ACROPOLIS WP5 – Integrated Risk Model

1. ACROPOLIS WP5 – Integrated Risk Model Hilko van der Voet Biometris, DLO, Wageningen University and Research Centre ACROPOLIS kick-off meeting 7-8 June 2010, Utrecht

2. Participants WP5 • DLO (Biometris < (S)DLO < WUR) • 42.5 PM • FERA • 51.5 PM • RIVM • 3 PM • and need a lot of collaboration with others

3. How we see WP 5 in the project ....

4. Task 5.1.a - Review of existing models • Exposure assessment • MCRA, CREME, NCI, MSM, LifeLine, CARES, EUROPOEM, BREAM, ... • Hazard characterisation (BenchMark Dose) • PROAST, EPA-BMDS • Integrated (Margin of Exposure) • IPRA

5. Task 5.1.b - Design of integrated model • Long-term and short-term assessments • synergy with EFSA project ETUI (European Tool Usual Intake) • Models for cumulative assessment • build on experience from triazole project (EFSA 2009) and Safefoods (van der Voet et al. 2009, Bosgra et al. 2009, Müller et al. 2009) • Models for aggregate assessment • include experiences from WP3 • Models for integrated risk assessment • exposure assessment and hazard characterization • RPFs estimated from tox data and used in cum. exp. ass.

6. 5.2 Addressing uncertainty • Building on EFSA (2006) tiered appraoch • Qualitative: systematic identification and evaluation of uncertainties • user-friendly web-based software tool in M3 (August 2010) for members of WP 2/3/4 •  proposal for uncertainties that will be quantified • Quantitative: 2D Monte Carlo approach • inner loop: constructs variability distribution • outer loop: constructs uncertainty distributions

7. 5.3 Implementation • Pipeline of sub-models with well-defined I/O • input tox data and BMD modelling • input field trial / monitoring data and link wih consumption data • probabilistic exposure modelling • integrating exposure and BMD models • cumulative assessment • aggregate assessment • uncertainty analysis • Use of existing modules if possible

8. 5.4 Validation • Validation using simulated datasets based on realistic scenarios • Collection of real datasets for comparative testing of models (relative validation) • Compare measured and predicted intake from appropriate studies • Compare with other models (LifeLine, Cares)

9. 5.5 User guidelines and publications • Develop user guidelines how to use the integrated model and how to perform uncertainty analysis • Publications on new approaches to modelling and uncertainty assessment

10. positive value non-detect (< 0.05) non-measurement Cumulative exposure: residue data

11. Cumulative exposure assessment Several approaches possible: • RPF-weighted summing of residue concentrations per sample • Calculate RPF-weighted sum per sample, then MCRA for ‘single’ compound (uncertainties in RPF cannot be handled) • Integrate RPF-weighted summing in MCRA • Parallel MCRA runs for the compounds, then RPF-weighted summing of intakes • same sequence of simulated consumers

12. Approaches to cumulative exposure assessment i=person, j=food, k=compound, l=portion, s=sample 1a. 1b. 2.

13. Cumulative exposure, Approach 1 Assumes that the total set of samples is representative for each food Advantage: • incorporates correlations between compounds • negative correlation: lower exposure • positive correlation: higher exposure • Disadvantage: • requires data for all compounds in all samples • for non-measured compounds effectively a concentration 0 is assumed • estimated exposure may be too low

14. Cumulative exposure, Approach 2 Assumes that per compound the set of samples with measurements is representative for a food • Advantage: • each compound may have its own set of samples • Disadvantage: • does not incorporates correlations between compounds

15. Contributions by compound and food • Overall contributions recalculated from single-compound MCRA output

16. Deliverables 5.1 Functional design of the cumulative risk model combining useful algorithms of existing software and new functionality defined in other WPs (M12, May 2011). 5.2 First prototype of the cumulative risk model (elements will be clear, not all parts will be programmed in the internet version) (M18, Nov 2011). 5.3 Prototype of an internet based integrated model addressing both cumulative and aggregate exposure and quantification of selected uncertainties (M30, Nov 2012). 5.4 A user and reference guideline of the model including uncertainty analysis (M30, Nov 2012). 5.5 A scientific paper, ready for submission, describing the integrated risk model and its statistical validation (M36, May 2013). 5.6 A scientific paper on new approaches to uncertainty analysis for use in aggregate and cumulative risk assessment of pesticides (M36, May 2013).

17. Milestones 5.1 Consensus on uncertainties in to be included in cumulative and aggregate exposure assessment (M6, Nov 2010). 5.2 Availability of the functional design of the model (M12, May 2011). 5.3 Availability of first prototype of the cumulative risk model (M18, Nov 2011). 5.4 Availability of prototype of an internet based integrated model addressing both cumulative and aggregate exposure and quantification of selected uncertainties (M30, Nov 2012). 5.5 A user and reference guideline of the integrated risk model including uncertainty analysis (M30, Nov 2012).