ACROPOLIS WP5 – Integrated Risk Model Hilko van der Voet Biometris, DLO, Wageningen University and Research Centre ACROPOLIS kick-off meeting 7-8 June.

Slides:



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

1Scientific Advisory Board meeting | 31 maart 2011 Jacob van Klaveren ACROPOLIS Scientific Advisory Board Jacob van Klaveren.
Assessment of the uncertainty of CO2 sink of forest land in the EU 15's GHG inventory by V. Blujdea, G. Grassi & R. Pilli CCU JRC.
1 Consumer Exposure Assessment at the U.S. Environmental Protection Agency: A ccomplishments and Opportunities for Global Collaboration Thomas Brennan.
DICODE-FP7 Project WP6 - Validation & Assessment.
NCeSS e-Stat quantitative node Prof. William Browne & Prof. Jon Rasbash University of Bristol.
An innovative tool for the review of health and safety work practices and the implementation of effective controls of particulate exposures.
PERFORMER KO MEETING NICE - 12 th & 13 th September 2013 WP1short presentation.
Francesca Arena European Commission Health and Consumers Directorate General Future data requirements related to bees for the authorisation of plant protection.
Alternate approach to developing target levels Increasingly common ( NASA, NRC, USEPA ) Statistical vs deterministic inputs ( can be combined ) Addresses.
Data Mining Methodology 1. Why have a Methodology  Don’t want to learn things that aren’t true May not represent any underlying reality ○ Spurious correlation.
©2001 Plan B Systems Inc. PBSi Quantitative Cost/Schedule Risk Analysis.
Modelling cumulative risk Hilko van der Voet Biometris, DLO, Wageningen University and Research Centre Third ACROPOLIS consortium meeting 31 March 2011,
PROBABILISTIC DIETARY EXPOSURE ASSESSMENT TO PESTICIDE RESIDUES.
CONFERENCE ON “ FOOD ADDITIVES : SAFETY IN USE AND CONSUMER CONCERNS“ JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY NAIROBI, 24 JUNE 2014.
National Institute for Public Health and the Environment 1 Integrated probabilistic risk assessment Bas Bokkers National Institute for Public Health and.
Approaches to Data Acquisition The LCA depends upon data acquisition Qualitative vs. Quantitative –While some quantitative analysis is appropriate, inappropriate.
Michael H. Dong MPH, DrPA, PhD readings Human Exposure Assessment II (8th of 10 Lectures on Toxicologic Epidemiology)
Cumulative Risk Assessment for Pesticide Regulation: A Risk Characterization Challenge Mary A. Fox, PhD, MPH Linda C. Abbott, PhD USDA Office of Risk Assessment.
Monte Carlo Analysis A Technique for Combining Distributions.
Development plan and quality plan for your Project
Decision analysis and Risk Management course in Kuopio
Sources of Uncertainty and Current Practices for Addressing Them: Exposure Perspective Clarence W. Murray, III, Ph.D. Center for Food Safety and Applied.
Computer Simulation A Laboratory to Evaluate “What-if” Questions.
Mantova 18/10/2002 "A Roadmap to New Product Development" Supporting Innovation Through The NPD Process and the Creation of Spin-off Companies.
Business Process Performance Prediction on a Tracked Simulation Model Andrei Solomon, Marin Litoiu– York University.
Environmental Risk Analysis
Kick off meeting, swarm E2E study, nio #1 8-Sep-15 Development Approach Task 1: Industrial Module –to be used by industry for their system simulation –Output:
Irwin/McGraw-Hill 1 Market Risk Chapter 10 Financial Institutions Management, 3/e By Anthony Saunders.
VTT-STUK assessment method for safety evaluation of safety-critical computer based systems - application in BE-SECBS project.
CRESCENDO Full virtuality in design and product development within the extended enterprise Naples, 28 Nov
Managing food chain risks: the role of uncertainty Richard Shepherd University of Surrey.
Introduction to MCMC and BUGS. Computational problems More parameters -> even more parameter combinations Exact computation and grid approximation become.
Simulation Prepared by Amani Salah AL-Saigaly Supervised by Dr. Sana’a Wafa Al-Sayegh University of Palestine.
