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Exposure Data Landscape. Peter P. Egeghy National Exposure Research Laboratory. NCCT Elaine Cohen Hubal Richard Judson Shad Mosher Sumit Gangwal Doris Sloan Jamie Vail. NERL Dan Vallero Linda Sheldon Carry Croghan Cecilia Tan. Acknowledgements. Disclaimer.

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exposure data landscape

Exposure Data Landscape

Peter P. EgeghyNational Exposure Research Laboratory

acknowledgements
NCCT

Elaine Cohen Hubal

Richard Judson

Shad Mosher

Sumit Gangwal

Doris Sloan

Jamie Vail

NERL

Dan Vallero

Linda Sheldon

Carry Croghan

Cecilia Tan

Acknowledgements

Disclaimer

This work may not necessarily reflect official Agency policy.

outline
Outline
  • Context
  • History
  • Assessment of Current Landscape
  • Expectations of the Future
large numbers and volumes of chemicals are produced
Large Numbers and Volumes of Chemicals are Produced
  • Chemical production has increased spectacularly since 1970s
    • Expansion of chemical portfolio
    • Expansion of types of products
    • Ubiquitous integration
  • Formidable number of chemicals in commercial use
    • 143,000 substances in Europe
    • 100,000 in US
  • Approximately 30,000 substances marketed in volumes > 1 t/y
    • About 3,000 HPV chemicals make up 95% of total production

* Projected

size of chemical universe makes exposure assessment difficult
Size of Chemical Universe Makes Exposure Assessment Difficult
  • The vast majority of chemicals in commerce:
    • Are unmeasured in environmental or biological media
    • Have unknown environmental fate and exposure potential
    • Have non-quantified human and ecosystem health impacts
  • Resource and technological limits
  • Exposure modeling
    • Broader indicators and surrogates
    • Production volume, use category, product formulation, chemical release, pathways, degradation, activities/behaviors
    • Need for high throughput methods
slide7

Exposure Framework

FATE/TRANSPORT

CONCENTRATION

ACTIVITY

EXPOSURE

MANUFACTURE

RELEASE

PRODUCT 1

PRODUCT 2

PRODUCT 3

PRODUCT 4

PRODUCT 5

Market Share

Population

PRODUCT 6

Location

Frequency

PRODUCT 7

Timing

PRODUCT 8

PRODUCT …

PRODUCT n

WorkplaceExposure

Water

Food

EnvironmentalRelease

Chemical

Transportation

Land

A C T I V I T I E S

Air

Production/Formulation(Product orProcessing Aid)

Disposal

Incineration

INTERMEDIATES

CHEMICAL

HumanExposure

Recycling

SewageTreatment

DEGRADATES

ConsumerUse

IndoorAir

OutdoorAir

SurfaceDust

Soil

A C T I V I T I E S

Food

Water

1992 inventory of data
Compilation of federally managed data systems with exposure information

Conducted jointly by EPA, CDC, and ATSDR

Premise: Data systems exist that could be used to conduct studies and evaluate regulatory effectiveness

Identified databases:

Environmental Measurements 54

Micro-Environmental Concs 10

Human Samples 13

1992 Inventory of Data
data sharing pressures have increased
Data Sharing Pressures Have Increased
  • Changes in information technology reenergized the decades-old call for consistency and standardized procedures for collecting, storing, and reporting exposure-related information
    • Public Health: epidemiology, exposure limits, risk management
  • NIH Data Sharing Policy (2003)
    • Data sharing plan included in application (>$500K)
    • OMB Circular A-110 – Applies to EPA as well
  • Journals being asked to require basic data as supplementary material
  • Recently, REACH legislation has produced increased interest
    • Manufacturers/Importers required to consider likely exposures
    • Predictive tools are being developed
accessible exposure databases aid chemical prioritization
Accessible Exposure Databases Aid Chemical Prioritization
  • Accessible exposure databases facilitate:
    • Application of environmental informatics tools
    • Linkages with toxicity data (ACToR, DSSTox)
    • Linkages with product usage data
    • Large-scale, multidimensional data analysis
  • Formal representation of key concepts and relationships
    • Defines exposure domain and data structure

Brazma et al., 2006 Genetics 7:593-605

overview of exposure data sources

Source/Release

Overview of Exposure Data Sources

Production/ Import Volumes

EPA HPVIS

EPA IUR

EU ESIS

Environmental Releases

EPA TRI

HC NPRI

DOE GHG

Consumer Products

Household Products DB

Voluntary Cosmetic Reg. DB

Product Usage Information

EPA Pesticide Usage Data

UK Pharma-ceutical Usage

USDA DB

Production/ Process Information

EPA HPVIS

ATSDR Tox Profiles

DEA NFLIS

Environmental Transformation

Environmental Fate Simulator

ECOTOX DB

EU CAESAR

Transport/Fate

Outdoor Air Monitoring/ Modeling

EPA AirData

EPA NATA

UN IPCC GHG

Water Monitoring Data

EPA NCOD & UCM Program

UK Pharm Water

Environmental

Concentration

DOE IndoorAir

EPA HEDS

WHO Global Indoor Air DB

Indoor Air Monitoring Data

Human Exposure Monitoring

EPA HEDS

FDA TDS

THL Platform

Activity Patterns Information

EPA NHAPS

EPA CHAD

Human Biological Monitoring

CDC NHANES

EPA HEDS

German ES

Exposure

other data aggregators
Other Data Aggregators
  • UMDNJ Environmental Bioinformatics Knowledge Base (ebKB)
  • NLM Hazardous Substances Databank (HSDB)
  • ATSDR HazDat/Sequoia
  • EPA Envirofacts Data Warehouse
  • EPA DataFinder
another new initiative ctd exposure data curation pilot
Curate and integrate data in CTD

Develop exposure ontology

Define scope of data to be curated

Test curation protocol

Another New Initiative:CTD Exposure Data Curation Pilot

Source: C. Mattingly

risk21 exposure science sub team
ILSI HESI initiative to advance risk assessment

Multi-stakeholder approach and collaboration

Particular attention to exposure assessment

Facilitate integration of exposure data

Rapid prioritization

Chemical evaluation

Chemical management

Key focus: Exposure Data Standards

Disseminate data

Link with toxicity data

Risk21 Exposure Science Sub-Team
conclusions
Conclusions
  • Exposure surrogates exist across the source-to-dose continuum
  • New publically accessible systems are constantly being added
  • Several efforts are currently underway to catalog and link the varied sources of exposure data
  • These efforts support much needed predictive models for screening chemicals based on exposure
  • Data sharing pressures will accelerate these efforts