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Integrated probabilisticrisk assessment
Bas Bokkers
National Institute for Public Health andthe Environment (RIVM) – the Netherlands
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Deterministic risk assessment
-Variability extreme consumer
sensitive subpopulations
-Uncertainty limited concentration data
interspecies extrapolation
A deterministic risk assessment does not discriminatebetween variability and uncertainty
Worst-case / conservative approach using point values
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Exposure = consumption concentration
Deterministic risk assessment
PoD
AF1 AF2 ….. AFi* **
*
Risk if exposure > ADI or
ADI =
ADIexposure
<1
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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?
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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
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Integrated probabilistic risk assessment:
Evaluates - both variability and uncertainty (but separately)
-in both exposure 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
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but variability distributions can
inform iBMD and iEXP distributions
= consumption concentration
Probabilistic risk assessment
PoD
AF1 AF2 ….. AFi* **
*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
iBMDiEXP
<1
of
of
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Probabilistic risk assessment
iBMD distr.
iEXP distr.
An individual is at risk when his/her iEXP > iBMD or wheniBMDiEXP
<1
=
1
* Fraction of the population affected
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Uncertainty distributions can inform uncertainty
in iBMD and iEXP distributions
= consumption concentration
Probabilistic risk assessment
PoD
AF1 AF2 ….. AFi* **
*
iBMD =
iEXP
of
of
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0 500 1000 1500
dose
200
250
300
350
400
450
BW
PoD distribution
PoD
AF1 AF2 ….. AFi* **distr. iBMD =
Critical effect size (CES)X% decrease in BW
distributionBMD
BMD distribution
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Assessment factors
PoD
AF1 AF2 ….. AFi* **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
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Integrated probabilistic hazard characterization
PoD
AF1 AF2 ….. AFi* **distr. iBMD =
=
*** ……
Variability and uncertainty in these distributions
are analyzed separately
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Integrated probabilistic risk assessment
iBMD distr.
iEXP distr.
An individual is at risk when his/her iEXP > iBMD or wheniBMDiEXP
<1
=
1
* Fraction of the population affected
* Uncertainty can be quantified
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effect D
effect C
effect B
effect A
Example of integrated prob. RA output
Lower PercentileUpper percentile
Det
Prob
(% affected & CI)
no risk0.0001
risk
iBMDiEXP
=1
risk
10 100 1000
risknot excl
(0-0.005)
0.0001(0-0.8)
0.1(0-20)
8(5-20)
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Contribution to uncertainty
0
25
50
75
100
Consu
mption
Conce
ntrati
on
BMD
Inter
spec
ies
Intra
spec
ies
% c
ont
ribu
tion
to u
nce
rta
inty
Guidance to reduce uncertainty in the RA
0
25
50
75
100
Consumption Concentration BMD Interspecies Intraspecies
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• 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
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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……..
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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
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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