Office of Research and Development
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Office of Research and Development
October 24, 2012
Moving Forward
Tina Bahadori, D.Sc. National Program Director EPA Chemical Safety for Sustainability Program NIEHS Superfund Research Program Annual Meeting Exposure Symposium
Production/Usage
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60
65
70
75
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17Number of Factors
AIC
Sco
re
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Disclaimer: The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.
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Chemical Production Increasing
0
500
1000
1500
2000
2500
Bill
ion
US
$
1950 1970 1990 2010*Year
World Chemical Production
• 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
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Exposure Information: Chemical Coverage
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
Num
ber o
f Che
mic
als
Data Category
P.P. Egeghy et al. / Science of the Total Environment 414 (2012) 159–166
“EPA study reveals barren exposure data landscape” -EDF Chemicals & Nanomaterials Blog, March 16, 2012
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Potential Exposure
from ExpoCast
Providing an Exposure Context for ToxCast
ExpoCast Prediction (mg/kg BW/day)
mg/kg BW/day
Potential Hazard from ToxCast with
Reverse Toxicokinetics
Low Risk
Med Risk
High Risk
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Quantitative Risk Assessment Using ToxCast Requires Exposure
Green squares indicate estimated exposures from EPA REDs or CDC NHANES: ~71% of Phase I ~7% of Phase II
Ora
l Equ
ival
ent D
oses
and
Est
imat
ed E
xpos
ures
(m
g/kg
/day
)
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ExpoCast Predictions for Rapid Risk Assessment
~93% Phase I and ~89% Phase II coverage by ExpoCast Chemicals with Indoor/consumer use in red Chemicals with Far field (industrial/agricultural) release in blue
Ora
l Equ
ival
ent D
oses
and
Est
imat
ed E
xpos
ures
(m
g/kg
/day
)
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Integration and Translation
•Systems framework •Biologically-relevant exposure metrics •Knowledge-base infrastructure
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Systems Exposure Science : Extending Network Analysis
Consider coupled networks spanning multiple levels of biological organization
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Stressor Biological Receptor Outcome Perturbation Perturbation
Population
Individual
Tissue
Cell
Biological Molecules
Environmental Source
Ambient Exposure
Environmental Source Personal
Exposure
Internal Exposure (Tissue Dose)
Dose to Cell
Dose of Stressor Molecules
Disease Incidence/Prevalence
Disease State (Changes to Health Status)
Dynamic Tissue Changes (Tissue Injury)
Dynamic Cell Changes (Alteration in Cell Division,
Cell Death)
Dynamic Changes in Intracellular Processes
Cohen Hubal, JESEE, 2008
Integrating Systems Biology and Exposure Science Exposure at All Levels of Biological Organization
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Biologically-Relevant Exposure Metrics
Markers required that can be directly associated with key events in disease processes and with individual exposure profiles – ‘Omic technologies showing potential to yield a new generation of
exposure metrics (Wild, 2009) (Altered global gene expression associated with exposures to arsenic,
cigarette smoke, benzene, metal fumes and air pollution) – Better environmental biosensors required to study gene-environment
interactions associated with complex disease (Collins 2007) (Nano-scale sensor arrays can be developed to detect specific sets of
environmental agents (Andreescu et al, 2009)) – Characterizing the “internal environment” - strategy for capturing
“snapshots” of critical portions of a person’s Exposome (Rapport and Smith, Science, 2010)
Investment in this area of research required to provide important
approaches for assessing real-world exposures
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Exposure Phenotype Outcome (e.g., OMIM, MeSH)
Chemical (e.g., MeSH)
Biological System (e.g., Functional model of anatomy)
Assessed by
Pathways, Networks Reactions (e.g., KEGG, Reactome)
Occur within
Genes Gene Products
Biological Process Molecular Function Cellular Component (e.g., Gene Ontology
Interact via
Encode Annotated with
Exposure Stressor (e.g., ExO)
Exposure Receptor (e.g., ExO)
Is a
Interacts with
Exposure Event (e.g., ExO, ExpoCastDB)
Via an
Results in an
Interacts with (e.g., CTD)
Interacts with (e.g., CTD)
Is a
Mattingly et al, ES&T 2012
High-level schematic of Exposure Ontology (ExO) Integration Within a Broader Biological Context
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The Strategy: Building Capacity
• Research needs: characterize exposures quickly and cost-effectively at multiple levels of integration (time, space, biological scale), for multiple and cumulative stressors
• Develop advanced exposure infrastructure to forecast, prevent, and mitigate potential impacts and unintended consequences –Non targeted environmental monitoring and surveillance –Sensor networks, advanced biomonitoring, activity tracking –Data storage and distribution systems –Exposure-based predictive screening and modeling systems to
anticipate exposures
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Approach
• Pragmatic approach –Conduct strategic data-gathering efforts –Draw from scientific innovations in fields outside traditional
exposure science –Leverage active initiatives and planned infrastructure – e.g.,
CDC National Environmental Public Health Tracking Network (EPHT), National Ecological Observatory Network (NEON)
• Engage stakeholders in development and use of exposure information – including health agencies, regulators, and communities
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