Literature DB >> 7570659

Development of structure-activity relationship rules for predicting carcinogenic potential of chemicals.

Y T Woo1, D Y Lai, M F Argus, J C Arcos.   

Abstract

Since the inception of Section 5 (Premanufacturing/Premarketing Notification, PMN) of the Toxic Substances Control Act (TSCA), structure-activity relationship (SAR) analysis has been effectively used by U.S. Environmental Protection Agency's (EPA) Structure Activity Team (SAT) in the assessment of potential carcinogenic hazard of new chemicals for which test data are not available. To capture, systematize and codify the Agency's predictive expertise in order to make it more widely available to assessors outside the TSCA program, a cooperative project was initiated to develop a knowledge rule-based expert system to mimic the thinking and reasoning of the SAT. In this communication, we describe the overall structure of this expert system, discuss the scientific bases and principles of SAR analysis of chemical carcinogens used in the development of SAR knowledge rules, and delineate the major factors/rules useful for assessing the carcinogenic potential of fibers, polymers, metals/metalloids and several major classes of organic chemicals. An integrative approach using available short-term predictive tests and non-cancer toxicological data to supplement SAR analysis has also been described.

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Year:  1995        PMID: 7570659     DOI: 10.1016/0378-4274(95)03373-s

Source DB:  PubMed          Journal:  Toxicol Lett        ISSN: 0378-4274            Impact factor:   4.372


  6 in total

1.  Multicomponent criteria for predicting carcinogenicity: dataset of 30 NTP chemicals.

Authors:  J Huff; E Weisburger; V A Fung
Journal:  Environ Health Perspect       Date:  1996-10       Impact factor: 9.031

Review 2.  In silico prediction of drug toxicity.

Authors:  John C Dearden
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

3.  Weighted feature significance: a simple, interpretable model of compound toxicity based on the statistical enrichment of structural features.

Authors:  Ruili Huang; Noel Southall; Menghang Xia; Ming-Hsuang Cho; Ajit Jadhav; Dac-Trung Nguyen; James Inglese; Raymond R Tice; Christopher P Austin
Journal:  Toxicol Sci       Date:  2009-10-04       Impact factor: 4.849

Review 4.  Use of mechanism-based structure-activity relationships analysis in carcinogenic potential ranking for drinking water disinfection by-products.

Authors:  Yin-Tak Woo; David Lai; Jennifer L McLain; Mary Ko Manibusan; Vicki Dellarco
Journal:  Environ Health Perspect       Date:  2002-02       Impact factor: 9.031

Review 5.  Use of QSARs in international decision-making frameworks to predict health effects of chemical substances.

Authors:  Mark T D Cronin; Joanna S Jaworska; John D Walker; Michael H I Comber; Christopher D Watts; Andrew P Worth
Journal:  Environ Health Perspect       Date:  2003-08       Impact factor: 9.031

6.  A Predictive Model for Toxicity Effects Assessment of Biotransformed Hepatic Drugs Using Iterative Sampling Method.

Authors:  Alaa Tharwat; Yasmine S Moemen; Aboul Ella Hassanien
Journal:  Sci Rep       Date:  2016-12-09       Impact factor: 4.379

  6 in total

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