Advertisement

pp 1-30 | Cite as

In Vitro-In Vivo Extrapolation to Predict Bioaccumulation and Toxicity of Chemicals in Fish Using Physiologically Based Toxicokinetic Models

  • Julita Stadnicka-MichalakEmail author
  • Kristin Schirmer
Protocol
Part of the Methods in Pharmacology and Toxicology book series

Abstract

Out of the >107 million chemicals already registered with the Chemical Abstracts Services, less than 0.5% are being regulated, and even fewer are evaluated for their safety. Consequently, a new paradigm in risk assessment is urgently needed. It should encompass faster and less costly methods and reduce the number of animals needed for testing. One proposal is to combine computational modeling with small-scale bioassay methods. This chapter describes the methods that link in vitro bioassays using fish cells with physiologically based toxicokinetic (PBTK) modeling in order to predict the acute toxicity, bioaccumulation, and impact of chemicals on fish growth. The main focus is on PBTK modeling; thus all the model equations and parameters available for eight fish species as well as suggestions for possible software implementation will be provided. The PBTK model described here can account for respiratory and dietary uptake routes and for chemical biotransformation processes.

Keywords

PBTK model Fish growth Lethality Integrated testing design Predictive modeling Chemical risk assessment Fish cell lines Toxicokinetics and toxicodynamics 

Notes

Acknowledgments

Two ongoing research projects informed about several details that are presented in this chapter. These projects are the ECO34 project funded by the CEFIC-LRI, “A tiered testing strategy for rapid estimation of bioaccumulation by a combined modeling—in vitro testing approach” (PI: Prof. Kristin Schirmer), and the project funded by the 3R Swiss Foundation, “Combining computational modelling with in vitro cellular responses in order to predict chemical impact on fish growth” (PI: Prof. Kristin Schirmer).

