1. Process-based toxicity analysis in risk assessment Tjalling Jager Bas Kooijman Dept. Theoretical Biology

2. Contents  Dynamic Energy Budget (DEB) theory  Current procedures in (eco)tox  Introduction to DEBtox  Advanced examples  The DEB laboratory

3. Why DEB theory? How do individuals acquire and allocate their resources?

4. Relation DEB and toxicants ? ?

5. ? ?

6. ? ?

7. Dynamic Energy Budgets foodfaeces reserves structure maturity maint.somatic maint. assimilation  1-  maturity offspring

8. DEB pillars  Quantitative theory; “first principles” –time, energy and mass balance  Life-cycle of the individual –links levels of organisation: molecule  ecosystems  Comparison of species –body-size scaling relationships; e.g. metabolic rate  Fundamental to biology; many practical applications –(bio)production,(eco)toxicity, climate change …

9. Chemical-related projects at TB  Dutch government (RWS and RIVM) –biaccumulation metals in mussels; biomonitoring –toxicokinetics dioxin in humans  Dutch Technology Foundation STW –DEBdeg (bio)degradation of (toxic) compounds –DEBtum tumour induction/growth, analysis tox data –DEBtox ind  pop (reprod. modes in nematodes)  EU Projects –ModelKey effects on ecosystems and food chains –NoMiracle mixture toxicity More info: http://www.bio.vu.nl/thb/research/project/

10. Current procedures in (eco)tox

11. “RISK” Risk assessment EXPOSURE EFFECTS Available dataAssessment factor Three LC50s1000 One NOEC100 Two NOECs50 Three NOECs10

12. Integrated model for system Integrated model for system Process parameters at env. conditions Process parameters at env. conditions PEC Lab. experiments Exposure assessment

13. Contr. Standard approaches NOEC Response log concentration LOEC * 1. Statistical testing

14. What’s wrong with NOEC?  No statistically significant effect is not no effect  Effect at NOEC regularly 10-34%, up to >50%  Inefficient use of data –only last time point, only lowest doses –for non-parametric tests also values discarded OECD Braunschweig meeting 1996: NOEC is inappropriate and should be phased out! OECD Braunschweig meeting 1996: NOEC is inappropriate and should be phased out!

15. Standard approaches EC50 Response log concentration 1. Statistical testing 2. Curve fitting

16. What’s wrong with ECx?  No estimation of process parameters –not possible to extrapolate to env. conditions  Inefficient use of data (last time point only)  ECx depends on exposure time Regression model is purely empirical

17. Effects change in time 00.10.20.30.40.50.60.7 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 concentration fraction surviving 48 hours 24 hours Nonylphenol, survival

18. Why does LC50 decrease? Toxicokinetics –effects are related to internal concentrations time internal concentration chemical A chemical B chemical C –kinetics depend on chemical

19. Why does LC50 decrease? Toxicokinetics –effects are related to internal concentrations –kinetics depend on chemical –and species … time internal concentration chemical A chemical B chemical C small fish large fish Daphnia

20. Sub-lethal EC10 in time survival body length cumul. reproduction body length cumul. reproduction 05101520 0 0.5 1 1.5 2 2.5 carbendazim time (days) 0246810121416 0 20 40 60 80 100 120 140 pentachlorobenzene time (days) does not necessarily decrease in time …

21. Consequences Procedures are inefficient  Test protocols yield more data than are used NOEC and LCx/ECx are not representative  Change in time, depending on species, body size, chemical and endpoint Standard exposure time leads to systematic error  in comparing effects –between chemicals (comparative RA, QSARs …?) –between species (SSDs … ?) OECD Braunschweig meeting 1996: Exposure time should be incorporated in data analysis OECD Braunschweig meeting 1996: Exposure time should be incorporated in data analysis

22. Introduction to DEBtox

23. DEBtox –Windows software, version 1.0 in 1996, version 2.0.1 in 2004 –Included in draft ISO/OECD guidance on statistical analysis of ecotox data OECD Braunschweig meeting 1996: Exposure time should be incorporated in data analysis Mechanistic models should be favoured if they fit the data OECD Braunschweig meeting 1996: Exposure time should be incorporated in data analysis Mechanistic models should be favoured if they fit the data

24. Why process-based? Understand toxic effects –biology of organism and toxic mechanisms Match experimental set-up –e.g. degradation, pulse exposure Predictions for exposure situation –e.g. populations, food level, varying exposure

25. DEBtox basics  Effect depends on internal concentration –one-compartment model toxicokinetics 

26. target parameter  toxicokinetics DEBtox basics  Chemical affects a parameter in DEB –e.g. maintenance rate 

27. target parameter toxicokinetics DEBtox basics  Change in target parameter affects endpoint –survival, reproduction, growth   DEB model 

28. Modes of Action foodfaeces reserves structure maturity offspring maturity maint.somatic maint. assimilation  1-    assimilation   maintenance costs   growth costs   reproduction costs   hazard to embryo  hazard (lethal effects)  tumour  tumour induction   endocrine disruption 

29. Windows version  User-friendly software, freely downloadable  Only for standard tests –acute survival –Daphnia reproduction –fish growth –algal population growth

30. Example: survival dieldrin 0.03.25.610183256100 020 1 18 175 220 191715960 320 19159210 420 19144100 520 18124000 620191893000 72018 82000 time (d) concentration (µg/L)

