Ecotoxicity Testing

Ecotoxicity Testing and the 3Rs Alternatives.   Ecotoxicology is the study of how environmental pollution affects ecological entities, i.e. populations, communities or ecosystems. Government agencies regulate new chemical products and pollution from industry and agriculture, mandating toxicity tests to determine how substances effect the environment. Organizations are prioritizing the development and validation of ecotoxicity testing methods that avoid using living animals. These alternative testing methods include in vitro tests such as cell lines, bioassays, and microfluidic (“organ-on-a-chip”) devices; in silico/computer modeling and databases of animal testing data for chemical compounds; as well as in chemico analysis. Other ecotoxicity tests considered as replacement methods utilize lower organisms such as pond snails, fish embryos, or algae.
Search for Scientific Literature on 3Rs approaches to Toxicity Testing

The following resources contain scientific literature about reduction, refinement or replacement (3Rs alternatives) in ecotoxicity testing.

Organizations working to validate alternative methods for Ecotoxicity Testing

Toxicity Testing in the 21st Century – A Vision and a Strategy 
The National Research Council was asked by the U.S. Environmental Protection Agency to review the state of the science and create a far-reaching vision for the future of toxicity testing. Developing, improving, and validating new laboratory tools could improve our ability to understand the hazards and risks posed by chemicals. This would lead to more informed environmental regulations and dramatically reduce the need for animal testing because the new tests would be based on human cells and cell components.
EURL ECVAM: Accepted Alternative Methods for Toxicity Testing 
The European Union Reference Laboratory for alternatives to animal testing (EURL) ECVAM has contributed to the validation of the test methods. The validation of other test methods has been undertaken by ICATM (International Cooperation on Alternative Test Methods) partners.   
ICE: Integrated Chemical Environment, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM) 
Successful computational toxicology projects depend on high-quality data that are freely available and formatted for use in computational workflows. The Integrated Chemical Environment (ICE) addresses the data needs frequently expressed by NICEATM stakeholders. Launched in March 2017, ICE provides curated data from NICEATM, its partners, and other resources, as well as tools to facilitate the safety assessment of chemicals.   
Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM)
ICCVAM is a permanent committee of the National Institute of Environmental Health Sciences and is composed of representatives from sixteen federal regulatory and research agencies, including USDA. One of the goals of ICCVAM is to reduce, refine, or replace the use of animals in toxicological and safety testing where feasible.   
NICEATM: Accepted Alternative Methods
The NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM) is an NTP office focused on the development and evaluation of alternatives to animal use for chemical safety testing. The topics in this section provide information about approaches used to replace, reduce, or refine animal use while ensuring that the toxic potential of substances is appropriately characterized.  
NICEATM Alternative Methods: Computational Toxicology Projects
Computational toxicology uses mathematics, informatics and computer models to better understand toxicity mechanisms and predict toxic effects. On this page you will also find links to the Integrated Chemical Environment (ICE), which provides data and tools to help with the development of new testing approaches. You will also find information on the Open Structure-activity/property Relationship APP (OPERA), which provides predictions on physiochemical properties, environmental fate, and toxicity endpoints. 
TSAR (Tracking Systems for Alternative Methods towards Regulatory acceptance), EURL-EVCAM
TSAR tracks the progress of alternative, non-animal methods, for testing chemicals or biological agents such as vaccines towards acceptance as a recognized test method for use in various sectors.


Ecotoxicity Testing & the 3Rs Alternatives Selected Bibliography

Below is a selected bibliography of scholarly literature from 2010 to 2021 on 3Rs approaches to replace, reduce and refine animal use in ecotoxicity testing.

Multiple 3Rs Testing Methods in Ecotoxicity 

Ashauer, R., & Jager, T. (2018). Physiological modes of action across species and toxicants: The key to predictive  ecotoxicology. Environmental Science. Processes & Impacts, 20(1), 48–57.

