA) algorithm improves toxicogenomic data analysis. CBA offers superior accuracy, sensitivity, and specificity compared to linear discriminant analysis (LDA) for knowledge discovery.

Keywords:
CBAClass association rule miningMicroarrayToxicogenomics

More Related Videos

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

3.3K
Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation
17:28

Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation

Published on: June 17, 2015

13.2K

Related Experiment Videos

Last Updated: Feb 22, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
09:01

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

7.7K
Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

3.3K
Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation
17:28

Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation

Published on: June 17, 2015

13.2K

Area of Science:

  • Bioinformatics
  • Toxicogenomics
  • Data Mining

Background:

  • High-throughput biological technologies generate vast datasets.
  • Extracting accurate and interpretable knowledge from complex biological data remains challenging.

Purpose of the Study:

  • To evaluate the Classification Based on Association (CBA) algorithm for analyzing toxicogenomic data.
  • To compare the performance and interpretability of CBA against linear discriminant analysis (LDA).

Main Methods:

  • Applied the CBA algorithm, a class association rule mining technique.
  • Utilized the TG-GATEs database containing toxicogenomic and toxicological data for over 150 compounds.
  • Compared CBA-generated classifiers with those from LDA.

Main Results:

  • CBA demonstrated superior predictive performance over LDA.
  • CBA achieved higher accuracy (83% vs. 75%), sensitivity (82% vs. 72%), and specificity (85% vs. 75%).
  • CBA also offered enhanced interpretability of the results.

Conclusions:

  • The CBA algorithm is a powerful tool for deriving accurate and understandable knowledge from toxicogenomic data.
  • CBA outperforms LDA in both predictive accuracy and interpretability for this type of analysis.