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Articles

Ecotoxicity interspecies QAAR models from Daphnia toxicity of pharmaceuticals and personal care productsFootnote$

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Pages 781-798 | Received 15 Jul 2016, Accepted 24 Aug 2016, Published online: 22 Sep 2016

References

  • US EPA, Pharmaceuticals and Personal Care Products (PPCP). 2012. www.epa.gov
  • A.B.A. Boxall, M.A. Rudd, B.W. Brooks, D.J. Caldwell, K. Choi, S. Hickmann, E. Innes, K. Ostapyk, J. P. Staveley, T. Verslycke, G. T. Ankley, K. F. Beazley, S. E. Belanger, J. P. Berninger, P. Carriquiriborde, A. Coors, P. C. DeLeo, S. D. Dyer, J. F. Ericson, F. Gagné, J. P. Giesy, T. Gouin, L. Hallstrom, M. V. Karlsson, D. G. J. Larsson, J. M. Lazorchak, F. Mastrocco, A. McLaughlin, M. E. McMaster, R. D. Meyerhoff, R. Moore, J. L. Parrott, J. R. Snape, R. Murray-Smith, M. R. Servos, P. K. Sibley, J. O. Straub, N. D. Szabo, E. Topp, G. R. Tetreault, V. L. Trudeau, and G. Van Der Kraak, Pharmaceuticals and personal care products in the environment: What are the big questions?, Environ. Health Perspect. 120 (2012), pp. 1221–1229.
  • K.Y. Bell, M.J.M. Wells, K.A. Traexler, M.-L. Pellegrin, A. Morse, and J. Bandy, Emerging pollutants, Water Environ. Res. 83 (2011), pp. 1906–1984.
  • C. Hignite and D.L. Azarnoff, Drugs and drug metabolites as environmental contaminants: Chlorophenoxyisobutyrate and salicylic acid in sewage water effluent, Life Sci. 20 (1977), pp. 337–341.
  • G.W. Aherne, J. English, and V. Marks, The role of immunoassay in the analysis of microcontaminants in water samples, Ecotoxicol. Environ. Saf. 9 (1985), pp. 79–83.
  • M.L. Richardson and J.M. Bowron, The fate of pharmaceutical chemicals in the aquatic environment, J. Pharm. Pharmacol. 37 (1985), pp. 1–12.
  • A.K. da Silva, M.J.M. Wells, A.N. Morse, M.-L. Pellegrin, S.M. Miller, J. Peccia, and L.C. Sima, Emerging pollutants – Part I: Occurrence, fate and transport, Water Environ. Res. 84 (2012), pp. 1878–1908.
  • A.K. da Silva, J. Amador, C. Cherchi, S.M. Miller, A.N. Morse, M.-L. Pellegrin, and M.J. Wells, Emerging pollutants – Part I: Occurrence, fate and transport, Water Environ. Res. 85 (2013), pp. 1978–2021.
  • S.R. Hughes, P. Kay, and L.E. Brown, Global Synthesis and critical evaluation of pharmaceutical data sets collected from river systems, Environ. Sci. Technol. 47 (2013), pp. 661–677.
  • K. Kümmerer, Pharmaceuticals in the Environment: Sources, Fate, Effects and Risks, Springer Science & Business Media, Berlin, 2013.
  • C.G. Daughton and T.A. Ternes, Pharmaceuticals and personal care products in the environment: Agents of subtle change?, Environ. Health Perspect. 107 (1999), pp. 907–938.
  • V. Matamoros and J. Bayona, Elimination of pharmaceuticals and personal care products in subsurface flow constructed wetlands, Environ. Sci. Technol. 40 (2006), pp. 5811–5816.
  • J.M. Brausch and G.M. Rand, A review of personal care products in the aquatic environment: Environmental concentrations and toxicity, Chemosphere 82 (2011), pp. 1518–1532.
  • Q. Bu, B. Wang, J. Huang, S. Deng, and G. Yu, Pharmaceuticals and personal care products in the aquatic environment in China: A review, J. Hazard. Mater. 262 (2013), pp. 189–211.
  • S. Ortiz de García, G. Pinto Pinto, P. García Encina, and R. Irusta Mata, Consumption and occurrence of pharmaceutical and personal care products in the aquatic environment in Spain, Sci. Total Environ. 444 (2013), pp. 451–465.
  • G.H. Han, H.G. Hur, and S.D. Kim, Ecotoxicological risk of pharmaceuticals from wastewater treatment plants in Korea: Occurrence and toxicity to Daphnia magna, Environ. Toxicol. Chem. 25 (2006), pp. 265–271.
  • S. Castiglioni, R. Bagnati, R. Fanelli, F. Pomati, D. Calamari, and E. Zuccato, Removal of pharmaceuticals in sewage treatment plants in Italy, Environ. Sci. Technol. 40 (2006), pp. 357–363.
