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Extrapolating to time-varying exposure …

Extrapolating to time-varying exposure …. Tjalling Jager Dept. Theoretical Biology. using biology-based modelling. Problem of extrapolation. Protection goal. Available data. ??. different exposure time different temperature different species time-varying exposure

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Extrapolating to time-varying exposure …

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  1. Extrapolating to time-varying exposure … Tjalling Jager Dept. Theoretical Biology using biology-based modelling

  2. Problem of extrapolation Protection goal Available data ?? • different exposure time • different temperature • different species • time-varying exposure • species interactions • populations • other stresses • mixture toxicity • …

  3. Time-varying exposure Specifically relevant for risk assessment • accidental spills • plant-protection products • industrial chemicals; ‘intermittent release’ Scientifically interesting • response of growth, reproduction and survival? • reversibility of effects? • how does this translate to population impact and recovery?

  4. pesticide fate modelling oil-spill modelling Fate modelling

  5. Effects modelling? • NOEC and ECx cannot complement fate models • purely descriptive statistics • only valid for particular test duration and endpoint • only defined for constant exposure • Impossible to experimentally test each scenario …

  6. internal concentration in time toxico- kinetics toxico- dynamics external concentration in time effects on life history in time extensively studied Biology-based modelling Explicit assumptions about processes chemicals must be taken up to be toxic less popular …

  7. Effects on reproduction

  8. Effects on reproduction

  9. Effects on reproduction

  10. Effects on reproduction

  11. Sub-lethal effects • Understanding growth and reproduction requires understanding resource allocation • Dynamic Energy Budget (DEB) theory specifies allocation rules • focus of dept. Theoretical Biology

  12. DEBtox • TK model • one-compartment model • account for growth toxicokinetics external concentration • Target • energy-budget parameter • threshold for effects: NEC target parameter internal concentration over time animal model • Animal model • simplified DEB model survival/growth/repro Kooijman & Bedaux (1996), Jager et al. (2006)

  13. triphenyltin body length cumulative offspring time time Target: maintenance Jager et al. (2004)

  14. pentachlorobenzene body length cumulative offspring time time Target: costs for growth Alda Álvarez et al. (2006)

  15. DEBtox • Well-tested for constant exposure • Recognition in regulatory context • included in ISO/OECD guidance • workshop at JRC/ECB Ispra • Embedded in (inter)national science • e.g., participation in EU projects NoMiracle and ModelKey • Applicable to time-varying exposure?

  16. toxicokinetics target parameter animal model environ. conc. time Time-varying exposure

  17. environ. conc. time time toxicokinetics target parameter animal model Assumption toxicokinetics follows first-order, one-comp. model internal conc.

  18. environ. conc. NEC time time toxicokinetics target parameter animal model Assumption effects on energetic processes are reversible blank value assimilation eff. internal conc.

  19. cumul. reproduction body length time time toxicokinetics target parameter animal model

  20. Experimental validation Pieters et al. (2006) • Daphnia magna and fenvalerate • modified 21-day reproduction test • pulse exposure for 24 hours • two food levels (relative food level is parameter in DEB)

  21. Body length Cumulative offspring Fraction surviving High food Low food Pulse exposure mode of action: ‘assimilation’ phys. parameters: 5 tox. parameters: 6 • Insights • tox. parameters independent of food • chemical effects fully reversible

  22. Population approaches Effects on individual budgets forms basis of population response • Intrinsic rate of increase • only for exponential growth in constant environment • Leslie-matrix model • classes characterised by one state variable (size or age) • Cohort-based (e.g., escalator-boxcar train) • cohorts can be specified by many state variables • dynamically follow food concentration

  23. Cohort based, fenvalerate High food Limiting food Jager et al., 2007 (RIVM report)

  24. Concluding remarks Time-varying exposure of populations is highly relevant • both from scientific and regulatory perspective DEBtox provides natural modelling framework • covers both lethal and sub-lethal effects • no fundamental obstacles for time-variable exposure Individual budgets as basis for population response • one of pillars of DEB theory • cohort-based approaches look promising

  25. Project structure based on DEBtox, coding MatLab Model development Lab experiments Population framework food? predation? migration? support from BASF AG cohort-based reversibility?multiple pulses? Data analysis Population predictions

  26. Extrapolation ?? www.bio.vu.nl/thb

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