References

  1. 1.
    European_Commission (2010) European Commission. Sixth report on the statistics on the number of animals used for experimental and other scientific purposes in the member states of the European Union COM 511. http://eur-lex.europa.eu/resource.html?uri=cellar:e76f9589-b5ae-4a05-8cd9-edda3a843bb5.0001.01/DOC_1&format=PDF
  2. 2.
    European_Commission (2013) European Commission. Seventh report on the statistics on the number of animals used for experimental and other scientific purposes in the member states of the European Union. http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52013DC0859&from=EN
  3. 3.
    Scholz S, Sela E, Blaha L, Braunbeck T, Galay-Burgos M, García-Franco M, Guinea J, Klüver N, Schirmer K, Tanneberger K, Tobor-Kapłon M, Witters H, Belanger S, Benfenati E, Creton S, Cronin MTD, Eggen RIL, Embry M, Ekman D, Gourmelon A, Halder M, Hardy B, Hartung T, Hubesch B, Jungmann D, Lampi MA, Lee L, Léonard M, Küster E, Lillicrap A, Luckenbach T, Murk AJ, Navas JM, Peijnenburg W, Repetto G, Salinas E, Schüürmann G, Spielmann H, Tollefsen KE, Walter-Rohde S, Whale G, Wheeler JR, Winter MJ (2013) A European perspective on alternatives to animal testing for environmental hazard identification and risk assessment. Regul Toxicol Pharmacol 67(3):506–530Google Scholar
  4. 4.
    CAS (2014) Chemical abstract services databases. http://www.casorg/content/cas-databases
  5. 5.
    van Leeuwen CJ (2007) General introduction. In: van Leeuwen CJ, Vermeire TG (eds) Risk assessment of chemicals. Springer, Dordrecht, p 686Google Scholar
  6. 6.
    Stadnicka-Michalak J, Schirmer K, Ashauer R (2015) Toxicology across scales: cell population growth in vitro predicts reduced fish growth. Sci Adv 1(7):e1500302Google Scholar
  7. 7.
    Kirla KT, Groh KJ, Steuer AE, Poetzsch M, Banote RK, Stadnicka-Michalak J, Eggen RIL, Schirmer K, Kraemer T (2016) From the cover: Zebrafish larvae are insensitive to stimulation by cocaine: importance of exposure route and toxicokinetics. Toxicol Sci 154(1):183–193.  https://doi.org/10.1093/toxsci/kfw156CrossRefGoogle Scholar
  8. 8.
    Nichols JW, Fitzsimmons PN, Whiteman FW, Dawson TD, Babeu L, Juenemann J (2004) A physiologically based toxicokinetic model for dietary uptake of hydrophobic organic compounds by fish. I. Feeding studies with 2,2′,5,5′-tetrachlorobiphenyl. Toxicol Sci 77:206–218Google Scholar
  9. 9.
    Poet TS, Kousba AA, Dennison SL, Timchalk C (2004) Physiologically based pharmacokinetic/pharmacodynamic model for the organophosphorus pesticide diazinon. Neurotoxicology 25(6):1013–1030.  https://doi.org/10.1016/j.neuro.2004.03.002CrossRefGoogle Scholar
  10. 10.
    Brinkmann M, Schlechtriem C, Reininghaus M, Eichbaum K, Buchinger S, Reifferscheid G, Hollert H, Preuss TG (2016) Cross-species extrapolation of uptake and disposition of neutral organic chemicals in fish using a multispecies physiologically-based toxicokinetic model framework. Environ Sci Tech 50(4):1914–1923.  https://doi.org/10.1021/acs.est.5b06158CrossRefGoogle Scholar
  11. 11.
    Nichols JW, Fitzsimmons PN, Whiteman FW, Kuehl DW, Butterworth BC, Jenson CT (2001) Dietary uptake kinetics of 2,2′, 5,5′-tetrachlorobiphenyl in rainbow trout, vol 29. American Society for Pharmacology and Experimental Therapeutics, Bethesda, MD, ETATS-UNISGoogle Scholar
  12. 12.
    Nichols JW, McKim JM, Andersen ME, Gargas ML, Ckewell HJ, Erickson RJ (1990) A physiologically based toxicokinetic model for the uptake and disposition of waterborne organic chemicals in fish. Toxicol Appl Pharmacol 106:433–447Google Scholar
  13. 13.
    Nichols JW, McKim JM, Lien GJ, Hoffman AD, Bertelsen SL, Elonen CM (1996) A physiologically based toxicokinetic model for dermal absorption of organic chemicals by fish. Fundam Appl Toxicol 31:229–242Google Scholar
