» Articles » PMID: 31724447

Application of Interspecies Correlation Estimation (ICE) Models and QSAR in Estimating Species Sensitivity to Pesticides

Overview
Date 2019 Nov 15
PMID 31724447
Citations 6
Authors
Affiliations
Soon will be listed here.
Abstract

Ecological risk assessment is challenged by the need to assess hazard to the diverse communities of organisms inhabiting aquatic and terrestrial systems. Computational approaches, such as Quantitative Structure Activity Relationships (QSAR) and Interspecies Correlation Estimation (ICE) models, are useful tools that provide estimates of acute toxicity where data are lacking or limited for ecological risk assessments (ERA). This review describes the technical basis of ICE models for use in pesticide ERA that may be used in conjunction with QSAR model estimates or surrogate species toxicity data and demonstrates the potential for improving hazard assessment. Validation and uncertainty analysis of ICE model predictions are summarized and used as guidance for selecting ICE models and evaluating toxicity predictions. A user-friendly web-based ICE modelling platform (Web-ICE) is described and demonstrated through case studies. Case studies include the development of Species Sensitivity Distributions generated from QSAR and ICE estimates, comparative sensitivity for a pesticide and its degradate, and application of ICE-estimated toxicity values for listed species assessments.

Citing Articles

Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report.

Banjare P, Murmu A, Matore B, Singh J, Papa E, Roy P Toxicol Res (Camb). 2024; 13(6):tfae191.

PMID: 39559274 PMC: 11569388. DOI: 10.1093/toxres/tfae191.


Sediment Toxicity Tests: A Critical Review of Their use in Environmental Regulations.

Leppanen M, Sourisseau S, Burgess R, Simpson S, Sibley P, Jonker M Environ Toxicol Chem. 2024; 43(8):1697-1716.

PMID: 38597781 PMC: 11326746. DOI: 10.1002/etc.5861.


Comparison of Substance-Based and Whole-Effluent Toxicity of Produced Water Discharges from Norwegian Offshore Oil and Gas Installations.

de Vries P, Jak R, Frost T Environ Toxicol Chem. 2022; 41(9):2285-2304.

PMID: 35723421 PMC: 9545660. DOI: 10.1002/etc.5414.


Daphnia magna and Ceriodaphnia dubia Have Similar Sensitivity in Standard Acute and Chronic Toxicity Tests.

Connors K, Brill J, Norberg-King T, Barron M, Carr G, Belanger S Environ Toxicol Chem. 2021; 41(1):134-147.

PMID: 34918372 PMC: 9601221. DOI: 10.1002/etc.5249.


A QSAR-ICE-SSD Model Prediction of the PNECs for Per- and Polyfluoroalkyl Substances and Their Ecological Risks in an Area of Electroplating Factories.

Zhang J, Zhang M, Tao H, Qi G, Guo W, Ge H Molecules. 2021; 26(21).

PMID: 34770982 PMC: 8587016. DOI: 10.3390/molecules26216574.


References
1.
Villaverde J, Sevilla-Moran B, Lopez-Goti C, Alonso-Prados J, Sandin-Espana P . Computational Methodologies for the Risk Assessment of Pesticides in the European Union. J Agric Food Chem. 2017; 65(10):2017-2018. DOI: 10.1021/acs.jafc.7b00516. View

2.
Schafer Jr E, Bowles Jr W . Acute oral toxicity and repellency of 933 chemicals to house and deer mice. Arch Environ Contam Toxicol. 1985; 14(1):111-29. DOI: 10.1007/BF01055769. View

3.
Schmolke A, Thorbek P, Chapman P, Grimm V . Ecological models and pesticide risk assessment: current modeling practice. Environ Toxicol Chem. 2010; 29(4):1006-12. DOI: 10.1002/etc.120. View

4.
Awkerman J, Raimondo S, Jackson C, Barron M . Augmenting aquatic species sensitivity distributions with interspecies toxicity estimation models. Environ Toxicol Chem. 2013; 33(3):688-95. DOI: 10.1002/etc.2456. View

5.
Sanderson H, Johnson D, Wilson C, Brain R, Solomon K . Probabilistic hazard assessment of environmentally occurring pharmaceuticals toxicity to fish, daphnids and algae by ECOSAR screening. Toxicol Lett. 2003; 144(3):383-95. DOI: 10.1016/s0378-4274(03)00257-1. View