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Integrated probabilistic
risk assessment
Bas Bokkers
National Institute for Public Health and
the Environment (RIVM) – the Netherlands
Deterministic risk assessment
-Variability
extreme consumer
sensitive subpopulations
-Uncertainty
limited concentration data
interspecies extrapolation
Worst-case / conservative approach using point values
A deterministic risk assessment does not discriminate
between variability and uncertainty
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Deterministic risk assessment
PoD
ADI =
AF1 AF2 ….. AFi
*
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* *
Exposure = consumption
* concentration
Risk if exposure > ADI or
ADI
<1
exposure
Conclusions deterministic RA
Inconclusive:
- Exposure is slightly higher than ADI
“risks cannot be excluded”
Qualitative:
- Exposure > ADI
risk
everyone affected?
Remaining question:
Quantify the risk:
*Percentage of population affected ?
Quantify the uncertainty
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Probabilistic risk assessment
- Variability
extreme consumer
sensitive subpopulations
- Uncertainty
limited concentration data
interspecies extrapolation
Realistic approach using distributions
A probabilistic risk assessment can discriminate
between variability and uncertainty
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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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Probabilistic risk assessment
Individual’s dose that would lead to some predefined effect:
PoD
of iBMD =
AF1 AF2 ….. AFi
*
* *
The same individual’s exposure:
of iEXP = consumption concentration
*
This individual is at risk when his/her iEXP > iBMD or when
No information on the individuals……
but variability distributions can
inform iBMD and iEXP distributions
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iBMD
<1
iEXP
Probabilistic risk assessment
iBMD
<1
An individual is at risk when his/her iEXP > iBMD or when
iEXP
iBMD distr.
=
1
iEXP distr.
* Fraction of the population affected
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Probabilistic risk assessment
PoD
of iBMD =
AF1 AF2 ….. AFi
*
* *
of iEXP = consumption concentration
*
Uncertainty distributions can inform uncertainty
in iBMD and iEXP distributions
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PoD distribution
BMD distribution
PoD
distr. iBMD =
AF1 AF2 ….. AFi
450
* *
200
250
300
BW
Critical effect size (CES)
X% decrease in BW
350
400
*
0
500
1000
1500
dose
BMD distribution
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Assessment factors
PoD
distr iBMD =
AF1 AF2 ….. AFi
*
* *
Interspecies
Subchronic-to-chronic
based on historical data (BMD ratios)*
Subacute-to-chronic
Sensitivity in whole
Intraspecies
population: Variability
1
Uncertainty about
the variability
*see e.g.
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Bokkers and Slob tox sci 85 & crit rev toxicol 37
Kramer et al. regul toxicol pharm 23
See van der Voet et al. food chem tox 47
Integrated probabilistic hazard characterization
PoD
distr. iBMD =
AF1 AF2 ….. AFi
*
* *
=
*
*
…… *
Variability and uncertainty in these distributions
are analyzed separately
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Integrated probabilistic risk assessment
iBMD
<1
An individual is at risk when his/her iEXP > iBMD or when
iEXP
iBMD distr.
=
1
iEXP distr.
* Fraction of the population affected
* Uncertainty can be quantified
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Example of integrated prob. RA output
Lower Percentile
Upper percentile
Prob
Det
(% affected & CI)
0.0001
(0-0.005)
effect A
no risk
effect B
risk
not excl
0.0001
(0-0.8)
effect C
risk
0.1
(0-20)
effect D
risk
8
(5-20)
10
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iBMD
=1
iEXP
100
1000
100
100
75
75
50
50
25
25
cie
s
In
t
ra
sp
e
cie
s
er
sp
e
In
t
BM
D
n
nc
en
tra
tio
Co
ns
um
pt
io
n
0
Co
% contribution to uncertainty
Contribution to uncertainty
0
Consumption Concentration
BMD
Guidance to reduce uncertainty in the RA
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Interspecies
Intraspecies
Applied in
• European projects
• Peer reviewed journals
• RA advise to Dutch government
Limitations
• Not implemented yet: approach for carcinogens
• More time-consuming (vs lower tier deterministic RA)
• Limited no. of uncertainties incorporated
Future challenges
• Extend approach for carcinogens
• Increase acceptance
How…..?
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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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Thank you for your attention
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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 antiandrogenic 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
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