Literature DB >> 17365963

The role of the European Chemicals Bureau in promoting the regulatory use of (Q)SAR methods.

A P Worth1, A Bassan, J De Bruijn, A Gallegos Saliner, T Netzeva, G Patlewicz, M Pavan, I Tsakovska, S Eisenreich.   

Abstract

Under the proposed REACH (Registration, Evaluation and Authorisation of CHemicals) legislation, (Q)SAR models and grouping methods (chemical categories and read across approaches) are expected to play a significant role in prioritising industrial chemicals for further assessment, and for filling information gaps for the purposes of classification and labelling, risk assessment and the assessment of persistent, bioaccumulative and toxic (PBT) chemicals. The European Chemicals Bureau (ECB), which is part of the European Commission's Joint Research Centre (JRC), has a well-established role in providing independent scientific and technical advice to European policy makers. The ECB also promotes consensus and capacity building on scientific and technical matters among stakeholders in the Member State authorities and industry. To promote the availability and use of (Q)SARs and related estimation methods, the ECB is carrying out a range of activities, including applied research in computational toxicology, the assessment of (Q)SAR models and methods, the development of technical guidance documents and computational tools, and the organisation of training courses. This article provides an overview of ECB activities on computational toxicology, which are intended to promote the development, validation, acceptance and use of (Q)SARs and related estimation methods, both at the European and international levels.

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Year:  2007        PMID: 17365963     DOI: 10.1080/10629360601054255

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  19 in total

1.  QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes.

Authors:  Nikita Basant; Shikha Gupta
Journal:  Environ Sci Pollut Res Int       Date:  2017-04-24       Impact factor: 4.223

Review 2.  Big-data and machine learning to revamp computational toxicology and its use in risk assessment.

Authors:  Thomas Luechtefeld; Craig Rowlands; Thomas Hartung
Journal:  Toxicol Res (Camb)       Date:  2018-05-01       Impact factor: 3.524

3.  Integration of in silico methods and computational systems biology to explore endocrine-disrupting chemical binding with nuclear hormone receptors.

Authors:  P Ruiz; A Sack; M Wampole; S Bobst; M Vracko
Journal:  Chemosphere       Date:  2017-03-09       Impact factor: 7.086

4.  In silico prediction of the developmental toxicity of diverse organic chemicals in rodents for regulatory purposes.

Authors:  Nikita Basant; Shikha Gupta; Kunwar P Singh
Journal:  Toxicol Res (Camb)       Date:  2016-02-29       Impact factor: 3.524

5.  Modeling the toxicity of chemical pesticides in multiple test species using local and global QSTR approaches.

Authors:  Nikita Basant; Shikha Gupta; Kunwar P Singh
Journal:  Toxicol Res (Camb)       Date:  2015-12-10       Impact factor: 3.524

6.  3D QSAR studies of hydroxylated polychlorinated biphenyls as potential xenoestrogens.

Authors:  Patricia Ruiz; Kundan Ingale; John S Wheeler; Moiz Mumtaz
Journal:  Chemosphere       Date:  2015-11-19       Impact factor: 7.086

7.  Integrated testing strategies for safety assessments.

Authors:  Thomas Hartung; Tom Luechtefeld; Alexandra Maertens; Andre Kleensang
Journal:  ALTEX       Date:  2013       Impact factor: 6.043

8.  Structure-activity relationship analysis of N-benzoylpyrazoles for elastase inhibitory activity: a simplified approach using atom pair descriptors.

Authors:  Andrei I Khlebnikov; Igor A Schepetkin; Mark T Quinn
Journal:  Bioorg Med Chem       Date:  2008-01-15       Impact factor: 3.641

9.  Transport and dynamics of toxic pollutants in the natural environment and their effect on human health: research gaps and challenge.

Authors:  Andrew Hursthouse; George Kowalczyk
Journal:  Environ Geochem Health       Date:  2008-11-11       Impact factor: 4.609

Review 10.  QSPR studies on aqueous solubilities of drug-like compounds.

Authors:  Pablo R Duchowicz; Eduardo A Castro
Journal:  Int J Mol Sci       Date:  2009-06-03       Impact factor: 6.208

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