Baderna, D., Lomazzi, E., Passoni, A., Pogliaghi, A., Petoumenou, M. I., Bagnati, R., Lodi, M., Viarengo, A., Sforzini, S., Benfenati, E., & Fanelli, R. (2015). Chemical characterization and ecotoxicity of three soil foaming agents used in mechanized tunneling. Journal of Hazardous Materials, 296, 210–220.

Bols, N. C., & Hermens, J. L. M. (2008). Developing a list of reference chemicals for testing alternatives to whole fish  toxicity tests. Aquatic Toxicology (Amsterdam, Netherlands), 90(2), 128–137.

Burden, N., Benstead, R., Clook, M., Doyle, I., Edwards, P., Maynard, S. K., Ryder, K., Sheahan, D., Whale, G., van Egmond, R., Wheeler, J. R., & Hutchinson, T. H. (2016). Advancing the 3Rs in regulatory ecotoxicology: A pragmatic cross-sector approach. Integrated Environmental Assessment and Management, 12(3), 417–421.   

Burden, N., Benstead, R., Benyon, K., Clook, M., Green, C., Handley, J., Harper, N., Maynard, S. K., Mead, C., Pearson, A., Ryder, K., Sheahan, D., Egmond, R., Wheeler, J. R., & Hutchinson, T. H. (2020). Key Opportunities to Replace, Reduce, and Refine Regulatory Fish Acute Toxicity Tests. Environmental Toxicology and Chemistry, 39(10), 2076–2089.

Cho, S., & Yoon, J.-Y. (2017). Organ-on-a-chip for assessing environmental toxicants. Current Opinion in Biotechnology, 45, 34–42.

Coady, K. K., Biever, R. C., Denslow, N. D., Gross, M., Guiney, P. D., Holbech, H., Karouna-Renier, N. K., Katsiadaki, I., Krueger, H., Levine, S. L., Maack, G., Williams, M., Wolf, J. C., & Ankley, G. T. (2017). Current limitations and recommendations to improve testing for the environmental assessment of endocrine active substances. Integrated Environmental Assessment and Management, 13(2), 302–316.

Croce, R., Cina, F., Lombardo, A., Crispeyn, G., Cappelli, C. I., Vian, M., Maiorana, S., Benfenati, E., & Baderna, D. (2017). Aquatic toxicity of several textile dye formulations: Acute and chronic assays with Daphnia magna and Raphidocelis subcapitata. Ecotoxicology and Environmental Safety, 144, 79–87.

Fahd, F., Khan, F., Veitch, B., & Yang, M. (2017). Aquatic ecotoxicological models and their applicability in Arctic regions. Marine Pollution Bulletin, 120(1–2), 428–437.

Henneberg, A., Bender, K., Blaha, L., Giebner, S., Kuch, B., Kohler, H.-R., Maier, D., Oehlmann, J., Richter, D., Scheurer, M., Schulte-Oehlmann, U., Sieratowicz, A., Ziebart, S., & Triebskorn, R. (2014). Are in vitro methods for the detection of endocrine potentials in the aquatic environment predictive for in vivo effects? Outcomes of the Projects SchussenAktiv and SchussenAktivplus in the Lake Constance Area, Germany. PloS One, 9(6), e98307.

Hensen, B., Olsson, O., & Kümmerer, K. (2020). A strategy for an initial assessment of the ecotoxicological effects of transformation products of pesticides in aquatic systems following a tiered approach. Environment International, 137, 105533. 

Hultman, M. T., Loken, K. B., Grung, M., Reid, M. J., & Lillicrap, A. (2019). Performance of Three-Dimensional Rainbow Trout (Oncorhynchus mykiss) Hepatocyte Spheroids for Evaluating Biotransformation of Pyrene. Environmental Toxicology and Chemistry, 38(8), 1738–1747.

Ishibashi, H., Uchida, M., Hirano, M., Hayashi, T., Yamamoto, R., Kubota, A., Ichikawa, N., Ishibashi, Y., Tominaga, N., & Arizono, K. (2021). In vivo and in silico analyses of estrogenic potential of equine estrogens in medaka (Oryzias latipes). Science of the Total Environment, 767. Scopus. 