  • L. Cizmas, V.K. Sharma, C.M. Gray, and T.J. McDonald, Pharmaceuticals and personal care products in waters: Occurrence, toxicity, and risk, Environ. Chem. Lett. 13 (2015), pp. 381–394.
  • J.M. Brausch, K.A. Connors, B.W. Brooks, and G.M. Rand, Human pharmaceuticals in the aquatic environment: A review of recent toxicological studies and considerations for toxicity testing, in Reviews of Environmental Contamination and Toxicology, Vol. 218, D.M. Whitacre, ed., Springer, New York, NY, 2012, pp. 1–99.
  • C. Schmitt, M. Oetken, O. Dittberner, M. Wagner, and J. Oehlmann, Endocrine modulation and toxic effects of two commonly used UV screens on the aquatic invertebrates Potamopyrgus antipodarum and Lumbriculus variegatus, Environ. Pollut. 152 (2008), pp. 322–329.
  • Directive 2004/27/EC of the European Parliament and of the Council of 31 March 2004 amending Directive 2001/83/EC on the Community code relating to medicinal products for human use. Official Journal L 136, 30/04/2004 pp. 34-57. 2004.
  • Directive 2004/28/EC of the European Parliament and of the Council of 31 March 2004 amending Directive 2001/82/EC on the Community code relating to veterinary medicinal products. Official Journal L 136, 30/04/2004 pp. 58-84. 2004.
  • REGULATION (EC) No 1223/2009 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 30 November 2009 on cosmetic products. 2009.
  • European Parliament and Council, Regulation (EC) no 1907/2006 on Registration, Evaluation, Authorization and restriction of Chemicals (REACH). 2006, p. 2006.
  • A. Sobek, S. Bejgarn, C. Rudén, L. Molander, and M. Breitholtz, In the shadow of the Cosmetic Directive — Inconsistencies in EU environmental hazard classification requirements for UV-filters, Sci. Total Environ. 461–462 (2013), pp. 706–711.
  • DIRECTIVE 2013/39/EU OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 12 August 2013 amending Directives 2000/60/EC and 2008/105/EC as regards priority substances in the field of water policy. 2013.
  • COMMISSION IMPLEMENTING DECISION (EU) 2015/495 of 20 March 2015 establishing a watch list of substances for Union-wide monitoring in the field of water policy pursuant to Directive 2008/105/EC of the European Parliament and of the Council. 2015.
  • M.O. Barbosa, N.F.F. Moreira, A.R. Ribeiro, M.F.R. Pereira, and A.M.T. Silva, Occurrence and removal of organic micropollutants: An overview of the watch list of EU Decision 2015/495, Water Res. 94 (2016), pp. 257–279.
  • P. Gramatica, S. Cassani, and A. Sangion, PBT assessment and prioritization by PBT Index and consensus modeling: Comparison of screening results from structural models, Environ. Int. 77 (2015), pp. 25–34.
  • S. Cassani and P. Gramatica, Identification of potential PBT behavior of personal care products by structural approaches, Sustain. Chem. Pharm. 1 (2015), pp. 19–27.
  • A. Sangion and P. Gramatica, PBT assessment and prioritization of contaminants of emerging concern: Pharmaceuticals, Environ. Res. 147 (2016), pp. 297–306.
  • P. Gramatica, Prioritization of Chemicals Based on Chemoinformatic Analysis, in Handbook of Computational Chemistry, J. Leszczynski, ed., Springer, Dordrecht, 2016, pp. 1–33.
  • K. Roy, S. Kar, and R.N. Das, Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment, Academic Press, New York, NY, 2015.
  • P. Gramatica, S. Cassani, and A. Sangion, Aquatic ecotoxicity of personal care products: QSAR models and ranking for prioritization and safer alternatives’ design, Green Chem. 18 (2016), pp. 4393–4406.
  • A. Sangion and P. Gramatica, Hazard of pharmaceuticals for aquatic environment: Prioritization by structural approaches and prediction of ecotoxicity, Environ. Int. 2016, in press doi: 10.1016/j.envint.2016.08.008.
  • M.T.D. Cronin and J.C. Dearden, QSAR in toxicology. 2. Prediction of acute mammalian toxicity and interspecies correlations, Quant. Struct.-Act. Relatsh. 14 (1995), pp. 117–120.
  • J. Devillers and H. Devillers, Prediction of acute mammalian toxicity from QSARs and interspecies correlations, SAR QSAR Environ. Res. 20 (2009), pp. 467–500.
