Development of an Enhanced Mechanistically Driven Mode of Action Classification Scheme for Adverse Effects on Environmental Species-Reference-Cited by-同舟云学术

Development of an Enhanced Mechanistically Driven Mode of Action Classification Scheme for Adverse Effects on Environmental Species

Published:2021-01-22 Issue:3 Volume:55 Page:1897-1907
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Sapounidou Maria¹,Ebbrell David J.¹,Bonnell Mark A.²,Campos Bruno³,Firman James W.¹^ORCID,Gutsell Steve³,Hodges Geoff³,Roberts Jayne³,Cronin Mark T. D.¹

Affiliation:

1. School of Pharmacy and Bimolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K.

2. Science and Risk Assessment Directorate, Environment & Climate Change Canada, 351 St. Joseph Blvd, Gatineau, Quebec K1A 0H3, Canada

3. Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, U.K.

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acs.est.0c06551

Reference84 articles.

1. Computational modelling for the sustainable management of chemicals

2. USEPA (2020) United States Environmental Protection Agency. ECOSAR Software, 2020; https://www.epa.gov/tsca-screening-tools/ecological-structure-activity-relationships-ecosar-predictive-model.

3. (Q)SARs to predict environmental toxicities: current status and future needs

4. Computational Methods to Predict Toxicity

5. The Role of Hydrophobicity in Toxicity Prediction

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