Advertisement

Development of Baseline Quantitative Structure-Activity Relationships (QSARs) for the Effects of Active Pharmaceutical Ingredients (APIs) to Aquatic Species

  • David J. Ebbrell
  • Mark T. D. Cronin
  • Claire M. Ellison
  • James W. Firman
  • Judith C. MaddenEmail author
Protocol
Part of the Methods in Pharmacology and Toxicology book series (MIPT)

Abstract

The aim of this work was to develop predictive approaches for acute and chronic toxicity in fish, Daphnia, and algae utilizing baseline toxicity models. Currently available public active pharmaceutical ingredient (API) ecotoxicity data were compared to published baseline toxicity QSARs and classification schemes for industrial chemicals. The results showed that methods of assessing ecotoxicity for industrial chemicals are not adequate for the assessment of APIs. To develop equivalent prediction methods for APIs, acute baseline toxicity QSARs for APIs based on hydrophobicity (as log P) were constructed, and the lower limits of toxicity for the public API data were compared with published industrial baseline toxicity QSARs for fish, Daphnia, and algae. These baseline toxicity QSARs were subsequently compared to the available acute toxicity data from the iPiE database. Since 75% of APIs are ionizable, baseline toxicity QSARs were also constructed using log D at pH 7.0. For chronic toxicity baselines, uncensored NOEC and LOEC data from the iPiE database were plotted using either log P or log D at pH 7.0. An alternative methodology was used to develop chronic baseline toxicity QSARs which consisted of iteratively refining the line of best fit until approximately 90% of the values were above the baseline toxicity QSARs. These chronic baseline toxicity QSARs could subsequently be used to identify groups which exhibit toxicity in excess of the baseline (i.e., greater than 10× the hydrophobicity-predicted toxicity).

Key words

NOEC LOEC QSAR Environmental Risk Assessment Aquatic toxicity Baseline toxicity Excess toxicity 

Notes

Acknowledgments

The financial contribution of the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in-kind contribution through the European Union Innovative Medicines Initiative (IMI) iPiE Project (Grant Agreement no. 115735) is gratefully acknowledged.