  • I. Kahn, U. Maran, E. Benfenati, T. Netzeva, T. Schultz, and M. Cronin, Comparative quantitative structure-activity-activity relationships for toxicity to Tetrahymena pyriformis and Pimephales promelas, Altern. Lab. Anim. ATLA 35 (2007), pp. 15–24.
  • N. Basant, S. Gupta, and K.P. Singh, Predicting the acute neurotoxicity of diverse organic solvents using probabilistic neural networks based QSTR modeling approaches, NeuroToxicology 53 (2016), pp. 45–52.
  • Y. Zhao, L. Wang, H. Gao, and Z. Zhang, Quantitative structure-activity relationships—Relationship between toxicity of organic chemicals to fish and to photobacterium phosphoreum, Chemosphere 26 (1993), pp. 1971–1979.
  • S. Kar and K. Roy, First report on interspecies quantitative correlation of ecotoxicity of pharmaceuticals, Chemosphere 81 (2010), pp. 738–747.
  • X. Zhang, W. Qin, J. He, Y. Wen, L. Su, L. Sheng, and Y. Zhao, Discrimination of excess toxicity from narcotic effect: Comparison of toxicity of class-based organic chemicals to Daphnia magna and Tetrahymena pyriformis, Chemosphere 93 (2013), pp. 397–407.
  • S. Cassani, S. Kovarich, E. Papa, P.P. Roy, L. van der Wal, and P. Gramatica, Daphnia and fish toxicity of (benzo)triazoles: Validated QSAR models, and interspecies quantitative activity-activity modelling, J. Haz. Mat. 258–259 (2013), pp. 50–60.
  • S.D. Dimitrov, O.G. Mekenyan, G.D. Sinks, and T.W. Schultz, Global modeling of narcotic chemicals: Ciliate and fish toxicity, J. Mol. Struct. THEOCHEM 622 (2003), pp. 63–70.
  • S. Dimitrov, Y. Koleva, T.W. Schultz, J.D. Walker, and O. Mekenyan, Interspecies quantitative structure-activity relationship model for aldehydes: Aquatic toxicity, Environ. Toxicol. Chem. 23 (2004), pp. 463–470.
  • X. Wang, C. Sun, Y. Wang, and L. Wang, Quantitative structure–activity relationships for the inhibition toxicity to root elongation of Cucumis sativus of selected phenols and interspecies correlation with Tetrahymena pyriformis, Chemosphere 46 (2002), pp. 153–161.
  • E. Zvinavashe, T. Du, T. Griff, H.H.J. van den Berg, A.E.M.F. Soffers, J. Vervoort, A. Murk, and I. Rietjens, Quantitative structure-activity relationship modeling of the toxicity of organothiophosphate pesticides to Daphnia magna and Cyprinus carpio, Chemosphere 75 (2009), pp. 1531–1538.
  • S. Gupta, N. Basant, and K.P. Singh, Predicting aquatic toxicities of benzene derivatives in multiple test species using local, global and interspecies QSTR modeling approaches, RSC Adv. 5 (2015), pp. 71153–71163.
  • A. Furuhama, K. Hasunuma, and Y. Aoki, Interspecies quantitative structure–activity–activity relationships (QSAARs) for prediction of acute aquatic toxicity of aromatic amines and phenols, SAR QSAR Environ. Res. 26 (2015), pp. 301–323.
  • S.D. Dyer, D.J. Versteeg, S.E. Belanger, J.G. Chaney, and F.L. Mayer, Interspecies correlation estimates predict protective environmental concentrations, Environ. Sci. Technol. 40 (2006), pp. 3102–3111.
  • Web-based Interspecies Correlation Estimation (Web-ICE) for Acute Toxicity: User Manual. Version 3.3, EPA/600/R-15/192, U. S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division. Gulf Breeze, FL. 2015.
  • M.H. Fatemi, E. Mousa Shahroudi, and Z. Amini, Development of quantitative interspecies toxicity relationship modeling of chemicals to fish, J. Theor. Biol. 380 (2015), pp. 16–23.
  • H. Sanderson and M. Thomsen, Comparative analysis of pharmaceuticals versus industrial chemicals acute aquatic toxicity classification according to the United Nations classification system for chemicals. Assessment of the (Q)SAR predictability of pharmaceuticals acute aquatic toxicity and their predominant acute toxic mode-of-action, Toxicol. Lett. 187 (2009), pp. 84–93.
  • ECOTOX User Guide: ECOTOXicology Database System. Version 4.0 (2015). Available at http://www.epa.gov/ecotox/.
  • OECD, Principles for the validation, for regulatory purposes, of (Quantitative) Structure–Activity Relationship Models, Paris, 2004.
  • OECD, Test No. 202: Daphnia Sp. Acute Immobilisation Test, Organisation for Economic Co-operation and Development, Paris, 2004.
  • OECD, Test No. 203: Fish, Acute Toxicity Test, Organisation for Economic Co-operation and Development, Paris, 1992.