Kollar, T., Kasa, E., Ferincz, A., Urbanyi, B., Csenki-Bakos, Z., & Horvath, A. (2018). Development of an in vitro toxicological test system based on zebrafish (Danio rerio) sperm analysis. Environmental Science and Pollution Research International, 25(15), 14426–14436.

Madden, J. C., Rogiers, V., & Vinken, M. (2014). Application of in silico and in vitro methods in the development of adverse outcome pathway constructs in wildlife. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 369(1656).

Miller, T. H., Gallidabino, M. D., MacRae, J. I., Owen, S. F., Bury, N. R., & Barron, L. P. (2019). Prediction of bioconcentration factors in fish and invertebrates using machine learning. The Science of the Total Environment, 648, 80–89.

Mondou, M., Hickey, G. M., Rahman, H. T., Maguire, S., Pain, G., Crump, D., Hecker, M., & Basu, N. (2020). Factors Affecting the Perception of New Approach Methodologies (NAMs) in the  Ecotoxicology Community. Integrated Environmental Assessment and Management, 16(2), 269–281.

Neale, P. A., Ait-Aissa, S., Brack, W., Creusot, N., Denison, M. S., Deutschmann, B., Hilscherová, K., Hollert, H., Krauss, M., Novák, J., Schulze, T., Seiler, T.-B., Serra, H., Shao, Y., & Escher, B. I. (2015). Linking in Vitro Effects and Detected Organic Micropollutants in Surface Water Using  Mixture-Toxicity Modeling. Environmental Science & Technology, 49(24), 14614–14624.

Nendza, M., Kuhne, R., Lombardo, A., Strempel, S., & Schuurmann, G. (2018). PBT assessment under REACH: Screening for low aquatic bioaccumulation with QSAR classifications based on physicochemical properties to replace BCF in vivo testing on fish. The Science of the Total Environment, 616–617, 97–106.

Patlewicz, G. Y., & Lander, D. R. (2013). A step change towards risk assessment in the 21st century. Frontiers in Bioscience (Elite Edition), 5, 418–434.

Rehberger, K., Kropf, C., & Segner, H. (2018). In vitro or not in vitro: a short journey through a long history. Environmental sciences Europe, 30, 23.

Schirmer, K., Tanneberger, K., Kramer, N. I., Völker, D., Scholz, S., Hafner, C., Lee, L. E. J., Tralau, T., Riebeling, C., Pirow, R., Oelgeschläger, M., Seiler, A., Liebsch, M., & Luch, A. (2012). Wind of change challenges toxicological regulators. Environmental Health Perspectives, 120(11), 1489–1494.

Teixidó, E., Leuthold, D., de Crozé, N., Léonard, M., & Scholz, S. (2020). Comparative Assessment of the Sensitivity of Fish Early-Life Stage, Daphnia, and Algae Tests to the Chronic Ecotoxicity of Xenobiotics: Perspectives for Alternatives to Animal Testing. Environmental Toxicology and Chemistry, 39(1), 30–41. Scopus. 

Vonk, J. A., Benigni, R., Hewitt, M., Nendza, M., Segner, H., van de Meent, D., & Cronin, M. T. D. (2009). The use of mechanisms and modes of toxic action in integrated testing strategies: The report and recommendations of a workshop held as part of the European Union  OSIRIS Integrated Project. Alternatives to Laboratory Animals : ATLA, 37(5), 557–571.

Walker, C. H. (2008). Ecotoxicity testing: Science, politics and ethics. Alternatives to Laboratory Animals : ATLA, 36(1), 103–112.

In Vitro Methodologies

Baron, M. G., Purcell, W. M., Jackson, S. K., Owen, S. F., & Jha, A. N. (2012). Towards a more representative in vitro method for fish ecotoxicology: Morphological and biochemical characterisation of three-dimensional spheroidal hepatocytes. Ecotoxicology (London, England), 21(8), 2419–2429.

Cervena, T., Vrbova, K., Rossnerova, A., Topinka, J., & Rossner, P., Jr. (2019). Short-term and Long-term Exposure of the MucilAirTM Model to Polycyclic Aromatic Hydrocarbons. Alternatives to Laboratory Animals : ATLA, 47(1), 9–18. Scopus.

