Literature DB >> 30320239

Predictive Models for Acute Oral Systemic Toxicity: A Workshop to Bridge the Gap from Research to Regulation.

Nicole C Kleinstreuer1, Agnes Karmaus2, Kamel Mansouri2, David G Allen2, Jeremy M Fitzpatrick3, Grace Patlewicz3.   

Abstract

In early 2018, the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) published the "Strategic Roadmap for Establishing New Approaches to Evaluate the Safety of Chemicals and Medical Products in the United States" (ICCVAM 2018). Cross-agency federal workgroups have been established to implement this roadmap for various toxicological testing endpoints, with an initial focus on acute toxicity testing. The ICCVAM acute toxicity workgroup (ATWG) helped organize a global collaboration to build predictive in silico models for acute oral systemic toxicity, based on a large dataset of rodent studies and targeted towards regulatory needs identified across federal agencies. Thirty-two international groups across government, industry, and academia participated in the project, culminating in a workshop in April 2018 held at the National Institutes of Health (NIH). At the workshop, computational modelers and regulatory decision makers met to discuss the feasibility of using predictive model outputs for regulatory use in lieu of acute oral systemic toxicity testing. The models were combined to yield consensus predictions which demonstrated excellent performance when compared to the animal data, and workshop outcomes and follow-up activities to make these tools available and put them into practice are discussed here.

Entities:  

Keywords:  ICCVAM; QSAR; acute oral toxicity; read-across; workshop

Year:  2018        PMID: 30320239      PMCID: PMC6178952          DOI: 10.1016/j.comtox.2018.08.002

Source DB:  PubMed          Journal:  Comput Toxicol        ISSN: 2468-1113


  3 in total

Review 1.  Status of acute systemic toxicity testing requirements and data uses by U.S. regulatory agencies.

Authors:  Judy Strickland; Amy J Clippinger; Jeffrey Brown; David Allen; Abigail Jacobs; Joanna Matheson; Anna Lowit; Emily N Reinke; Mark S Johnson; Michael J Quinn; David Mattie; Suzanne C Fitzpatrick; Surender Ahir; Nicole Kleinstreuer; Warren Casey
Journal:  Regul Toxicol Pharmacol       Date:  2018-02-03       Impact factor: 3.271

2.  CERAPP: Collaborative Estrogen Receptor Activity Prediction Project.

Authors:  Kamel Mansouri; Ahmed Abdelaziz; Aleksandra Rybacka; Alessandra Roncaglioni; Alexander Tropsha; Alexandre Varnek; Alexey Zakharov; Andrew Worth; Ann M Richard; Christopher M Grulke; Daniela Trisciuzzi; Denis Fourches; Dragos Horvath; Emilio Benfenati; Eugene Muratov; Eva Bay Wedebye; Francesca Grisoni; Giuseppe F Mangiatordi; Giuseppina M Incisivo; Huixiao Hong; Hui W Ng; Igor V Tetko; Ilya Balabin; Jayaram Kancherla; Jie Shen; Julien Burton; Marc Nicklaus; Matteo Cassotti; Nikolai G Nikolov; Orazio Nicolotti; Patrik L Andersson; Qingda Zang; Regina Politi; Richard D Beger; Roberto Todeschini; Ruili Huang; Sherif Farag; Sine A Rosenberg; Svetoslav Slavov; Xin Hu; Richard S Judson
Journal:  Environ Health Perspect       Date:  2016-02-23       Impact factor: 9.031

3.  OPERA models for predicting physicochemical properties and environmental fate endpoints.

Authors:  Kamel Mansouri; Chris M Grulke; Richard S Judson; Antony J Williams
Journal:  J Cheminform       Date:  2018-03-08       Impact factor: 5.514

  3 in total
  13 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.  CATMoS: Collaborative Acute Toxicity Modeling Suite.

