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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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add Grocery [ 16 ] Toys [ 10 ], drop Home [ 3 ]

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add Sports & Outdoors [ 7 ] Craft & Party Supply [ 8 ], drop Home [ 3 ]

add Home [ 3 ]add Beauty [ 13 ] Baby [ 4 ] Patio & Garden [ 2 ], drop Sports & Outdoors [ 7 ] Production/Usage

add LogPadd Auto and Tires [ 7 ] Vapor Pressure, drop LogP

add Pets [ 5 ]

add Home Improvement [ 13 ]

add Health [ 8 ] Electronics [ 6 ] LogP, dro add Home Improvement [ 13 ]

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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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