1. National Institute for Public Health and the Environment 1 Integrated probabilistic risk assessment Bas Bokkers National Institute for Public Health and the Environment (RIVM) – the Netherlands

2. National Institute for Public Health and the Environment 2 Deterministic risk assessment -Variability extreme consumer sensitive subpopulations -Uncertainty limited concentration data interspecies extrapolation A deterministic risk assessment does not discriminate between variability and uncertainty Worst-case / conservative approach using point values

3. National Institute for Public Health and the Environment 3 Exposure = consumption concentration Deterministic risk assessment PoD AF 1 AF 2 ….. AF i *** * Risk if exposure > ADI or ADI = ADI exposure <1

4. National Institute for Public Health and the Environment 4 Conclusions deterministic RA Inconclusive: -Exposure is slightly higher than ADI “risks cannot be excluded” *Percentage of population affected ? Quantify the uncertainty Remaining question: Quantify the risk: Qualitative: -Exposure > ADI risk everyone affected?

5. National Institute for Public Health and the Environment 5 Probabilistic risk assessment -Variability extreme consumer sensitive subpopulations -Uncertainty limited concentration data interspecies extrapolation A probabilistic risk assessment can discriminate between variability and uncertainty Realistic approach using distributions

6. National Institute for Public Health and the Environment 6 Integrated probabilistic risk assessment: Evaluates - both variability and uncertainty (but separately) -in bothexposure assessment hazard characterization - in a single (integrated) analysis For instance: Combine variability in exposure with variability in sensitivity Combine uncertainty in concentrations with uncertainty in interspecies differences

7. National Institute for Public Health and the Environment 7 but variability distributions can inform iBMD and iEXP distributions = consumption concentration Probabilistic risk assessment PoD AF 1 AF 2 ….. AF i *** * This individual is at risk when his/her iEXP > iBMD or when iBMD Individual’s dose that would lead to some predefined effect: The same individual’s exposure: No information on the individuals…… = iEXP iBMD iEXP <1 of

8. National Institute for Public Health and the Environment 8 Probabilistic risk assessment iBMD distr. iEXP distr. An individual is at risk when his/her iEXP > iBMD or when iBMD iEXP <1 = 1 * Fraction of the population affected

9. National Institute for Public Health and the Environment 9 Uncertainty distributions can inform uncertainty in iBMD and iEXP distributions = consumption concentration Probabilistic risk assessment PoD AF 1 AF 2 ….. AF i *** * iBMD= iEXP of

10. National Institute for Public Health and the Environment 10 PoD distribution PoD AF 1 AF 2 ….. AF i *** distr. iBMD = Critical effect size (CES) X% decrease in BW distributionBMD BMD distribution

11. National Institute for Public Health and the Environment 11 Assessment factors PoD AF 1 AF 2 ….. AF i *** distr iBMD = Interspecies Subchronic-to-chronic Subacute-to-chronic based on historical data (BMD ratios)* *see e.g. Bokkers and Slob tox sci 85 & crit rev toxicol 37 Kramer et al. regul toxicol pharm 23 Intraspecies 1 Sensitivity in whole population: Variability Uncertainty about the variability See van der Voet et al. food chem tox 47

12. National Institute for Public Health and the Environment 12 Integrated probabilistic hazard characterization PoD AF 1 AF 2 ….. AF i *** distr. iBMD = = *** …… Variability and uncertainty in these distributions are analyzed separately

13. National Institute for Public Health and the Environment 13 Integrated probabilistic risk assessment iBMD distr. iEXP distr. An individual is at risk when his/her iEXP > iBMD or when iBMD iEXP <1 = 1 * Fraction of the population affected * Uncertainty can be quantified

14. National Institute for Public Health and the Environment 14 Example of integrated prob. RA output Lower Percentile Upper percentile Det Prob (% affected & CI) no risk 0.0001 risk iBMD iEXP =1 risk 101001000 risk not excl (0-0.005) 0.0001 (0-0.8) 0.1 (0-20) 8 (5-20)

15. National Institute for Public Health and the Environment 15 Contribution to uncertainty % contribution to uncertainty Guidance to reduce uncertainty in the RA

16. National Institute for Public Health and the Environment 16 Not implemented yet: approach for carcinogens More time-consuming (vs lower tier deterministic RA) Limited no. of uncertainties incorporated Applied in European projects Peer reviewed journals RA advise to Dutch government Future challenges Extend approach for carcinogens Increase acceptance How…..? Limitations

17. National Institute for Public Health and the Environment 17 All ingredients are available Dose-response modeling / BMD techniques are available Empirical AF distributions are available (excl. intraspecies AF) Probabilistic exposure assessment techniques are available Integration techniques are available Limited tox or exposure data? Larger uncertainty Incorporated in probabilistic RA And……..

18. National Institute for Public Health and the Environment 18 Benefits of (integrated) probabilistic RA Quantification of -Fraction of the population affected -Uncertainty Risks can be compared -between effects -between substances Probabilistic approach provides more insight in risk Targeted risk management actions or further research

19. National Institute for Public Health and the Environment 19 Thank you for your attention

20. National Institute for Public Health and the Environment 20 Further reading Bokkers, B. et al (2009). The practicability of the integrated probabilistic risk assessment (IPRA) approach for substances in food. RIVM report 320121001/2009, Bilthoven, the Netherlands. http://www.rivm.nl/bibliotheek/rapporten/320121001.pdf Bosgra, S. et al (2009). An integrated probabilistic framework for cumulative risk assessment of common mechanism chemicals in food: an example with organophosphorus pesticides. Regul Toxicol Pharmacol 54, 124-33. Müller, A.K. et al (2009). Probabilistic cumulative risk assessment of anti- androgenic pesticides in food. Food Chem Toxicol 47, 2951-62. van der Voet, H. and Slob, W. (2007). Integration of probabilistic exposure assessment and probabilistic hazard characterization. Risk Anal 27, 351-71. Benchmark dose software: www.proast.nl EFSA (2009) Guidance of the Scientific Committee: use of the benchmark dose approach in risk assessment. The EFSA Journal 1150, 1-72 http://www.efsa.europa.eu/en/scdocs/scdoc/1150.htm bas.bokkers@rivm.nl