References

  1. 1.
    European Medicines Agency (EMEA, 2006): Guideline on the environmental risk assessment of medicinal products for human use. Doc. Ref. EMEA/CHMP/SWP/4447/00 corr 2Google Scholar
  2. 2.
    OECD (2018) Test no. 201: freshwater alga and cyanobacteria, growth inhibition test. Available online at http://www.oecd-ilibrary.org/environment/test-no-201-alga-growth-inhibition-test_9789264069923-en;jsessionid=3he2xatcu4u0i.x-oecd-live-03
  3. 3.
    OECD (2004) Test No. 202: Daphnia sp. Acute immobilisation test. Available online at http://www.oecd-ilibrary.org/environment/test-no-202-daphnia-sp-acute-immobilisation-test_9789264069947-en. Accessed 17 Oct 2017
  4. 4.
    OECD (1992) Test No. 203: fish, acute toxicity test. Available online at http://www.oecd-ilibrary.org/environment/test-no-203-fish-acute-toxicity-test_9789264069961-en. Accessed 17 Oct 2017
  5. 5.
    OECD (2018) Test no. 210: fish, early-life stage toxicity test, growth inhibition test. Available online at http://www.oecd-ilibrary.org/environment/test-no-210-fish-early-life-stage-toxicity-test_9789264203785-en;jsessionid=3he2xatcu4u0i.x-oecd-live-03
  6. 6.
  7. 7.
    Vestel J, Caldwell DJ, Constantine L, D’Arco VJ, Davidson T, Dolan DG et al (2016) Use of acute and chronic ectoxicity data in environmental risk assessment of pharmaceuticals. Environ Toxicol Chem 35:1201–1212CrossRefGoogle Scholar
  8. 8.
    ECETOC Technical Report No. 120: activity-based relationships for aquatic ecotoxicology data: use of the activity approach to strengthen MoA predictions (2013)Google Scholar
  9. 9.
    Crane M, Watts C, Boucard T (2006) Chronic aquatic environmental risks from exposure to human pharmaceuticals. Sci Total Environ 367:23–41CrossRefGoogle Scholar
  10. 10.
    Cronin MTD, Dearden JC, Dobbs AJ (1991) QSAR studies of comparative toxicity in aquatic organisms. Sci Total Environ 109:431–439CrossRefGoogle Scholar
  11. 11.
    Könemann H (1981) Quantitative structure-activity-relationships in fish toxicity studies. 1. Relationship for 50 industrial pollutants. Toxicology 19:209–221CrossRefGoogle Scholar
  12. 12.
    Russom CL, Bradbury SP, Broderius SJ, Hammermeister DE, Drummond RA (1997) Predicting modes of toxic action from chemical structure: acute toxicity in the fathead minnow (Pimephales promelas). Environ Toxicol Chem 16:948–967CrossRefGoogle Scholar
  13. 13.
    Austin T, Denoyelle M, Chaudry A, Stradling S, Eadsforth C (2015) European chemicals agency dossier submissions as an experimental data source: refinement of a fish toxicity model for predicting acute LC50 values. Environ Toxicol Chem 34:369–378CrossRefGoogle Scholar
  14. 14.
    Webb SF (2004) A data-based perspective on the environmental risk assessment of human pharmaceuticals I - collation of available ecotoxicity data. In: Kummerer K (ed) Pharmaceuticals in the environment: Sources, fate, effects and risks, 2nd edn. Springer, Berlin, pp 317–342CrossRefGoogle Scholar
  15. 15.
    Kar S, Roy K (2010) First report on interspecies quantitative correlation of ecotoxicity of pharmaceuticals. Chemosphere 81:738–747CrossRefGoogle Scholar
  16. 16.
    Tugcu G, Turker Sacan M, Vracko M, Novic M, Minovski N (2012) QSTR modelling of the acute toxicity of pharmaceuticals to fish. SAR QSAR Environ Res 23:297–310CrossRefGoogle Scholar
  17. 17.
    Sanderson H, Thomsen M (2007) Ecotoxicological quantitative structure-activity relationships for pharmaceuticals. Bull Environ Contam Toxicol 79:331–335CrossRefGoogle Scholar
  18. 18.
    Escher BI, Baumgartner R, Koller M, Treyer K, Lienert J, McArdell CS (2011) Environmental toxicology and risk assessment of pharmaceuticals from hospital wastewater. Water Res 45:75–92CrossRefGoogle Scholar
  19. 19.
    Escher BI, Bramaz N, Mueller JF, Quayle P, Rutishauser S, Vermeirssen ELM (2008) Toxic equivalent concentrations (TEQs) for baseline toxicity and specific modes of action as a tool to improve interpretation of ectoxicity testing of environmental samples. J Environ Monit 10:612–621CrossRefGoogle Scholar
  20. 20.