Curtis, T. M., Collins, A. M., Gerlach, B. D., Brennan, L. M., Widder, M. W., van der Schalie, W. H., Vo, N. T. K., & Bols, N. C. (2013). Suitability of invertebrate and vertebrate cells in a portable impedance-based  toxicity sensor: Temperature mediated impacts on long-term survival. Toxicology in Vitro : An International Journal Published in Association with BIBRA, 27(7), 2061–2066.

Embry, M. R., Belanger, S. E., Braunbeck, T. A., Galay-Burgos, M., Halder, M., Hinton, D. E., Léonard, M. A., Lillicrap, A., Norberg-King, T., & Whale, G. (2010). The fish embryo toxicity test as an animal alternative method in hazard and risk  assessment and scientific research. Aquatic Toxicology (Amsterdam, Netherlands), 97(2), 79–87.

Gerbron, M., Geraudie, P., Rotchell, J., & Minier, C. (2010). A new in vitro screening bioassay for the ecotoxicological evaluation of the estrogenic responses of environmental chemicals using roach (Rutilus rutilus) liver explant culture. Environmental Toxicology, 25(5), 510–516.

Green, B. T., Lee, S. T., Davis, T. Z., & Welch, K. D. (2020). Microsomal activation, and SH-SY5Y cell toxicity studies of tremetone and 6-hydroxytremetone isolated from rayless goldenrod (Isocoma pluriflora) and white snakeroot (Agertina altissima), respectively. Toxicon: X, 5, 100018.

Heinrich, P., Diehl, U., Förster, F., & Braunbeck, T. (2014). Improving the in vitro ethoxyresorufin-O-deethylase (EROD) assay with RTL-W1 by  metabolic normalization and use of β-naphthoflavone as the reference substance. Comparative Biochemistry and Physiology. Toxicology & Pharmacology : CBP, 164, 27–34.

Huang, S., Wiszniewski, L., Constant, S., & Roggen, E. (2013). Potential of in vitro reconstituted 3D human airway epithelia (MucilAirTM) to assess respiratory sensitizers. Toxicology in Vitro, 27(3), 1151–1156. Scopus.

Laue, H., Hostettler, L., Sanders, G., Kreutzer, G., & Natsch, A. (2020). PeBiToSens (TM): A Platform for PBT Screening of Fragrance Ingredients Without Animal Testing. Chimia, 74(3), 168–175. 

Lee, S. T., Stonecipher, C. A., dos Santos, F. C., Pfister, J. A., Welch, K. D., Cook, D., Green, B. T., Gardner, D. R., & Panter, K. E. (2019). An Evaluation of Hair, Oral Fluid, Earwax, and Nasal Mucus as Noninvasive Specimens to Determine Livestock Exposure to Teratogenic Lupine Species. Journal of Agricultural and Food Chemistry, 67(1), 43–49.

Norberg-King, T. J., Embry, M. R., Belanger, S. E., Braunbeck, T., Butler, J. D., Dorn, P. B., Farr, B., Guiney, P. D., Hughes, S. A., Jeffries, M., Journel, R., Lèonard, M., McMaster, M., Oris, J. T., Ryder, K., Segner, H., Senac, T., Van Der Kraak, G., Whale, G., & Wilson, P. (2018). An International Perspective on the Tools and Concepts for Effluent Toxicity  Assessments in the Context of Animal Alternatives: Reduction in Vertebrate Use. Environmental Toxicology and Chemistry, 37(11), 2745–2757.

Saeed, S., Al-Naema, N., Butler, J. D., & Febbo, E. J. (2015). Arabian killifish (Aphanius dispar) embryos: A model organism for the risk  assessment of the Arabian Gulf coastal waters. Environmental Toxicology and Chemistry, 34(12), 2898–2905.

Steimberg, N. (2020). IPS, organoids and 3D models as advanced tools for in vitro toxicology. ALTEX, 136–140.