BASELINE software tool for calculation of microbiological criteria and risk management metrics for selected foods and hazards WP6 Model Development Final.
E-PreS: Monitoring and Evaluation of Natural Hazard Preparedness at School Environments Stathes Hadjiefthymiades National Kapodistrian University of Athens.
Hybrid Simulation with Qualitative and Quantitative Integrated Model under Uncertainty Business Environment Masanori Akiyoshi (Osaka University) Masaki.
Module 3 Risk Analysis and its Components. Risk Analysis ● WTO SPS agreement puts emphasis on sound science ● Risk analysis = integrated mechanism to.
Simulation is the process of studying the behavior of a real system by using a model that replicates the behavior of the system under different scenarios.
Center for Radiative Shock Hydrodynamics Fall 2011 Review Assessment of predictive capability Derek Bingham 1.
Ch 10 - Risk Management Learning Objectives You should be able to: List and describe risk management processes, inputs, outputs, and tools List and describe.
ENSEMBLES RT4/RT5 Joint Meeting Paris, February 2005 Overview of the WP5.3 Activities Partners: ECMWF, METO/HC, MeteoSchweiz, KNMI, IfM, CNRM, UREAD/CGAM,
Simulation is the process of studying the behavior of a real system by using a model that replicates the system under different scenarios. A simulation.
© 2006 Pearson Addison-Wesley. All rights reserved 2-1 Chapter 2 Principles of Programming & Software Engineering.
HSRB Chair Summary of October 20 Recommendations Sean Philpott, PhD, MSBioethics HSRB Chair October 21, 2009.
WP2: Cumulative dietary exposure and hazard assessment Bernadette Ossendorp en Polly Boon.
RLV Reliability Analysis Guidelines Terry Hardy AST-300/Systems Engineering and Training Division October 26, 2004.
Modelling the Process and Life Cycle. The Meaning of Process A process: a series of steps involving activities, constrains, and resources that produce.
Freshfel Europe Acropolis WP 6. Freshfel Europe European fresh fruit and vegetables association 200 members frpm production to retailers Based in Brussels.
Add your Logo in the slide master menu GLOBAQUA Meeting, January 13th-14th, Freising IMPLICATIONS Module Reporting back Implications Module: WP8, WP9,
1 Simulation Scenarios. 2 Computer Based Experiments Systematically planning and conducting scientific studies that change experimental variables together.
Office of Research and Development National Center for Environmental Assessment Human Health Risk Assessment and Information for SRP July 28, 2009 Reeder.
Introduction It had its early roots in World War II and is flourishing in business and industry with the aid of computer.
1. Consumers, Health, Agriculture and Food Executive Agency Risk assessment with regard to food and feed safety Risk analysis Why risk assessment in the.
Overview of the GEMS Food programme to support chemical risk assessment Dr Philippe Verger.
Development of improved approaches for exposure estimations of operators, workers, bystanders and residents Rianda Gerritsen-Ebben, representing BROWSE.
Acute Toxicity Studies Single dose - rat, mouse (5/sex/dose), dog, monkey (1/sex/dose) 14 day observation In-life observations (body wt., food consumption,
Probabilistic methods for aggregate and cumulative exposure to pesticides Marc Kennedy Risk and Numerical Sciences team
QALIBRA - Introduction
WP1 – Smart City Energy Assessment and User Requirements
2. Industry 4.0: novel sensors, control algorithms, and servo-presses
PM 584 Education for Service/snaptutorial.com
Professor S K Dubey,VSM Amity School of Business
بسم الله الرحمن الرحیم.
Quantitative Risk Assessment
Uncertainty management
Georg Umgiesser and Natalja Čerkasova
European Commission, DG Environment Air & Industrial Emissions Unit
Background CRiteria for the IDentification of Groundwater thrEsholds: BRIDGE Co-ordinator: BRGM (Fr) Groundwater Characterisation workshop, 25 June 2004.
DESIGN OF EXPERIMENTS by R. C. Baker
Presentation transcript:

ACROPOLIS WP5 – Integrated Risk Model Hilko van der Voet Biometris, DLO, Wageningen University and Research Centre ACROPOLIS kick-off meeting 7-8 June 2010, Utrecht

Participants WP5 DLO (Biometris < (S)DLO < WUR) 42.5 PM FERA 51.5 PM RIVM 3 PM and need a lot of collaboration with others

How we see WP 5 in the project....

Task 5.1.a - Review of existing models Exposure assessment MCRA, CREME, NCI, MSM, LifeLine, CARES, EUROPOEM, BREAM,... Hazard characterisation (BenchMark Dose) PROAST, EPA-BMDS Integrated (Margin of Exposure) IPRA

Task 5.1.b - Design of integrated model Long-term and short-term assessments synergy with EFSA project ETUI (European Tool Usual Intake) Models for cumulative assessment build on experience from triazole project (EFSA 2009) and Safefoods (van der Voet et al. 2009, Bosgra et al. 2009, Müller et al. 2009) Models for aggregate assessment include experiences from WP3 Models for integrated risk assessment exposure assessment and hazard characterization RPFs estimated from tox data and used in cum. exp. ass.

5.2 Addressing uncertainty Building on EFSA (2006) tiered appraoch Qualitative: systematic identification and evaluation of uncertainties user-friendly web-based software tool in M3 (August 2010) for members of WP 2/3/4 proposal for uncertainties that will be quantified Quantitative: 2D Monte Carlo approach inner loop: constructs variability distribution outer loop: constructs uncertainty distributions

5.3 Implementation Pipeline of sub-models with well-defined I/O input tox data and BMD modelling input field trial / monitoring data and link wih consumption data probabilistic exposure modelling integrating exposure and BMD models cumulative assessment aggregate assessment uncertainty analysis Use of existing modules if possible

5.4 Validation Validation using simulated datasets based on realistic scenarios Collection of real datasets for comparative testing of models (relative validation) Compare measured and predicted intake from appropriate studies Compare with other models (LifeLine, Cares)

5.5 User guidelines and publications Develop user guidelines how to use the integrated model and how to perform uncertainty analysis Publications on new approaches to modelling and uncertainty assessment

Cumulative exposure: residue data positive value non-detect (< 0.05) non- measurement

Cumulative exposure assessment Several approaches possible: 1.RPF-weighted summing of residue concentrations per sample a.Calculate RPF-weighted sum per sample, then MCRA for single compound (uncertainties in RPF cannot be handled) b.Integrate RPF-weighted summing in MCRA 2.Parallel MCRA runs for the compounds, then RPF- weighted summing of intakes same sequence of simulated consumers

Approaches to cumulative exposure assessment 1a. 1b. 2. i=person, j=food, k=compound, l=portion, s=sample

Cumulative exposure, Approach 1 Assumes that the total set of samples is representative for each food Advantage: incorporates correlations between compounds negative correlation: lower exposure positive correlation: higher exposure Disadvantage: requires data for all compounds in all samples for non-measured compounds effectively a concentration 0 is assumed estimated exposure may be too low

Cumulative exposure, Approach 2 Assumes that per compound the set of samples with measurements is representative for a food Advantage: each compound may have its own set of samples Disadvantage: does not incorporates correlations between compounds

Contributions by compound and food Overall contributions recalculated from single- compound MCRA output

Deliverables 5.1 Functional design of the cumulative risk model combining useful algorithms of existing software and new functionality defined in other WPs (M12, May 2011). 5.2 First prototype of the cumulative risk model (elements will be clear, not all parts will be programmed in the internet version) (M18, Nov 2011). 5.3 Prototype of an internet based integrated model addressing both cumulative and aggregate exposure and quantification of selected uncertainties (M30, Nov 2012). 5.4 A user and reference guideline of the model including uncertainty analysis (M30, Nov 2012). 5.5 A scientific paper, ready for submission, describing the integrated risk model and its statistical validation (M36, May 2013). 5.6 A scientific paper on new approaches to uncertainty analysis for use in aggregate and cumulative risk assessment of pesticides (M36, May 2013).

Milestones 5.1 Consensus on uncertainties in to be included in cumulative and aggregate exposure assessment (M6, Nov 2010). 5.2 Availability of the functional design of the model (M12, May 2011). 5.3 Availability of first prototype of the cumulative risk model (M18, Nov 2011). 5.4 Availability of prototype of an internet based integrated model addressing both cumulative and aggregate exposure and quantification of selected uncertainties (M30, Nov 2012). 5.5 A user and reference guideline of the integrated risk model including uncertainty analysis (M30, Nov 2012).