    Escher BI, Eggen RIL, Schreiber U, Schreiber Z, Vye E, Wisner B et al (2002) Baseline toxicity (narcosis) of organic chemicals determined by in vitro membrane potential measurements in energy-transducing membranes. Environ Sci Technol 36:1971–1979CrossRefGoogle Scholar
  21. 21.
    Escher BI, Hermens JLM (2002) Modes of action in ecotoxicology: their role in body burdens, species sensitivity, QSARs, and mixture effects. Environ Sci Technol 36(20):4201–4217CrossRefGoogle Scholar
  22. 22.
    Verhaar HJM, van Leeuwen CJ, Hermens JLM (1992) Classifying environmental-pollutants. 1. Structure-activity-relationships for prediction of aquatic toxicity. Chemosphere 25:471–491CrossRefGoogle Scholar
  23. 23.
    Thomas P, Dawick J, Lampi M, Lemaire P, Presow S, van Egmond R et al (2015) Application of the activity framework for assessing aquatic ecotoxicology data for organic chemicals. Environ Sci Technol 49:12289–12296CrossRefGoogle Scholar
  24. 24.
    Ellison CM, Madden JC, Cronin MTD, Enoch SJ (2015) Investigation of the Verhaar scheme for predicting acute aquatic toxicity: improving predictions obtained from Toxtree ver. 2.6. Chemosphere 139:146–154CrossRefGoogle Scholar
  25. 25.
    Ellison CM, Piechota P, Madden JC, Enoch SJ, Cronin MT (2016) Adverse outcome pathway (AOP) informed modeling of aquatic toxicology: QSARs, read-across, and interspecies verification of modes of action. Environ Sci Technol 50:3995–4007CrossRefGoogle Scholar
  26. 26.
    Enoch SJ, Hewitt M, Cronin MTD, Azam S, Madden JC (2008) Classification of chemicals according to mechanism of aquatic toxicity: an evaluation of the implementation of the Verhaar scheme in Toxtree. Chemosphere 73:243–248CrossRefGoogle Scholar
  27. 27.
    ECETOC Technical Report No. 102: Intelligent testing strategies in ecotoxicology: mode of action approach for specifically acting chemicals (2007)Google Scholar
  28. 28.
    He J, Fu L, Wang Y, Li JJ, Wang XH, Su LM et al (2014) Investigation on baseline toxicity to rats based on aliphatic compounds and comparison with toxicity to fish: effect of exposure routes on toxicity. Regul Toxicol Pharmacol 70:98–106CrossRefGoogle Scholar
  29. 29.
    Su LM, Liu X, Wang Y, Li JJ, Wang XH, Sheng LX et al (2014) The discrimination of excess toxicity from baseline effect: effect of bioconcentration. Sci Total Environ 484:137–145CrossRefGoogle Scholar
  30. 30.
    Sanderson H, Thomsen M (2009) 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 187:84–93CrossRefGoogle Scholar
  31. 31.
    Brausch JM, Connors KA, Brooks BW, Rand GM (2012) Human pharmaceuticals in the aquatic environment: a review of recent toxicological studies and considerations for toxicity testing. In: Whitacre DM (ed) Reviews of environmental contamination and toxicology 218. Springer, pp 1–99Google Scholar
  32. 32.
    Hrovat M, Segner H, Jeram S (2009) Variability of in vivo fish acute toxicity data. Regulat Toxicolol Pharmacol 54:294–300CrossRefGoogle Scholar
  33. 33.
    ACD/Structure Elucidator, version 15.01, Advanced Chemistry Development, Inc., Toronto, ON, Canada, www.acdlabs.com (2015)
  34. 34.
    Hsieh SH, Hsu CH, Tsai DY, Chen CY (2006) Quantitative structure-activity relationships (QSAR) for toxicity of nonpolar narcotic chemicals to Pseudokirchneriella subcapitata. Environ Toxicol Chem 25:2920–2926CrossRefGoogle Scholar
  35. 35.
    Tsai KP, Chen CY (2007) An algal toxicity database of organic toxicants derived by a closed-system technique. Environ Toxicol Chem 26:1931–1939CrossRefGoogle Scholar
  36. 36.
    Zhang X, Qin W, He J, Wen Y, Su L, Sheng L et al (2013) Discrimination of excess toxicity from narcotic effect: comparison of toxicity of class-based organic chemicals to Daphnia magna and Tetrahymena pyriformis. Chemosphere 93:397–407CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  • David J. Ebbrell
    • 1
  • Mark T. D. Cronin
    • 1
  • Claire M. Ellison
    • 1
  • James W. Firman
    • 1
  • Judith C. Madden
    • 1
    Email author
  1. 1.School of Pharmacy and Biomolecular SciencesLiverpool John Moores UniversityLiverpoolUK

Personalised recommendations