Stelzer, J. A. A., Rosin, C. K., Bauer, L. H., Hartmann, M., Pulgati, F. H., & Arenzon, A. (2018). Is fish embryo test (FET) according to OECD 236 sensible enough for delivering  quality data for effluent risk assessment? Environmental Toxicology and Chemistry, 37(11), 2925–2932.

Stonecipher, C. A., Lee, S. T., Green, B. T., Cook, D., Welch, K. D., Pfister, J. A., & Gardner, D. R. (2019). Evaluation of noninvasive specimens to diagnose livestock exposure to toxic larkspur (Delphinium spp.). Toxicon : Official Journal of the International Society on Toxinology, 161, 33–39.

Wagner, M., Kienle, C., Vermeirssen, E. L. M., & Oehlmann, J. (2017). Endocrine Disruption and In Vitro Ecotoxicology: Recent Advances and Approaches. Advances in Biochemical Engineering/Biotechnology, 157, 1–58.

Zeng, F., Sherry, J. P., & Bols, N. C. (2016). Use of the rainbow trout cell lines, RTgill-W1 and RTL-W1 to evaluate the toxic  potential of benzotriazoles. Ecotoxicology and Environmental Safety, 124, 315–323.

In Chemico Methodologies
Trush, M., Metelytsia, L., Semenyuta, I., Kalashnikova, L., Papeykin, O., Venger, I., Tarasyuk, O., Bodachivska, L., Blagodatnyi, V., & Rogalsky, S. (2019). Reduced ecotoxicity and improved biodegradability of cationic biocides based on  ester-functionalized pyridinium ionic liquids. Environmental Science and Pollution Research International, 26(5), 4878–4889.

In Silico Methodologies

Bell, S. M., Angrish, M. M., Wood, C. E., & Edwards, S. W. (2016). Integrating Publicly Available Data to Generate Computationally Predicted Adverse Outcome Pathways for Fatty Liver. Toxicological Sciences : An Official Journal of the Society of Toxicology, 150(2), 510–520.

Cao, D.-S., Zhao, J.-C., Yang, Y.-N., Zhao, C.-X., Yan, J., Liu, S., Hu, Q.-N., Xu, Q.-S., & Liang, Y.-Z. (2012). In silico toxicity prediction by support vector machine and SMILES  representation-based string kernel. SAR and QSAR in Environmental Research, 23(1–2), 141–153.

Cappelli, C. I., Toropov, A. A., Toropova, A. P., & Benfenati, E. (2020). Ecosystem ecology: Models for acute toxicity of pesticides towards Daphnia magna. Environmental Toxicology and Pharmacology, 80, 103459. 

Chang, C. M., Chang, C.-W., Wu, F.-W., Chang, L., & Liu, T.-C. (2020). In silico ecotoxicological modeling of pesticide metabolites and mixtures. In Methods Pharmacol. Toxicol. (p. 589). Humana Press Inc.; Scopus. 
Connors, K. A., Beasley, A., Barron, M. G., Belanger, S. E., Bonnell, M., Brill, J. L., de Zwart, D., Kienzler, A., Krailler, J., Otter, R., Phillips, J. L., & Embry, M. R. (2019). Creation of a Curated Aquatic Toxicology Database: EnviroTox. Environmental Toxicology and Chemistry, 38(5), 1062–1073. 

Cronin, M. T. D. (2017). (Q)SARs to predict environmental toxicities: Current status and future needs. Environmental Science. Processes & Impacts, 19(3), 213–220.

Das, R. N., Roy, K., & Popelier, P. L. A. (2015). Interspecies quantitative structure-toxicity-toxicity (QSTTR) relationship modeling of ionic liquids. Toxicity of ionic liquids to V. fischeri, D. magna and S. vacuolatus. Ecotoxicology and Environmental Safety, 122, 497–520.

Douziech, M., Ragas, A. M. J., van Zelm, R., Oldenkamp, R., Jan Hendriks, A., King, H., Oktivaningrum, R., & Huijbregts, M. A. J. (2020). Reliable and representative in silico predictions of freshwater ecotoxicological hazardous concentrations. Environment International, 134, 105334. 