  14. 14.
    Nichols JW, Huggett DB, Arnot JA, Fitzsimmons PN, Cowan-Ellsberry CE (2013) Toward improved models for predicting bioconcentration of well-metabolized compounds by rainbow trout using measured rates of in vitro intrinsic clearance. Environ Toxicol Chem 32(7):1611–1622.  https://doi.org/10.1002/etc.2219CrossRefGoogle Scholar
  15. 15.
    OECD (2012) OECD fish toxicity testing framework. Series on testing and assessment. http://search.oecd.org/officialdocuments/displaydocumentpdf/?cote=ENV/JM/MONO%282012%2916&doclanguage=en
  16. 16.
    Bols NC, Dayeh VR, Lee LEJ, Schirmer K (2005) Use of fish cell lines in the toxicology and ecotoxicology of fish. In: Mohn TW, Mommsen TP (eds) Biochemistry and molecular biology of fishes. Elsevier Science, Amsterdam, p 6Google Scholar
  17. 17.
    Segner H (1998) Fish cell lines as a tool in aquatic toxicology. In: Braunbeck T, Hinton DE, Streit B (eds) Fish ecotoxicology. Birkhäuser, Basel, pp 1–38Google Scholar
  18. 18.
    Bols NC, Dayeh VR, Lee LEJ, Schirmer K (2005) Chapter 2 use of fish cell lines in the toxicology and ecotoxicology of fish. Piscine cell lines in environmental toxicology. In: Mommsen TP, Moon TW (eds) Biochemistry and molecular biology of fishes, vol 6. Elsevier, Amsterdam, pp 43–84Google Scholar
  19. 19.
    Castano A, Bols NC, Braunbeck T, Dierickx P, Halder M, Isomaa B, Kawahara K, Lee LEJ, Mothersill C, Pärt P, Repetto G, Sintes JR, Rufli H, Smith R, Wood C, Segner H (2003) The use of fish cells in ecotoxicology. The report and recommendations of ECVAM workshop 47. Altern Lab Anim 31:317–351Google Scholar
  20. 20.
    Nichols JW, McKim JM, Lien GJ, Hoffman AD, Bertelsen SL (1991) Physiologically based toxicokinetic modeling of three waterborne chloroethanes in rainbow trout (Oncorhynchus). Toxicol Appl Pharmacol 110:374–389Google Scholar
  21. 21.
    Bertelsen SL, Hoffman AD, Gallinat CA, Elonen CM, Nichols JW (1998) Evaluation of Log Kow and tissue lipid content as predictors of chemical partitioning to fish tissues. Environ Toxicol Chem 17(8):1477–1455Google Scholar
  22. 22.
    Arnot JA, Gobas F (2004) A food web bioaccumulation model for organic chemicals in aquatic ecosystems. Environ Toxicol Chem 23(10):2343–2355Google Scholar
  23. 23.
    Nichols JW, Fitzsimmons PN, Burkhard LP (2007) In vitro–in vivo extrapolation of quantitative hepatic biotransformation data for fish. II. Modeled effects on chemical bioaccumulation. Environ Toxicol Chem 26(6):1304–1319Google Scholar
  24. 24.
    Stadnicka J, Schirmer K, Ashauer R (2012) Predicting concentrations of organic chemicals in fish by using toxicokinetic models. Environ Sci Technol 46(6):3273–3280.  https://doi.org/10.1021/es2043728CrossRefGoogle Scholar
  25. 25.
    Jones HM, Gardner IB, Watson KJ (2009) Modelling and PBPK simulation in drug discovery. AAPS J 11(1):155–166.  https://doi.org/10.1208/s12248-009-9088-1CrossRefGoogle Scholar
  26. 26.
    Haddad S, Pelekis M, Krishnan K (1996) A methodology for solving physiologically based pharmacokinetic models without the use of simulation softwares. Toxicol Lett 85(2):113–126.  https://doi.org/10.1016/0378-4274(96)03648-XCrossRefGoogle Scholar
  27. 27.
    Krishnan K, Peyret T (2009) Physiologically based toxicokinetic (PBTK) modeling in ecotoxicology. In: Devillers J (ed) Ecotoxicology modeling. Springer, Boston, pp 145–175.  https://doi.org/10.1007/978-1-4419-0197-2_6CrossRefGoogle Scholar
  28. 28.
    Soderberg RW (1994) Flowing water fish culture. Lewis, Boca Raton, p 147Google Scholar
  29. 29.
    Erickson RJ, McKim JM (1990) A model for exchange of organic chemicals at fish gills: flow and diffusion limitations. Aquat Toxicol 18(4):175–197Google Scholar
  30. 30.