31. Example: survival dieldrin

32. NEC5.2 (2.7-6.9) µg/L Killing rate0.038 L/(µg d) Elim. rate0.79 d -1 Blank haz.0.0084 d -1 NEC5.2 (2.7-6.9) µg/L Killing rate0.038 L/(µg d) Elim. rate0.79 d -1 Blank haz.0.0084 d -1 0 d 1 d 2 d 3 d 4 d 5 d 6 d 7 d

33. Example: survival nonylphenol 0 h24 h48 h 0.00420 0.03220 0.05620 0.10020 0.18020 16 0.32020132 0.5602020 time concentration (mg/L)

34. Example: survival nonylphenol 24 hrs 48 hrs 0 hrs NEC0.14 (0.094-0.17) mg/L Killing rate0.66 L/(mg h) Elim. rate0.057 h -1 NEC0.14 (0.094-0.17) mg/L Killing rate0.66 L/(mg h) Elim. rate0.057 h -1

35. Example: survival nonylphenol LC0 LC50 NEC

36. Example: repro cadmium Mode of actioncosts for repro NEC3.3e-9 (0-0.017) mM Tolerance4.7e-9 mM Max. repro14 offspring/d Elim. rate2.6e-9 d -1 Mode of actioncosts for repro NEC3.3e-9 (0-0.017) mM Tolerance4.7e-9 mM Max. repro14 offspring/d Elim. rate2.6e-9 d -1

37. Example: repro cadmium EC0EC50

38. Advantages DEBtox  Make efficient use of all data points –more accurate parameter estimates –reduce number of test animals …  More information obtained –ECx at any time point can be calculated –mode of action; crucial for population response  Characterisation of effects –time-independent NEC may replace NOEC and ECx For the standard software

39. Advanced examples

40. DEBtox extensions Simultaneous fits on more data sets –endpoints, chemicals, species … Fit deviating experimental data –degradation, pulse exposure … Extrapolations –time, food level, temperature, (species) … At this moment only available as MatLab scripts

41. Simultaneous fits Survival and body residues for cadmium (Heugens et al.) NEC on internal basis:259 mg/kg dwt (202-321)

42. Extrapolation From continuous exposure to a 20-hour pulse 020406080100 0 0.2 0.4 0.6 0.8 1 time (hours) fraction surviving 0 mg/L 3 mg/L 4 mg/L 5 mg/L 10 mg/L

43. simultaneous fits Survival for 5 OP esters (data De Bruijn & Hermens) Same NEC, elim. rate, killing rate, receptor repair rate Different affinity for receptor Same NEC, elim. rate, killing rate, receptor repair rate Different affinity for receptor

44. simultaneous fits 0246810121416 0 0.2 0.4 0.6 0.8 1 survival 051015 0 20 40 60 80 100 120 reproduction body size Mode of action decrease assimilation Mode of action decrease assimilation Reproduction test with cadmium (data Heugens et al.)

45. Extrapolations 00.050.10.150.2 0 0.1 0.2 0.3 0.4 concentration population growth rate (1/day) 90% food 80% food To populations and limiting food

46. Simultaneous fits Body length Cumulative offspring Fraction surviving High food Low food Fenvalerate pulse at two food levels (data Pieters et al.) Mode of action:assimilation NEC survival:0.42 µg/L NEC growth/repro:0.051 µg/L Insights intrinsic sensitivity independent of food chemical effects fully reversible Mode of action:assimilation NEC survival:0.42 µg/L NEC growth/repro:0.051 µg/L Insights intrinsic sensitivity independent of food chemical effects fully reversible

47. Opportunities 1: Relevant endpoint concentration population growth rate PEC impact ecologically relevant time independent integrate endpoints comparable between chemicals NEC

48. impact PEC Opportunities 1: Relevant endpoint concentration population growth rate PEC impact ecologically relevant time independent integrate endpoints comparable between chemicals NEC

49. Opportunities 2: Match exposure scenario time exposure time survival

50. Opportunities 3: Reduce testing needs?  Use all of the data points –more data points per parameter –less animals needed  Less need to discard ‘poor’ data –disappearance of test compound –change in body weight of test organism –combine low-quality data sets  Less need for new tests –better extrapolations from lab data –opportunities for QSAR development …

51. Relations for alkyl benzenes Daphnia pulex, elimination 1 mm juveniles 3 mm adults Fathead minnows, NEC

52. The DEB laboratory

53. Electronic DEB laboratory DEBtox –Windows version 2.0.1. –routine applications DEBtool –open source (Octave, MatLab) –full range of DEB research (fundamental+applied) –also advanced DEBtox applications Freely downloadable from http://www.bio.vu.nl/thb/deb/deblab/

54. Finally … –exposure assessment is well ahead of effects assessment –effects assessment will benefit from a process- based approach more scientific extrapolation testing needs may be reduced –but … requires major shift in thinking basic methods are already available toxicity data are already reported in time In our opinion …

55. More information These slides are available at: http://www.bio.vu.nl/thb/users/bas/lectures/ Further reading (paper submitted): http://www.bio.vu.nl/thb/research/bib/ JageHeug2005.html Further literature: http://www.bio.vu.nl/thb/research/bib