Galimberti, F., Moretto, A., & Papa, E. (2020). Application of chemometric methods and QSAR models to support pesticide risk assessment starting from ecotoxicological datasets. Water Research, 174, 115583.

 Gajewicz-Skretna, A., Furuhama, A., Yamamoto, H., & Suzuki, N. (2021). Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: Towards similarity-based machine learning methods. Chemosphere, 280. Scopus.

Jager, T., & Kooijman, S. A. L. M. (2009). A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity. Ecotoxicology (London, England), 18(2), 187–196.

Judson, R., Houck, K., Martin, M., Knudsen, T., Thomas, R. S., Sipes, N., Shah, I., Wambaugh, J., & Crofton, K. (2014). In vitro and modelling approaches to risk assessment from the U.S. environmental protection agency ToxCast programme. Basic and Clinical Pharmacology and Toxicology, 115(1), 69–76. Scopus. 

Kar, S., Roy, K., & Leszczynski, J. (2018). Impact of Pharmaceuticals on the Environment: Risk Assessment Using QSAR Modeling Approach. Methods in Molecular Biology (Clifton, N.J.), 1800, 395–443.

Kleinstreuer, N. C., Karmaus, A. L., Mansouri, K., Allen, D. G., Fitzpatrick, J. M., & Patlewicz, G. (2018). Predictive models for acute oral systemic toxicity: A workshop to bridge the gap from research to regulation. Computational Toxicology, 8, 21–24. Scopus.

Lavado, G. J., Gadaleta, D., Toma, C., Golbamaki, A., Toropov, A. A., Toropova, A. P., Marzo, M., Baderna, D., Arning, J., & Benfenati, E. (2020). Zebrafish AC50 modelling: (Q)SAR models to predict developmental toxicity in zebrafish embryo. Ecotoxicology and Environmental Safety, 202. Agricola.

Mansouri, K., Abdelaziz, A., Rybacka, A., Roncaglioni, A., Tropsha, A., Varnek, A., Zakharov, A., Worth, A., Richard, A. M., Grulke, C. M., Trisciuzzi, D., Fourches, D., Horvath, D., Benfenati, E., Muratov, E., Wedebye, E. B., Grisoni, F., Mangiatordi, G. F., Incisivo, G. M., … Judson, R. S. (2016). CERAPP: Collaborative estrogen receptor activity prediction project. Environmental Health Perspectives, 124(7), 1023–1033. Scopus.

Mansouri, K., Kleinstreuer, N., Abdelaziz, A. M., Alberga, D., Alves, V. M., Andersson, P. L., Andrade, C. H., Bai, F., Balabin, I., Ballabio, D., Benfenati, E., Bhhatarai, B., Boyer, S., Chen, J., Consonni, V., Farag, S., Fourches, D., García-Sosa, A. T., Gramatica, P., … Judson, R. S. (2020). Compara: Collaborative modeling project for androgen receptor activity. Environmental Health Perspectives, 128(2). Scopus.

Mellor, C. L., Tollefsen, K. E., LaLone, C., Cronin, M. T. D., & Firman, J. W. (2020). In Silico Identification of Chemicals Capable of Binding to the Ecdysone Receptor. Environmental Toxicology and Chemistry, 39(7), 1438–1450.

Mougin, C., Azam, D., Caquet, T., Cheviron, N., Dequiedt, S., Le Galliard, J.-F., Guillaume, O., Houot, S., Lacroix, G., Lafolie, F., Maron, P.-A., Michniewicz, R., Pichot, C., Ranjard, L., Roy, J., Zeller, B., Clobert, J., & Chanzy, A. (2015). A coordinated set of ecosystem research platforms open to international research  in ecotoxicology, AnaEE-France. Environmental Science and Pollution Research International, 22(20), 16215–16228.

Nazmul Hassan, M., Peace, A., & Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA. (2020). Mechanistically derived Toxicant-mediated predator-prey model under Stoichiometric constraints. Mathematical Biosciences and Engineering, 17(1), 349–365.