    Lepak JM, Hooten MB, Johnson BM (2012) The influence of external subsidies on diet, growth and Hg concentrations of freshwater sport fish: implications for management and fish consumption advisories. Ecotoxicology 21(7):1878–1888Google Scholar
  31. 31.
    Lien GJ, McKim JM, Hoffman AD, Jenson CT (2001) A physiologically based toxicokinetic model for lake trout (Salvelinus namaycush). Aquat Toxicol 51(3):335–350Google Scholar
  32. 32.
    Yang F, Sun N, Sun YX, Shan Q, Zhao HY, Zeng DP, Zeng ZL (2013) A physiologically based pharmacokinetics model for florfenicol in crucian carp and oral-to-intramuscular extrapolation. J Vet Pharmacol Ther 36(2):192–200.  https://doi.org/10.1111/j.1365-2885.2012.01419.xCrossRefGoogle Scholar
  33. 33.
    Nichols JW, McKim JM, Lien GJ, Hoffman AD, Bertelsen SL, Gallinat CA (1993) Physiologically-based toxicokinetic modeling of three waterborne chloroethanes in channel catfish, Ictalurus punctatus. Aquat Toxicol 27:83–112Google Scholar
  34. 34.
    Lien GJ, Nichols JW, McKim JM, Gallinat CA (1994) Modeling the accumulation of three waterborne chlorinated ethanes in fathead minnows (Pimephales promelas): a physiologically based approach. Environ Toxicol Chem 13(7):1195–1205Google Scholar
  35. 35.
    Brinkmann M, Freese M, Pohlmann JD, Kammann U, Preuss TG, Buchinger S, Reifferscheid G, Beiermeister A, Hanel R, Hollert H (2015) A physiologically based toxicokinetic (PBTK) model for moderately hydrophobic organic chemicals in the European eel (Anguilla anguilla). Sci Total Environ 536:279–287.  https://doi.org/10.1016/j.scitotenv.2015.07.046CrossRefGoogle Scholar
  36. 36.
    Fitzsimmons PN, Fernandez JD, Hoffman AD, Butterworth BC, Nichols JW (2001) Branchial elimination of superhydrophobic organic compounds by rainbow trout (Oncorhynchus mykiss). Aquat Toxicol 55(1):23–34.  https://doi.org/10.1016/S0166-445X(01)00174-6CrossRefGoogle Scholar
  37. 37.
    deBruyn AMH, Gobas FAPC (2007) The sorptive capacity of animal protein. Environ Toxicol Chem 26(9):1803–1808.  https://doi.org/10.1897/07-016r.1CrossRefGoogle Scholar
  38. 38.
    Stadnicka-Michalak J, Weiss FT, Fischer M, Tanneberger K, Schirmer K (2018) Biotransformation of benzo[a]pyrene by three rainbow trout (Onchorhynchus mykiss) cell lines and extrapolation to derive a fish bioconcentration factor. Environ Sci Technol 52(5):3091–3100Google Scholar
  39. 39.
    Han X, Nabb DL, Mingoia RT, Yang CH (2007) Determination of xenobiotic intrinsic clearance in freshly isolated hepatocytes from rainbow trout (Oncorhynchus mykiss) and rat and its application in bioaccumulation assessment. Environ Sci Tech 41(9):3269–3276.  https://doi.org/10.1021/es0626279CrossRefGoogle Scholar
  40. 40.
    Austin RP, Barton P, Cockroft SL, Wenlock MC, Riley RJ (2002) The influence of nonspecific microsomal binding on apparent intrinsic clearance, and its prediction from physicochemical properties. Drug Metab Dispos 30(12):1497–1503.  https://doi.org/10.1124/dmd.30.12.1497CrossRefGoogle Scholar
  41. 41.
    Escher BI, Cowan-Ellsberry CE, Dyer S, Embry MR, Erhardt S, Halder M, Kwon JH, Johanning K, Oosterwijk MTT, Rutishauser S, Segner H, Nichols J (2011) Protein and lipid binding parameters in rainbow trout (Oncorhynchus mykiss) blood and liver fractions to extrapolate from an in vitro metabolic degradation assay to in vivo bioaccumulation potential of hydrophobic organic chemicals. Chem Res Toxicol 24(7):1134–1143.  https://doi.org/10.1021/tx200114yCrossRefGoogle Scholar
  42. 42.
    Nichols JW, Hoffman AD, ter Laak TL, Fitzsimmons PN (2013) Hepatic clearance of 6 polycyclic aromatic hydrocarbons by isolated perfused trout livers: prediction from in vitro clearance by liver S9 fractions. Toxicol Sci 136(2):359–372.  https://doi.org/10.1093/toxsci/kft219CrossRefGoogle Scholar
  43. 43.
