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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...
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
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...
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

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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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Omics in mechanistic and predictive toxicology.

Seema Singh1, Naveen Kumar Singhal, Garima Srivastava

  • 1Indian Institute of Toxicology Research (Council of Scientific and Industrial Research), Lucknow-226 001, India.

Toxicology Mechanisms and Methods
|January 20, 2010
PubMed
Summary

Omics technologies help understand toxicity mechanisms and predict chemical risks. While India rapidly adopts these methods, their predictive power in toxicology needs further development.

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Area of Science:

  • Toxicology
  • Genomics
  • Proteomics
  • Metabolomics

Background:

  • High-throughput omics strategies are crucial for elucidating molecular toxicity mechanisms.
  • Omics technologies aid in predicting chemical toxicity and identifying at-risk individuals.
  • India is a rapidly growing adopter of omics technologies in research and application.

Purpose of the Study:

  • To review the current status of omics-based research in toxicology.
  • To explore future possibilities of omics technologies at the Indian Institute of Toxicology Research (IITR).
  • To discuss the application of omics in understanding toxicity and disease risk.

Main Methods:

  • Review of omics-driven approaches in toxicology.
  • Identification of differentially expressed genes and proteins.
  • Association studies on genetic polymorphisms and toxicant-induced diseases.

Main Results:

  • Omics have identified molecular fingerprints for disease risk and toxicity prediction.
  • Significant progress in understanding mechanistic toxicology through omics.
  • Limited predictive value of current omics findings in toxicology.

Conclusions:

  • Omics research holds immense potential for advancing mechanistic toxicology.
  • Further development is needed to enhance the predictive value of omics in toxicology.
  • The Indian Institute of Toxicology Research (IITR) is poised to contribute to future omics advancements.