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 Experiment Videos

The computational prediction of toxicity.

M D Barratt1, R A Rodford

  • 1Marlin Consultancy, 10 Beeby Way, Carlton, Bedford MK43 7LW, UK. martin.d.barratt@btinternet.com

Current Opinion in Chemical Biology
|July 27, 2001
PubMed
Summary

Predictive toxicology from chemical structures needs better data and a multi-disciplinary approach. Current efforts may focus too much on methods over essential data creation for chemical toxicity endpoints.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

The validation of computational prediction techniques.

Alternatives to laboratory animals : ATLA·2015
Same author

The Integrated Use of Alternative Methods in Toxicological Risk Evaluation - ECVAM Integrated Testing Strategies Task Force Report 1.

Alternatives to laboratory animals : ATLA·2014
Same author

Photochemical binding of photoallergens to human serum albumin: A simple in vitro method for screening potential photoallergens.

Toxicology in vitro : an international journal published in association with BIBRA·2010
Same author

Skin sensitization structure-activity relationships for phenyl benzoates.

Toxicology in vitro : an international journal published in association with BIBRA·2010
Same author

Development of an expert system rulebase for identifying contact allergens.

Toxicology in vitro : an international journal published in association with BIBRA·2010
Same author

A Quantitative Structure-Activity Relationship (QSAR) for prediction of alpha(2mu)-globulin nephropathy.

Toxicology in vitro : an international journal published in association with BIBRA·2010

Area of Science:

  • Toxicology
  • Computational Chemistry
  • Data Science

Background:

  • Predictive toxicology aims to forecast chemical toxicity based on molecular structure.
  • Advancements in computational methods offer potential for toxicity prediction.
  • Challenges persist due to data quality and scope limitations.

Purpose of the Study:

  • To review recent progress in predicting chemical toxicity from structure.
  • To highlight key challenges and requirements for advancing predictive toxicology.
  • To assess the balance between methodological development and data generation.

Main Methods:

  • Literature review of recent developments in predictive toxicology.
  • Analysis of common problems and necessary approaches in the field.
  • Evaluation of the impact of data availability on progress.

Main Results:

  • Progress in predictive toxicology is hindered by a lack of high-quality toxicological data.
  • A multi-disciplinary approach and focus on mechanisms of action are crucial.
  • Overemphasis on statistical methods may detract from essential data set creation.

Conclusions:

  • Future advancements require addressing data sparseness and focusing on under-investigated toxicological endpoints and chemical classes.
  • Integrating mechanistic understanding and diverse expertise is vital for robust toxicity predictions.
  • Strategic data generation is as critical as methodological innovation in predictive toxicology.

Related Experiment Videos