Literature DB >> 31078681

Exploring current read-across applications and needs among selected U.S. Federal Agencies.

Grace Patlewicz1, Lucina E Lizarraga2, Diego Rua3, David G Allen4, Amber B Daniel4, Suzanne C Fitzpatrick5, Natàlia Garcia-Reyero6, John Gordon7, Pertti Hakkinen8, Angela S Howard4, Agnes Karmaus4, Joanna Matheson7, Moiz Mumtaz9, Andrea-Nicole Richarz10, Patricia Ruiz9, Louis Scarano11, Takashi Yamada12, Nicole Kleinstreuer13.   

Abstract

Read-across is a well-established data gap-filling technique applied for regulatory purposes. In US Environmental Protection Agency's New Chemicals Program under TSCA, read-across has been used extensively for decades, however the extent of application and acceptance of read-across among U.S. federal agencies is less clear. In an effort to build read-across capacity, raise awareness of the state of the science, and work towards a harmonization of read-across approaches across U.S. agencies, a new read-across workgroup was established under the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). This is one of several ad hoc groups ICCVAM has convened to implement the ICCVAM Strategic Roadmap. In this article, we outline the charge and scope of the workgroup and summarize the current applications, tools used, and needs of the agencies represented on the workgroup for read-across. Of the agencies surveyed, the Environmental Protection Agency had the greatest experience in using read-across whereas other agencies indicated that they would benefit from gaining a perspective of the landscape of the tools and available guidance. Two practical case studies are also described to illustrate how the read-across approaches applied by two agencies vary on account of decision context. Published by Elsevier Inc.

Entities:  

Keywords:  Analog approach; Category approach; ICCVAM; New approach methodology (NAM); Read-across; Regulatory purpose

Mesh:

Year:  2019        PMID: 31078681      PMCID: PMC6814248          DOI: 10.1016/j.yrtph.2019.05.011

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  40 in total

1.  New publicly available chemical query language, CSRML, to support chemotype representations for application to data mining and modeling.

Authors:  Chihae Yang; Aleksey Tarkhov; Jörg Marusczyk; Bruno Bienfait; Johann Gasteiger; Thomas Kleinoeder; Tomasz Magdziarz; Oliver Sacher; Christof H Schwab; Johannes Schwoebel; Lothar Terfloth; Kirk Arvidson; Ann Richard; Andrew Worth; James Rathman
Journal:  J Chem Inf Model       Date:  2015-02-19       Impact factor: 4.956

2.  Use of category approaches, read-across and (Q)SAR: general considerations.

Authors:  Grace Patlewicz; Nicholas Ball; Ewan D Booth; Etje Hulzebos; Elton Zvinavashe; Christa Hennes
Journal:  Regul Toxicol Pharmacol       Date:  2013-06-11       Impact factor: 3.271

3.  A strategy for structuring and reporting a read-across prediction of toxicity.

Authors:  T W Schultz; P Amcoff; E Berggren; F Gautier; M Klaric; D J Knight; C Mahony; M Schwarz; A White; M T D Cronin
Journal:  Regul Toxicol Pharmacol       Date:  2015-05-21       Impact factor: 3.271

4.  CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data.

Authors:  Daniel P Russo; Marlene T Kim; Wenyi Wang; Daniel Pinolini; Sunil Shende; Judy Strickland; Thomas Hartung; Hao Zhu
Journal:  Bioinformatics       Date:  2017-02-01       Impact factor: 6.937

5.  Results of a round-robin exercise on read-across.

Authors:  E Benfenati; M Belli; T Borges; E Casimiro; J Cester; A Fernandez; G Gini; M Honma; M Kinzl; R Knauf; A Manganaro; E Mombelli; M I Petoumenou; M Paparella; P Paris; G Raitano
Journal:  SAR QSAR Environ Res       Date:  2016-05-11       Impact factor: 3.000

6.  QSAR Toolbox - workflow and major functionalities.

Authors:  S D Dimitrov; R Diderich; T Sobanski; T S Pavlov; G V Chankov; A S Chapkanov; Y H Karakolev; S G Temelkov; R A Vasilev; K D Gerova; C D Kuseva; N D Todorova; A M Mehmed; M Rasenberg; O G Mekenyan
Journal:  SAR QSAR Environ Res       Date:  2016-02-19       Impact factor: 3.000

7.  Effects of aldehyde dehydrogenase-2 genetic polymorphisms on metabolism of structurally different aldehydes in human liver.