    Cowan-Ellsberry CE, Dyer SD, Erhardt S, Bernhard MJ, Roe AL, Dowty ME, Weisbrod AV (2008) Approach for extrapolating in vitro metabolism data to refine bioconcentration factor estimates. Chemosphere 70(10):1804–1817Google Scholar
  44. 44.
    Laue H, Gfeller H, Jenner KJ, Nichols JW, Kern S, Natsch A (2014) Predicting the bioconcentration of fragrance ingredients by rainbow trout using measured rates of in vitro intrinsic clearance. Environ Sci Tech 48(16):9486–9495.  https://doi.org/10.1021/es500904hCrossRefGoogle Scholar
  45. 45.
    Nichols J, Erhardt S, Dyer S, James M, Moore M, Plotzke K, Segner H, Schultz I, Thomas K, Vasiluk L, Weisbrod A (2007) Use of in vitro absorption, distribution, metabolism, and excretion (ADME) data in bioaccumulation assessments for fish. Hum Ecol Risk Assess Int J 13(6):1164–1191.  https://doi.org/10.1080/10807030701655897CrossRefGoogle Scholar
  46. 46.
    Tanneberger K, Knöbel M, Busser FJM, Sinnige TL, Hermens JLM, Schirmer K (2013) Predicting fish acute toxicity using a fish gill cell line-based toxicity assay. Environ Sci Technol 47(2):1110–1119.  https://doi.org/10.1021/es303505zCrossRefGoogle Scholar
  47. 47.
    Stadnicka-Michalak J, Tanneberger K, Schirmer K, Ashauer R (2014) Measured and modeled toxicokinetics in cultured fish cells and application to in vitro-in vivo toxicity extrapolation. PLoS One 9(3):e92303Google Scholar
  48. 48.
    Dayeh VR, Bols NC, Tanneberger K, Schirmer K, Lee LEJ (2013) The use of fish-derived cell lines for investigation of environmental contaminants: an update following OECD’s fish toxicity testing framework no. 171. In: Current protocols in toxicology. Wiley, New York.  https://doi.org/10.1002/0471140856.tx0105s56CrossRefGoogle Scholar
  49. 49.
    Schirmer K, Chan GJ, Greenberg BM, Dixon DG, Bols NC (1997) Methodology for demonstrating and measuring the photocytotoxicity of fluoranthene to fish cells in culture. Toxicol In Vitro 11:107–119Google Scholar
  50. 50.
    Dayeh VR, Schirmer K, Lee LEJ, Bols NC (2003) The use of fish-derived cell lines for investigation of environmental contaminants. In: Current protocols in toxicology, vol 1.5.1–1.5.17, Willey, New YorkGoogle Scholar
  51. 51.
    O'Brien J, Wilson I, Orton T, Pognan F (2000) Investigation of the Alamar Blue (resazurin) fluorescent dye for the assessment of mammalian cell cytotoxicity. Eur J Biochem 267(17):5421–5426.  https://doi.org/10.1046/j.1432-1327.2000.01606.xCrossRefGoogle Scholar
  52. 52.
    Borenfreund E, Puerner JA (1985) Toxicity determined in vitro by morphological alterations and neutral red absorption. Toxicol Lett 24(2):119–124.  https://doi.org/10.1016/0378-4274(85)90046-3CrossRefGoogle Scholar
  53. 53.
    Schirmer K, Chan AGJ, Bols NC (2000) Transitory metabolic disruption and cytotoxicity elicited by benzo[a]pyrene in two cell lines from rainbow trout liver. J Biochem Mol Toxicol 14(5):262–276Google Scholar
  54. 54.
    Calabrese EJ (2009) Getting the dose–response wrong: why hormesis became marginalized and the threshold model accepted. Arch Toxicol 83(3):227–247.  https://doi.org/10.1007/s00204-009-0411-5CrossRefGoogle Scholar
  55. 55.
    Calabrese EJ, Baldwin LA (1999) Reevaluation of the fundamental dose-response relationship—a new database suggests that the U-shaped, rather than the sigmoidal, curve predominates. Bioscience 49(9):725–732.  https://doi.org/10.2307/1313596CrossRefGoogle Scholar
  56. 56.
    Fay KA, Mingoia RT, Goeritz I, Nabb DL, Hoffman AD, Ferrell BD, Peterson HM, Nichols JW, Segner H, Han X (2014) Intra- and interlaboratory reliability of a cryopreserved trout hepatocyte assay for the prediction of chemical bioaccumulation potential. Environ Sci Tech 48(14):8170–8178Google Scholar
  57. 57.