  • Hypercube, Inc., HyperChem ( v. 7.03 for Windows), Geinesville (USA), 2002.
  • C.W. Yap, PaDEL-Descriptor: An open source software to calculate molecular descriptors and fingerprints, J. Comput. Chem. 32 (2011), pp. 1466–1474.
  • P. Gramatica, N. Chirico, E. Papa, S. Cassani, and S. Kovarich, QSARINS: A new software for the development, analysis, and validation of QSAR MLR models, J. Comput. Chem. 34 (2013), pp. 2121–2132.
  • P. Gramatica, S. Cassani, and N. Chirico, QSARINS-Chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS, J. Comput. Chem. 35 (2014), pp. 1036–1044.
  • P. Gramatica and A. Sangion, A historical excursus on the statistical validation parameters for QSAR models: A clarification concerning metrics and terminology, J. Chem. Inf. Model. 56 (2016), pp. 1127–1131.
  • L.M. Shi, H. Fang, W.D. Tong, J. Wu, R. Perkins, R.M. Blair, W.S. Branham, S.L. Dial, C.I. Moland, and D.M. Sheehan, QSAR models using a large diverse set of estrogens, J. Chem. Inf. Comput. Sci. 41 (2001), pp. 186–195.
  • G. Schueuermann, R.-U. Ebert, J. Chen, B. Wang, and R. Kuehne, External validation and prediction employing the predictive squared correlation coefficient - test set activity mean vs training set activity mean, J. Chem. Inf. Model. 48 (2008), pp. 2140–2145.
  • V. Consonni, D. Ballabio, and R. Todeschini, Comments on the definition of the Q(2) parameter for QSAR validation, J. Chem. Inf. Model. 49 (2009), pp. 1669–1678.
  • V. Consonni, D. Ballabio, and R. Todeschini, Evaluation of model predictive ability by external validation techniques, J. Chemom. 24 (2010), pp. 194–201.
  • N. Chirico and P. Gramatica, Real external predictivity of QSAR Models: How to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient, J. Chem. Inf. Model. 51 (2011), pp. 2320–2335.
  • N. Chirico and P. Gramatica, Real external predictivity of QSAR models. Part 2. New inter-comparable thresholds for different validation criteria and the need for scatter plot inspection, J. Chem. Inf. Model. 52 (2012), pp. 2044–2058.
  • L.I.-K. Lin, A concordance correlation coefficient to evaluate reproducibility, Biometrics 45 (1989), pp. 255–268.
  • K. Roy, R.N. Das, P. Ambure, and R.B. Aher, Be aware of error measures. Further studies on validation of predictive QSAR models, Chemom. Intell. Lab. Syst. 152 (2016), pp. 18–33.
  • P. Gramatica, S. Cassani, P.P. Roy, S. Kovarich, C.W. Yap, and E. Papa, QSAR modeling is not ‘Push a button and find a correlation’: A case study of toxicity of (benzo-)triazoles on algae, Mol. Inform. 31 (2012), pp. 817–835.
  • S. Broderius, D. Hammermeister, C. Russom, D. Barnidge, D. Brooke, G. Elonen, M. Hoglund, M. Kahl, G. Mielke, and J. Tho, Toxicity of eight terpenes to fathead minnows (Pimephales promelas), daphnids (Daphnia magna), and Algae (Selanastrum capricornutum), ASCI Corp. USEPA Environ. Res. Lab.-Duluth 57 (1990).
  • D. Geiger, L. Brooke, and D. Call, Acute Toxicities of Organic Chemicals to Fathead Minnows (Pimephales promelas), Vol. V, Cent. Lake Super. Environ. Stud. Univ. Wis, Super, 1990.
  • M. Fingas, D. Kyle, N. Laroche, B. Fieldhouse, G. Sergy, and G. Stoodley, The Effectiveness testing of oil spill-treating agents, in The Use of Chemicals in Oil Spill Response, P. Lane, ed., ASTM International, West Conshohocken, PA, 1995, pp. 286–286.
  • National Association of Photographic Manufacturers, Environmental Effect of Photoprocessing Chemicals Vol I and II, EPA/OTS Doc. #40-8469216, 1974, pp. 536.
  • T.L. Randall and P.V. Knopp, Detoxification of specific organic substances by wet oxidation, J. Water Pollut. Control Fed. 52 (1980), pp. 2117–2130.
  • M.E. Bender, The toxicity of the hydrolysis and breakdown products of malathion to the fathead minnow (Pimephales Promelas, Rafinesque), Water Res. 3 (1969), pp. 571–582.
  • R. Todeschini and V. Consonni, Handbook of Molecular Descriptors, John Wiley & Sons, New York, NY, 2008.

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