1Scientific Advisory Board meeting | 31 maart 2011 Milan WP2: Data organisation and electronic platform Polly Boon.

1 Scientific Advisory Board meeting | 31 maart 2011

Milan

WP2: Data organisation and electronic platform

Polly Boon

Scientific Advisory Board meeting | 31 maart 2011

Milan

2

Contents

●WP2 tasks●MCRA●WP2 state of the art●Plans for the future


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WP2● Title: Cumulative dietary exposure

and hazard assessment● Partners involved:

– CZ: National Institute of Public Health– NL: National Institute for Public Health

and the Environment– IT: University of Milan / National

Research Institute for Food and Nutrition– SE: National Food Administration

– UK: Chemicals Regulation Directorate

● Partners outside project:– F: ANSES– DK: DTU


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WP2: Tasks (1)● Organisation of input data

– National food consumption data– National pesticide residue concentration data

› OPs, triazoles, synthetic pyrethroids, chlorpyrifos› National monitoring programme’s

– Processing– Variability + unit weight – Relative Potency Factors– Harmonisation of the data:

› Coding input data› Conversion to RAC ingredient

National recipes / conversion factors

› Pooling data

National data available for cumulative exposure modelling


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• BMD modelling– Organisation of the tox data relevant for identified chemical

groups› OPs, triazoles, synthethic pyrethroids› Data needed from toxicology (animal) studies:

● For quantal data: doses used, no. of responding animals per group, total no. of animals per group

● For continuous data: doses, mean response per dose group, SD in each group, and no. of animals per group.

› DARs, EFSA, JMPR, EPA, other sources (?)• Derivation RPFs based on the same toxicological endpoint, using

the same effect size

WP2: Tasks (2)


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• Use of developed cumulative exposure model– Case studies:

› OPs, triazoles, synthetic pyrethroids› Chlorpyrifos (biomarker)

– Based on EFSA guideline PPR, 4 exposure scenario’s– Based on current version (7.0) of MCRA – RPFs: Derived from BMD modelling

WP2: Tasks (3)


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• Internet based model (mcra.rivm.nl)• Modelling of dietary exposure / intake of food

chemicals (both adverse and beneficiary)• Human population

– Including subgroups (age, sex, diet, etc)

• Acute and chronic exposure– Acute: Monte Carlo sampling– Chronic: Statistical modelling

MCRA: Characteristics (1)


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MCRA: Characteristics (2)• Input:

– Food consumption data (daily consumption patterns of individuals)

– Concentration data (e.g. monitoring programmes, field trial, MRL)› Concentrations assigned to samples < LOR (% crop treated)

– Processing factors (fixed, distribution)– Variability factors, unit weights– Empirical or distributions– Conversion model

› Link between foods consumed and commodities analysed› Inclusion of mixed/prepared foods like pizza, bread


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MCRA: Characteristics (3)• Uncertainty analyses: bootstrapping

– Concentration– Consumption– Processing factors

• Cofactor / covariable analysis (chronic modelling)– Sex / age

• Scenario / sensitivity analyses


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MCRA: How does it work?

Calculation consists of four steps

Specify input data

Specify model

Set and run model

View output

I

II

IIIIV


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MCRA: Selection of input data (1) I


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MCRA: Selection of input data (2) I

A

B


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MCRA: Specify model (1) II


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MCRA: Specify model (2) II


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MCRA: Set and run (1)III


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MCRA: Set and run (2)III


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MCRA: View output (1)IV


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MCRA: View output (4)

Total distribution Upper 5 % (> 0.34 ug/kg bw/d)

IV


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WP2: State of the art (1)• National food consumption have been organised:

– National food codes– FoodEX1 codes

● National concentration data have been organised:– Captan and triazoles– RACs: CODEX codes (SAFE FOODS)

• Link based on Dutch RAC conversion model• Four exposure scenario’s of EFSA: captan, using

MCRA


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WP2: State of the art (2)• BMD modelling

• Inventory of triazole toxicity data from DARs, JMPR and EFSA, resulting in first dose response analysis using PROAST

• OPs data: SAFE FOODS• Synthetic pyrethroids: ?

-3.0 -2.5 -2.0 -1.5 -1.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

log10-dose.mgkgbw

Tm

PA

H.C

i.m

OTA

E4: y = a*[c-(c-1)exp(-bx)]Proast23.8 v ar- 0.1513 a- 0.9628 b- 25.63 c 0.05854 loglik -24.68 conv : 1 sf .x : 1 dty pe : 10 selected : dur.mth 3 106 CES 0.05 BMD 0.002129


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WP2: Immediate plans for the future• Cumulative exposure to triazoles according to four scenario’s

of EFSA• Inclusion of F and DK in the platform• Conversion of national foods to RACs based on national

recipe data and conversion factors• Harmonisation coding of RACs analysed according to EU

pesticide regulation• Harmonisation coding foods consumed using FoodEx codes• BMD modelling:

• Further research triazoles• BMD modelling OPs• Synthetic pyrethroids

24 Scientific Advisory Board meeting | 31 maart 2011

Milan

acropolis-eu.com

1Scientific Advisory Board meeting | 31 maart 2011 Milan WP2: Data organisation and electronic platform Polly Boon.

Documents

mcra slide

milan wp2

data national data available

future slide

dtu slide

b slide

data organisation

continuous data