integrated probabilistic risk assessment

National Institutefor Public Healthand the Environment

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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


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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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


PoD

AF1 AF2 ….. AFi* **

*

iBMD =

iEXP

of

of


10

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

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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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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 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

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integrated probabilistic risk assessment

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