Nymark, P., Rieswijk, L., Ehrhart, F., Jeliazkova, N., Tsiliki, G., Sarimveis, H., Evelo, C. T., Hongisto, V., Kohonen, P., Willighagen, E., & Grafstrom, R. C. (2018). A Data Fusion Pipeline for Generating and Enriching Adverse Outcome Pathway Descriptions. Toxicological Sciences : An Official Journal of the Society of Toxicology, 162(1), 264–275.

Ojha, P. K., Mandal, D., & Roy, K. (2020). QSPR modeling of adsorption of pollutants by carbon nanotubes (CNTs). In Methods Pharmacol. Toxicol.. (p. 511). Humana Press Inc.; Scopus.

Oki, N. O., Nelms, M. D., Bell, S. M., Mortensen, H. M., & Edwards, S. W. (2016). Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources. Current Environmental Health Reports, 3(1), 53–63.

Peng, D. L., & Picchioni, F. (2020). Prediction of toxicity of Ionic Liquids based on GC-COSMO method. Journal of Hazardous Materials, 398, 12.

Preuss, T. G., Hammers-Wirtz, M., & Ratte, H. T. (2010). The potential of individual based population models to extrapolate effects measured at standardized test conditions to relevant environmental conditions—An example for 3,4-dichloroaniline on Daphnia magna. Journal of Environmental Monitoring : JEM, 12(11), 2070–2079.

Raitano, G., Goi, D., Pieri, V., Passoni, A., Mattiussi, M., Lutman, A., Romeo, I., Manganaro, A., Marzo, M., Porta, N., Baderna, D., Colombo, A., Aneggi, E., Natolino, F., Lodi, M., Bagnati, R., & Benfenati, E. (2018). (Eco)toxicological maps: A new risk assessment method integrating traditional and in silico tools and its application in the Ledra River (Italy). Environment International, 119, 275–286.

Roy, K. (Ed.). (2020). Ecotoxicological QSARs. Springer US.

Salvito, D., Fernandez, M., Jenner, K., Lyon, D. Y., Knecht, J., Mayer, P., MacLeod, M., Eisenreich, K., Leonards, P., Cesnaitis, R., León‐Paumen, M., Embry, M., & Déglin, S. E. (2020). Improving the Environmental Risk Assessment of Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials. Environmental Toxicology and Chemistry, 39(11), 2097–2108.

Sangion, A., & Gramatica, P. (2016). Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity. Environment International, 95, 131–143. 

Schwobel, J. A. H., Madden, J. C., & Cronin, M. T. D. (2011). Application of a computational model for Michael addition reactivity in the prediction of toxicity to Tetrahymena pyriformis. Chemosphere, 85(6), 1066–1074.

Takata, M., Lin, B.-L., Xue, M., Zushi, Y., Terada, A., & Hosomi, M. (2020). Predicting the acute ecotoxicity of chemical substances by machine learning using graph theory. Chemosphere, 238, 124604.

Traore, H., Crouzet, O., Mamy, L., Sireyjol, C., Rossard, V., Servien, R., Latrille, E., Martin-Laurent, F., Patureau, D., & Benoit, P. (2018). Clustering pesticides according to their molecular properties, fate, and effects  by considering additional ecotoxicological parameters in the TyPol method. Environmental Science and Pollution Research International, 25(5), 4728–4738.

Webb, J. M., Smucker, B. J., & Bailer, A. J. (2014). Selecting the best design for nonstandard toxicology experiments. Environmental Toxicology and Chemistry, 33(10), 2399–2406.

Zhang, Chen, Cheng, F., Sun, L., Zhuang, S., Li, W., Liu, G., Lee, P. W., & Tang, Y. (2015). In silico prediction of chemical toxicity on avian species using chemical category approaches. Chemosphere, 122, 280–287.

Zhang, J., Bailer, A. J., & Oris, J. T. (2012). Bayesian approach to estimating reproductive inhibition potency in aquatic toxicity testing. Environmental Toxicology and Chemistry, 31(4), 916–927.


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