    Johanning K, Hancock G, Escher B, Adekola A, Bernhard MJ, Cowan-Ellsberry C, Domoradzki J, Dyer S, Eickhoff C, Embry M, Erhardt S, Fitzsimmons P, Halder M, Hill J, Holden D, Johnson R, Rutishauser S, Segner H, Schultz I, Nichols J (2012) Assessment of metabolic stability using the rainbow trout (Oncorhynchus mykiss) liver S9 fraction. Curr Protoc Toxicol 1(Suppl 53)Google Scholar
  58. 58.
    Fay KA, Nabb DL, Mingoia RT, Bischof I, Nichols JW, Segner H, Johanning K, Han X (2001) Determination of metabolic stability using cryopreserved hepatocytes from rainbow trout (Oncorhynchus mykiss). In: Current protocols in toxicology. Wiley, New York.  https://doi.org/10.1002/0471140856.tx0442s65CrossRefGoogle Scholar
  59. 59.
    Fay KA, Fitzsimmons PN, Hoffman AD, Nichols JW (2017) Comparison of trout hepatocytes and liver S9 fractions as in vitro models for predicting hepatic clearance in fish. Environ Toxicol Chem 36(2):463–471.  https://doi.org/10.1002/etc.3572CrossRefGoogle Scholar
  60. 60.
    Lo JC, Allard GN, Otton SV, Campbell DA, Gobas F (2015) Concentration dependence of biotransformation in fish liver S9: optimizing substrate concentrations to estimate hepatic clearance for bioaccumulation assessment. Environ Toxicol Chem 34(12):2782–2790.  https://doi.org/10.1002/etc.3117CrossRefGoogle Scholar
  61. 61.
    Han X, Nabb DL, Yang C-H, Snajdr SI, Mingoia RT (2009) Liver microsomes and S9 from rainbow trout (Oncorhynchus mykiss): comparison of basal-level enzyme activities with rat and determination of xenobiotic intrinsic clearance in support of bioaccumulation assessment. Environ Toxicol Chem 28(3):481–488.  https://doi.org/10.1897/08-269.1CrossRefGoogle Scholar
  62. 62.
    Kleinow KM, James MO, Tong Z, Venugopalan CS (1998) Bioavailability and biotransformation of benzo(a)pyrene in an isolated perfused in situ catfish intestinal preparation. Environ Health Perspect 106(3):155–166Google Scholar
  63. 63.
    James MO, Tong Z, Rowland-Faux L, Venugopal CS, Kleinow KM (2001) Intestinal bioavailability and biotransformation of 3-hydroxybenzo(a) pyrene in an isolated perfused preparation from channel catfish, Ictalurus punctatus. Drug Metab Dispos 29(5):721–728Google Scholar
  64. 64.
    Barron MG, Schultz IR, Hayton WL (1989) Presystemic branchial metabolism limits DI-2-ethylhexyl phthalate accumulation in fish. Toxicol Appl Pharmacol 98(1):49–57.  https://doi.org/10.1016/0041-008x(89)90133-6CrossRefGoogle Scholar
  65. 65.
    Carlsson C, Part P (2001) 7-ethoxyresorufin O-deethylase induction in rainbow trout gill epithelium cultured on permeable supports: asymmetrical distribution of substrate metabolites. Aquat Toxicol 54(1-2):29–38.  https://doi.org/10.1016/S0166-445x(00)00184-3CrossRefGoogle Scholar
  66. 66.
    Carlsson C, Part P, Brunstrom B (1999) 7-Ethoxyresorufin O-deethylase induction in cultured gill epithelial cells from rainbow trout. Aquat Toxicol 47(2):117–128.  https://doi.org/10.1016/S0166-445x(99)00008-9CrossRefGoogle Scholar
  67. 67.
    James MO, Altman AH, Morris K, Kleinow KM, Tong Z (1997) Dietary modulation of phase 1 and phase 2 activities with benzo(A)pyrene and related compounds in the intestine but not the liver of the channel catfish, Ictalurus punctatus. Drug Metab Dispos 25(3):346–354Google Scholar
  68. 68.
    Sacco JC, Lehmler HJ, Robertson LW, Li WJ, James MO (2008) Glucuronidation of polychlorinated biphenylols and UDP-glucuronic acid concentrations in channel catfish liver and intestine. Drug Metab Dispos 36(4):623–630.  https://doi.org/10.1124/dmd.107.019596CrossRefGoogle Scholar
  69. 69.
    Stuchal LD, Kleinow KM, Stegeman JJ, James MO (2006) Demethylation of the pesticide methoxychlor in liver and intestine from untreated, methoxychlor-treated, and 3-methylcholanthrene-treated channel catfish (Ictalurus punctatus): evidence for roles of CYP1 and CYP3a family isozymes. Drug Metab Dispos 34(6):932–938.  https://doi.org/10.1124/dmd.105.009068CrossRefGoogle Scholar