Authors:  Kamel Mansouri; Agnes L Karmaus; Jeremy Fitzpatrick; Grace Patlewicz; Prachi Pradeep; Domenico Alberga; Nathalie Alepee; Timothy E H Allen; Dave Allen; Vinicius M Alves; Carolina H Andrade; Tyler R Auernhammer; Davide Ballabio; Shannon Bell; Emilio Benfenati; Sudin Bhattacharya; Joyce V Bastos; Stephen Boyd; J B Brown; Stephen J Capuzzi; Yaroslav Chushak; Heather Ciallella; Alex M Clark; Viviana Consonni; Pankaj R Daga; Sean Ekins; Sherif Farag; Maxim Fedorov; Denis Fourches; Domenico Gadaleta; Feng Gao; Jeffery M Gearhart; Garett Goh; Jonathan M Goodman; Francesca Grisoni; Christopher M Grulke; Thomas Hartung; Matthew Hirn; Pavel Karpov; Alexandru Korotcov; Giovanna J Lavado; Michael Lawless; Xinhao Li; Thomas Luechtefeld; Filippo Lunghini; Giuseppe F Mangiatordi; Gilles Marcou; Dan Marsh; Todd Martin; Andrea Mauri; Eugene N Muratov; Glenn J Myatt; Dac-Trung Nguyen; Orazio Nicolotti; Reine Note; Paritosh Pande; Amanda K Parks; Tyler Peryea; Ahsan H Polash; Robert Rallo; Alessandra Roncaglioni; Craig Rowlands; Patricia Ruiz; Daniel P Russo; Ahmed Sayed; Risa Sayre; Timothy Sheils; Charles Siegel; Arthur C Silva; Anton Simeonov; Sergey Sosnin; Noel Southall; Judy Strickland; Yun Tang; Brian Teppen; Igor V Tetko; Dennis Thomas; Valery Tkachenko; Roberto Todeschini; Cosimo Toma; Ignacio Tripodi; Daniela Trisciuzzi; Alexander Tropsha; Alexandre Varnek; Kristijan Vukovic; Zhongyu Wang; Liguo Wang; Katrina M Waters; Andrew J Wedlake; Sanjeeva J Wijeyesakere; Dan Wilson; Zijun Xiao; Hongbin Yang; Gergely Zahoranszky-Kohalmi; Alexey V Zakharov; Fagen F Zhang; Zhen Zhang; Tongan Zhao; Hao Zhu; Kimberley M Zorn; Warren Casey; Nicole C Kleinstreuer
Journal:  Environ Health Perspect       Date:  2021-04-30       Impact factor: 9.031

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

Authors:  Grace Patlewicz; Lucina E Lizarraga; Diego Rua; David G Allen; Amber B Daniel; Suzanne C Fitzpatrick; Natàlia Garcia-Reyero; John Gordon; Pertti Hakkinen; Angela S Howard; Agnes Karmaus; Joanna Matheson; Moiz Mumtaz; Andrea-Nicole Richarz; Patricia Ruiz; Louis Scarano; Takashi Yamada; Nicole Kleinstreuer
Journal:  Regul Toxicol Pharmacol       Date:  2019-05-10       Impact factor: 3.271

Review 4.  In Silico Models for Predicting Acute Systemic Toxicity.

Authors:  Ivanka Tsakovska; Antonia Diukendjieva; Andrew P Worth
Journal:  Methods Mol Biol       Date:  2022

5.  Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods.

Authors:  Sankalp Jain; Vishal B Siramshetty; Vinicius M Alves; Eugene N Muratov; Nicole Kleinstreuer; Alexander Tropsha; Marc C Nicklaus; Anton Simeonov; Alexey V Zakharov
Journal:  J Chem Inf Model       Date:  2021-02-03       Impact factor: 4.956

6.  A cross-industry collaboration to assess if acute oral toxicity (Q)SAR models are fit-for-purpose for GHS classification and labelling.

Authors:  Joel Bercu; Melisa J Masuda-Herrera; Alejandra Trejo-Martin; Catrin Hasselgren; Jean Lord; Jessica Graham; Matthew Schmitz; Lawrence Milchak; Colin Owens; Surya Hari Lal; Richard Marchese Robinson; Sarah Whalley; Phillip Bellion; Anna Vuorinen; Kamila Gromek; William A Hawkins; Iris van de Gevel; Kathleen Vriens; Raymond Kemper; Russell Naven; Pierre Ferrer; Glenn J Myatt
Journal:  Regul Toxicol Pharmacol       Date:  2020-12-17       Impact factor: 3.271

7.  SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data.

Authors:  Domenico Gadaleta; Kristijan Vuković; Cosimo Toma; Giovanna J Lavado; Agnes L Karmaus; Kamel Mansouri; Nicole C Kleinstreuer; Emilio Benfenati; Alessandra Roncaglioni
Journal:  J Cheminform       Date:  2019-08-30       Impact factor: 5.514

8.  Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations.

Authors:  Saskia Comess; Alexia Akbay; Melpomene Vasiliou; Ronald N Hines; Lucas Joppa; Vasilis Vasiliou; Nicole Kleinstreuer
Journal:  Front Artif Intell       Date:  2020-05-15

9.  The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity.

Authors:  James W Firman; Mark T D Cronin; Philip H Rowe; Elizaveta Semenova; John E Doe
Journal:  Arch Toxicol       Date:  2022-01-16       Impact factor: 5.153

10.  Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach.

Authors:  Heather L Ciallella; Daniel P Russo; Lauren M Aleksunes; Fabian A Grimm; Hao Zhu
Journal:  Environ Sci Technol       Date:  2021-07-25       Impact factor: 11.357

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