1. Making sense of sub-lethal mixture effects Tjalling Jager, Tine Vandenbrouck, Jan Baas, Wim De Coen, Bas Kooijman

2. Challenge of mixture ecotoxicity  Some 100,000 man-made chemicals  Large range of natural ‘toxicants’  For animals, 1.25 million species described  Complex exposure situations

3. Typical approach AB

6. wait for 21 days …

7. Dose-response plot dose-ratio dependent deviation from CA concentration A concentration B total offspring

8. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

9. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

10. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

11. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

12. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

13. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

14. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

15. What question did we answer? “What is effect of constant exposure to this mixture on total Daphnia reproduction after 21 days under standard OECD test conditions?”

16. What question did we answer? “What is effect of constant exposure to this mixture on Daphnia reproduction after 21 days under standard OECD test conditions?”

17. What question did we answer? “What is effect of constant exposure to this mixture on Daphnia reproduction after 21 days under standard OECD test conditions?”

18. Better questions do we see these time patterns of effects? can we explain the effects on all endpoints over the life cycle in one framework? can we make useful predictions for other mixtures, other species, and other exposure situations?

19. external concentration B (in time) external concentration A (in time) effects in time Process-based

20. external concentration B (in time) external concentration A (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics Process-based internal concentration A in time internal concentration B in time survival as a chance process effects in time Tolerance distribution McCarty et al (1992) Lee & Landrum (2006) Stochastic death Ashauer et al. (2007) Baas et al. (2007, 2009) Tolerance distribution McCarty et al (1992) Lee & Landrum (2006) Stochastic death Ashauer et al. (2007) Baas et al. (2007, 2009)

21. Sub-lethal endpoints … growth reproduction feeding maintenance maturation

22. Sub-lethal endpoints … growth reproduction feeding maintenance maturation Rules for mass and energy flows DEB (Kooijman, 2000/2001) Rules for mass and energy flows DEB (Kooijman, 2000/2001)

23. Process-based external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time assimilation maintenanc e maturation …. theory implies interactions … growth

24. external concentration A (in time) toxico- kinetics toxico- kinetics external concentration B (in time) toxico- kinetics toxico- kinetics DEB model DEB model internal concentration A in time metabolic processes in time internal concentration B in time effects on all endpoints in time Process-based assimilation maintenanc e maturation ….

25. Simple mixture rules assimilation maintenance … compound‘target’metabolic process toxicity parameters linked (compare CA)

26. Simple mixture rules assimilation maintenance … compound‘target’metabolic process

27. Simple mixture rules assimilation maintenance … compound‘target’metabolic process toxicity parameters independent (compare IA)

28. fluoranthene pyrene PAHs in Daphnia  Based on standard 21-day OECD test 10 animals per treatment length, reproduction and survival every 2 days no body residues (TK inferred from effects)

29. Same target: costs reproduction (and costs growth) Same target: costs reproduction (and costs growth)

30. Iso-effect lines for body length <50% effect

31. Conclusions PAH mixture  Mixture effect consistent with ‘same target’ as expected for these PAHs explains all three endpoints, over time  Iso-effect lines are functions of time which differ between endpoints in this case: little deviation from CA  Few parameters for all data in time 14 parameters (+4 Daphnia defaults) (descriptive would require >100 parameters)

32. Parameter estimates external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars

33. Educated extrapolation external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars populations

34. Educated extrapolation external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars other endpoints other, e.g., repro rate respiration

35. Educated extrapolation external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars time-varying concentrations

36. Educated extrapolation external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars food limitation

37. Educated extrapolation external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars other narcotic compounds

38. Educated extrapolation external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time metabolic processes in time DEB model DEB model effects on all endpoints in time TK parstox parsDEB pars other (related) species

39. Final words  A process-based approach is essential … to progress the science of mixture toxicity to make useful predictions for RA  Key elements DEB approach one framework for all endpoints over time feasible with ‘reasonable’ data sets certain interactions are unavoidable …  Of course, more work is needed … validate predicted interactions and extrapolations ready to tackle more complex mixtures!

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