  70. 70.
    Weisbrod AV, Sahi J, Segner H, James MO, Nichols J, Schultz I, Erhardt S, Cowan-Ellsberry C, Bonnell M, Hoeger B (2009) The state of in vitro science for use in bioaccumulation assessments for fish. Environ Toxicol Chem 28(1):86–96Google Scholar
  71. 71.
    Schirmer K (2006) Proposal to improve vertebrate cell cultures to establish them as substitutes for regulatory testing of chemicals and effluents using fish. Toxicology 224:163–183Google Scholar
  72. 72.
    Thibaut R, Schnell S, Porte C (2009) Assessment of metabolic capabilities of PLHC-1 and RTL-W1 fish liver cell lines. Cell Biol Toxicol 25(6):611.  https://doi.org/10.1007/s10565-008-9116-4CrossRefGoogle Scholar
  73. 73.
    Behrens A, Schirmer K, Bols NC, Segner H (2001) Polycyclic aromatic hydrocarbons as inducers of cytochrome P4501A enzyme activity in the rainbow trout liver cell line, RTL-W1, and in primary cultures of rainbow trout hepatocytes. Environ Toxicol Chem 20(3):632–643.  https://doi.org/10.1002/etc.5620200324CrossRefGoogle Scholar
  74. 74.
    Putnam JG, Nelson JE, Leis EM, Erickson RA, Hubert TD, Amberg JJ (2017) Using silver and bighead carp cell lines for the identification of a unique metabolite fingerprint from thiram-specific chemical exposure. Chemosphere 168:1477–1485.  https://doi.org/10.1016/j.chemosphere.2016.11.046CrossRefGoogle Scholar
  75. 75.
    Escher BI, Hermens JLM (2004) Internal exposure: linking bioavailability to effects. Environ Sci Technol 38(23):455A–462A.  https://doi.org/10.1021/es0406740CrossRefGoogle Scholar
  76. 76.
    Stadnicka-Michalak J, Knöbel M, Zupanic A, Schirmer K (2017) A validated algorithm for selecting non-toxic chemical concentrations. ALTEX 35(1):37–50.  https://doi.org/10.14573/altex.1701231CrossRefGoogle Scholar
  77. 77.
    Sprague JB (1971) Measurement of pollutant toxicity to fish—III: sublethal effects and “safe” concentrations. Water Res 5(6):245–266.  https://doi.org/10.1016/0043-1354(71)90171-0CrossRefGoogle Scholar
  78. 78.
    von Bertalanffy L (1938) A quantitative theory of organic growth. Hum Biol 10(181):213Google Scholar
  79. 79.
    Schwarzenbach RP, Gschwend PM, Imboden DM (2003) Environmental organic chemistry. Wiley, New YorkGoogle Scholar
  80. 80.
    Hendriks AJ, Traas TP, Huijbregts MAJ (2005) Critical body residues linked to octanol−water partitioning, organism composition, and LC50 QSARs: meta-analysis and model. Environ Sci Technol 39(9):3226–3236.  https://doi.org/10.1021/es048442oCrossRefGoogle Scholar
  81. 81.
    Tropov AA, Roy K (2004) QSPR modeling of lipid-water partition coefficient by optimization of correlation weights of local graph invariants. J Chem Inf Comput Sci 44:179–186Google Scholar
  82. 82.
    Poła A, Michalak K, Burliga A, Motohashi N, Kawase M (2004) Determination of lipid bilayer/water partition coefficient of new phenothiazines using the second derivative of absorption spectra method. Eur J Pharm Sci 21(4):421–427Google Scholar
  83. 83.
    Grech A, Brochot C, Dorne J-L, Quignot N, Bois FY, Beaudouin R (2017) Toxicokinetic models and related tools in environmental risk assessment of chemicals. Sci Total Environ 578:1–15.  https://doi.org/10.1016/j.scitotenv.2016.10.146CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC  2019

Authors and Affiliations

  • Julita Stadnicka-Michalak
    • 1
    • 2
    Email author
  • Kristin Schirmer
    • 1
    • 2
    • 3
  1. 1.EPF Lausanne, School of Architecture, Civil and Environmental EngineeringLausanneSwitzerland
  2. 2.Eawag, Swiss Federal Institute of Aquatic Science and TechnologyDübendorfSwitzerland
  3. 3.ETH Zürich, Institute of Biogeochemistry and Pollutant DynamicsZürichSwitzerland

Personalised recommendations