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Beneris (Benefit-risk assessment for food: an iterative

value-of-information approach)

Jouni TuomistoKTL, Finland

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Partners

ESFINFundación Privada para la Investigación Nutricional

IELendacLendac Ltd

DKFVSTFood Safety Authority of Denmark

DKDTUTechnical University of Denmark

IEFSAIFood Safety Authority of Ireland

FIFFilesOy Foodfiles Ltd

NLTUDelftDelft University of Technology

FIKTLNational Public Health Institute

CountryParticipant short name

Participant name

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Objectives (selection)• A framework for handling complicated benefit-risk situations• Benefit-risk analysis methods

– Bayesian belief networks (BBN)– Methods for dose-response assessment, combining epidemiological and toxicological

data– A result database for information relevant for benefit-risk assessments

• Food risks and benefits– To estimate nutrient intakes and food consumption in various subgroups– To identify food consumption patterns and food choices that determine the intake

• Dissemination– To integrate results into updated benefit-risk assessments, and evaluate the

remaining uncertainties and their importance for decision-making.– To develop an internet interface for publishing risk assessment results.– To develop methods to collect feedback from end-users about benefit-risk analyses.

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Timeline• Project started April 1, 2006• Heande website opened September, 2006• Open Risk Assessment report September, 2007• Mid-term meeting November 7-9, 2007• Result database opened January, 2008• Full case study, fish fall 2008• Full case study, vegatable spring 2009• Final project meeting June, 2009• Project ends September 30, 2009

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The ORA report

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Results and deliverables achieved• Bayesian belief network (BBN) on fish prepared

– Work on parameter values under way• A methodology report:

– Tuomisto and Pohjola: Open Risk Assessment, 2007.• A website for making open assessments:

http://heande.pyrkilo.fi• A test database for the data repository

http://www.pyrkilo.fi/resultdb

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Methods and Approaches Open assessment

A general assessment method that enables unrestricted participation (i.e. mass collaboration) at all phases of the assessment process

Applies a defined information structure: causal diagrams with variables

Formal argumentation is used to resolve disputes Bayesian belief networks as the decision support

system

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Case studies Fish: benefits of nutrients and risks of pollutants in

fish– Dioxin, PCB, methyl mercury– Omega-3 fatty acids, selenium, iodine– Cardiovascular and cancer mortality, IQ loss,

developmental defects (teeth) Vegetables: impacts of vegetable-rich and

vegetable-poor diets in children– The detailed scoping under way

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BBN: fish case study

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Comments on Benefit-risk assessment tiered approach

Jouni T. TuomistoNational Public Health Institute (KTL),

Finland

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Important points• Question must be clear and for a need!• Iterative approach• Transparency• Need for procedural decisions acknowledged• Utilises approaches developed in other areas:

DALYs, QALYs

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Comments on procedural decisions• Who actually decides what is needed or sufficient?

– About the main questions asked.– About the outcomes considered.– About when the preference between scenarios is clear

enough.• What is the basis for these decisions? Are the

criteria explicated in an assessment?

• Truth should be used as the ultimate criterion

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Comments on Margin of Exposure (MoE)• DALYs of QALYs can be used in measuring both

risks and benefits• The use of MoE is ambiguous and should be

discouraged.– 10 % impact on a risk and on a benefit are NOT

comparable in any meaningful way.

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Comments on the process• ”Problem definition is an iterative process.” If

the main question changes, when is the assessment no longer the original assessment?

• If the approach is a general approach, it should work fine with risk assessments (no benefits) and benefit assessments (no risks) as well.