Literature DB >> 24206190

Framework for identifying chemicals with structural features associated with the potential to act as developmental or reproductive toxicants.

Shengde Wu1, Joan Fisher, Jorge Naciff, Michael Laufersweiler, Cathy Lester, George Daston, Karen Blackburn.   

Abstract

Developmental and reproductive toxicity (DART) end points are important hazard end points that need to be addressed in the risk assessment of chemicals to determine whether or not they are the critical effects in the overall risk assessment. These hazard end points are difficult to predict using current in silico tools because of the diversity of mechanisms of action that elicit DART effects and the potential for narrow windows of vulnerability. DART end points have been projected to consume the majority of animals used for compliance with REACH; thus, additional nonanimal predictive tools are urgently needed. This article presents an empirically based decision tree for determining whether or not a chemical has receptor-binding properties and structural features that are consistent with chemical structures known to have toxicity for DART end points. The decision tree is based on a detailed review of 716 chemicals (664 positive, 16 negative, and 36 with insufficient data) that have DART end-point data and are grouped into defined receptor binding and chemical domains. When tested against a group of chemicals not included in the training set, the decision tree is shown to identify a high percentage of chemicals with known DART effects. It is proposed that this decision tree could be used both as a component of a screening system to identify chemicals of potential concern and as a component of weight-of-evidence decisions based on structure-activity relationships (SAR) to fill data gaps without generating additional test data. In addition, the chemical groupings generated could be used as a starting point for the development of hypotheses for in vitro testing to elucidate mode of action and ultimately in the development of refined SAR principles for DART that incorporate mode of action (adverse outcome pathways).

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Year:  2013        PMID: 24206190     DOI: 10.1021/tx400226u

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  25 in total

Review 1.  Applying evolutionary genetics to developmental toxicology and risk assessment.

Authors:  Maxwell C K Leung; Andrew C Procter; Jared V Goldstone; Jonathan Foox; Robert DeSalle; Carolyn J Mattingly; Mark E Siddall; Alicia R Timme-Laragy
Journal:  Reprod Toxicol       Date:  2017-03-04       Impact factor: 3.143

2.  FutureTox II: in vitro data and in silico models for predictive toxicology.

Authors:  Thomas B Knudsen; Douglas A Keller; Miriam Sander; Edward W Carney; Nancy G Doerrer; David L Eaton; Suzanne Compton Fitzpatrick; Kenneth L Hastings; Donna L Mendrick; Raymond R Tice; Paul B Watkins; Maurice Whelan
Journal:  Toxicol Sci       Date:  2015-02       Impact factor: 4.849

3.  Predicting the future: opportunities and challenges for the chemical industry to apply 21st-century toxicity testing.

Authors:  Raja S Settivari; Nicholas Ball; Lynea Murphy; Reza Rasoulpour; Darrell R Boverhof; Edward W Carney
Journal:  J Am Assoc Lab Anim Sci       Date:  2015-03       Impact factor: 1.232

Review 4.  The Impact of Novel Assessment Methodologies in Toxicology on Green Chemistry and Chemical Alternatives.

Authors:  Ivan Rusyn; Nigel Greene
Journal:  Toxicol Sci       Date:  2018-02-01       Impact factor: 4.849

5.  Programming microphysiological systems for children's health protection.

Authors:  T B Knudsen; B Klieforth; W Slikker
Journal:  Exp Biol Med (Maywood)       Date:  2017-06-28

6.  Mitochondria as a target of organophosphate and carbamate pesticides: Revisiting common mechanisms of action with new approach methodologies.

Authors:  Maxwell C K Leung; Joel N Meyer
Journal:  Reprod Toxicol       Date:  2019-07-14       Impact factor: 3.143

7.  Practical application of the interim internal threshold of toxicological concern (iTTC): a case study based on clinical data.

Authors:  Abdulkarim Najjar; Corie A Ellison; Sebastien Gregoire; Nicola J Hewitt
Journal:  Arch Toxicol       Date:  2022-09-23       Impact factor: 6.168

8.  Leveraging complementary computational models for prioritizing chemicals of developmental and reproductive toxicity concern: an example of food contact materials.

Authors:  Chun-Wei Tung; Hsien-Jen Cheng; Chia-Chi Wang; Shan-Shan Wang; Pinpin Lin
Journal:  Arch Toxicol       Date:  2020-01-02       Impact factor: 5.153

Review 9.  FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children.

Authors:  Thomas B Knudsen; Suzanne Compton Fitzpatrick; K Nadira De Abrew; Linda S Birnbaum; Anne Chappelle; George P Daston; Dana C Dolinoy; Alison Elder; Susan Euling; Elaine M Faustman; Kristi Pullen Fedinick; Jill A Franzosa; Derik E Haggard; Laurie Haws; Nicole C Kleinstreuer; Germaine M Buck Louis; Donna L Mendrick; Ruthann Rudel; Katerine S Saili; Thaddeus T Schug; Robyn L Tanguay; Alexandra E Turley; Barbara A Wetmore; Kimberly W White; Todd J Zurlinden
Journal:  Toxicol Sci       Date:  2021-04-12       Impact factor: 4.849

10.  Characterizing cleft palate toxicants using ToxCast data, chemical structure, and the biomedical literature.

Authors:  Nancy C Baker; Nisha S Sipes; Jill Franzosa; David G Belair; Barbara D Abbott; Richard S Judson; Thomas B Knudsen
Journal:  Birth Defects Res       Date:  2019-08-30       Impact factor: 2.661

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