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Literature DB >> 18569330

Directions in QSAR modeling for regulatory uses in OECD member countries, EU and in Russia.

Natalja Fjodorova¹, Marjana Novich, Marjan Vrachko, Vjacheslav Smirnov, Nina Kharchevnikova, Zoya Zholdakova, Sergei Novikov, Natalja Skvortsova, Dmitrii Filimonov, Vladimir Poroikov, Emilio Benfenati.

Abstract

The aim of this article is to show the main aspects of quantitative structure activity relationship (QSAR) modeling for regulatory purposes. We try to answer the question; what makes QSAR models suitable for regulatory uses. The article focuses on directions in QSAR modeling in European Union (EU) and Russia. Difficulties in validation models have been discussed.

Mesh：

Substances：
Hazardous Substances

Year: 2008 PMID： 18569330 DOI： 10.1080/10590500802135578

Source DB: PubMed Journal: J Environ Sci Health C Environ Carcinog Ecotoxicol Rev ISSN： 1059-0501 Impact factor: 3.781

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Cited

8 in total

1. Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses.

Authors: Natalja Fjodorova; Marjan Vračko; Marjan Tušar; Aneta Jezierska; Marjana Novič; Ralph Kühne; Gerrit Schüürmann
Journal: Mol Divers Date: 2009-08-15 Impact factor: 2.943

2. Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests.

Authors: Rudra Narayan Das; Tânia E Sintra; João A P Coutinho; Sónia P M Ventura; Kunal Roy; Paul L A Popelier
Journal: Toxicol Res (Camb) Date: 2016-07-07 Impact factor: 3.524

3. 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

4. In Silico Models for Ecotoxicity of Pharmaceuticals.

Authors: Kunal Roy; Supratik Kar
Journal: Methods Mol Biol Date: 2016

5. Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

Authors: Lisa Truong; Gladys Ouedraogo; LyLy Pham; Jacques Clouzeau; Sophie Loisel-Joubert; Delphine Blanchet; Hicham Noçairi; Woodrow Setzer; Richard Judson; Chris Grulke; Kamel Mansouri; Matthew Martin
Journal: Arch Toxicol Date: 2017-10-27 Impact factor: 5.153

Directions in QSAR modeling for regulatory uses in OECD member countries, EU and in Russia.

1. Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses.

2. Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests.

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

4. In Silico Models for Ecotoxicity of Pharmaceuticals.

5. Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

6. Computational approaches to chemical hazard assessment.

7. Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

Review 8. Impact of Pharmaceuticals on the Environment: Risk Assessment Using QSAR Modeling Approach.