Authors:  Rui-Sheng Wang; Tamie Nakajima; Toshihiro Kawamoto; Takeshi Honma
Journal:  Drug Metab Dispos       Date:  2002-01       Impact factor: 3.922

8.  In silico toxicology protocols.

Authors:  Glenn J Myatt; Ernst Ahlberg; Yumi Akahori; David Allen; Alexander Amberg; Lennart T Anger; Aynur Aptula; Scott Auerbach; Lisa Beilke; Phillip Bellion; Romualdo Benigni; Joel Bercu; Ewan D Booth; Dave Bower; Alessandro Brigo; Natalie Burden; Zoryana Cammerer; Mark T D Cronin; Kevin P Cross; Laura Custer; Magdalena Dettwiler; Krista Dobo; Kevin A Ford; Marie C Fortin; Samantha E Gad-McDonald; Nichola Gellatly; Véronique Gervais; Kyle P Glover; Susanne Glowienke; Jacky Van Gompel; Steve Gutsell; Barry Hardy; James S Harvey; Jedd Hillegass; Masamitsu Honma; Jui-Hua Hsieh; Chia-Wen Hsu; Kathy Hughes; Candice Johnson; Robert Jolly; David Jones; Ray Kemper; Michelle O Kenyon; Marlene T Kim; Naomi L Kruhlak; Sunil A Kulkarni; Klaus Kümmerer; Penny Leavitt; Bernhard Majer; Scott Masten; Scott Miller; Janet Moser; Moiz Mumtaz; Wolfgang Muster; Louise Neilson; Tudor I Oprea; Grace Patlewicz; Alexandre Paulino; Elena Lo Piparo; Mark Powley; Donald P Quigley; M Vijayaraj Reddy; Andrea-Nicole Richarz; Patricia Ruiz; Benoit Schilter; Rositsa Serafimova; Wendy Simpson; Lidiya Stavitskaya; Reinhard Stidl; Diana Suarez-Rodriguez; David T Szabo; Andrew Teasdale; Alejandra Trejo-Martin; Jean-Pierre Valentin; Anna Vuorinen; Brian A Wall; Pete Watts; Angela T White; Joerg Wichard; Kristine L Witt; Adam Woolley; David Woolley; Craig Zwickl; Catrin Hasselgren
Journal:  Regul Toxicol Pharmacol       Date:  2018-04-17       Impact factor: 3.271

9.  Integrative chemical-biological read-across approach for chemical hazard classification.

Authors:  Yen Low; Alexander Sedykh; Denis Fourches; Alexander Golbraikh; Maurice Whelan; Ivan Rusyn; Alexander Tropsha
Journal:  Chem Res Toxicol       Date:  2013-08-05       Impact factor: 3.739

10.  Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility.

Authors:  Thomas Luechtefeld; Dan Marsh; Craig Rowlands; Thomas Hartung
Journal:  Toxicol Sci       Date:  2018-09-01       Impact factor: 4.849

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  3 in total

1.  Transitioning the Generalised Read-Across approach (GenRA) to quantitative predictions: A case study using acute oral toxicity data.

Authors:  George Helman; Imran Shah; Grace Patlewicz
Journal:  Comput Toxicol       Date:  2019-11-01

2.  A Framework that Considers the Impacts of Time, Cost, and Uncertainty in the Determination of the Cost Effectiveness of Toxicity-Testing Methodologies.

Authors:  Paul S Price; Bryan J Hubbell; Shintaro Hagiwara; Greg M Paoli; Daniel Krewski; Annette Guiseppi-Elie; Maureen R Gwinn; Norman L Adkins; Russell S Thomas
Journal:  Risk Anal       Date:  2021-09-07       Impact factor: 4.302

3.  Internationalization of read-across as a validated new approach method (NAM) for regulatory toxicology.

Authors:  Costanza Rovida; Tara Barton-Maclaren; Emilio Benfenati; Francesca Caloni; P. Charukeshi Chandrasekera; Christophe Chesné; Mark T D Cronin; Joop De Knecht; Daniel R Dietrich; Sylvia E Escher; Suzanne Fitzpatrick; Brenna Flannery; Matthias Herzler; Susanne Hougaard Bennekou; Bruno Hubesch; Hennicke Kamp; Jaffar Kisitu; Nicole Kleinstreuer; Simona Kovarich; Marcel Leist; Alexandra Maertens; Kerry Nugent; Giorgia Pallocca; Manuel Pastor; Grace Patlewicz; Manuela Pavan; Octavio Presgrave; Lena Smirnova; Michael Schwarz; Takashi Yamada; Thomas Hartung
Journal:  ALTEX       Date:  2020-04-30       Impact factor: 6.250

  3 in total

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