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Human Health Risk Assessment: EPA’s Current Challenges and the Future

Human Health Risk Assessment: EPA’s Current Challenges and the Future. Presentation for the National Capital Area Chapter - Society of Toxicology “Challenges and Opportunities in Putting High-Throughput Chemical Risk Characterization Into Real-World Practice” April 19, 2011 Washington, DC .

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Human Health Risk Assessment: EPA’s Current Challenges and the Future

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  1. Human Health Risk Assessment: EPA’s Current Challenges and the Future Presentation for the National Capital Area Chapter - Society of Toxicology “Challenges and Opportunities in Putting High-Throughput Chemical Risk Characterization Into Real-World Practice” April 19, 2011 Washington, DC Stan Barone Jr., PhD., National Center for Environmental Assessment Office of Research and Development United States Environmental Protection Agency

  2. Human Health Risk Assessment • Now and in the future, risk assessment remains fundamental to U.S. EPA’s approach to analysis of potential risk from exposure to environmental contaminants • Essential for U.S. EPA regulatory decision-making • Evolving in the face of new understandings about uncertainty, mode of action, metabolism, susceptibility, etc. • Addressing emerging science and new science challenges 1

  3. Current Approach • Large number of animals • Low throughput • Expensive • Time consuming • Pathology endpoints • Dose response extrapolations over a wide range • Application of uncertainty factors • Little focus on mode of action and biology • Few epidemiology studies 5 2

  4. Basic Principles of Risk Assessment at EPA • The starting point for risk assessment is a critical analysis of available scientific information. • Quantitative estimates of risk are, to the extent possible, • Biologically-motivated, • Data-driven. • When there is insufficient data, default methods are used that • Protect public health, • Ensure scientific validity (i.e., scientifically plausible and extensively peer reviewed), and • Create an orderly, transparent and predictable process. • Implementation of these principles involves extensive independent peer review.

  5. Human Health Risk Assessment Transforming to address emerging science and new science challenges • There are tens of thousands of chemicals that are untested and lack assessment of potential for human toxicity. • Current toxicology testing methods are too expensive, too slow, and can cope with too few chemicals. • Toxicology approaches are evolving away from reliance on in vivo testing of laboratory animals • Current approaches to risk analysis need to be significantly modified to deal with more chemicals; innovative approaches • Screening • Fingerprinting • Risk assessment approaches must be developed that can use the new generation of data types and arrays; “omics” • Thus, the environmental health community needs to develop next generation of risk assessment tools, approaches, and practices…NexGen risk assessment • Toxicity pathways • Focused high-throughput assessments

  6. Human Health Assessment IssuesMechanistic Considerations in Human Health Risk Assessment • Increased need to characterize: • A wider array of hazard traits • More chemicals (no data on most chemicals in commerce) • Human carcinogens increasingly emphasis on: • Multiple toxicity pathways, mechanisms affected • These mechanisms could inform new predictive approaches • In vitro assays • Human biomarkers • Dose-response curve: • In an individual: can take multiple forms depending on genetic background, target tissue, internal dose • In a population: variability in susceptibility in response are key determinants Source: Guyton et al. Improving prediction of chemical carcinogenicity by considering multiple mechanisms and applying toxicogenomic approaches. Mutat Res. 681(2-3):230-40, 2009.

  7. Environmental Chemical Stressor Background Exposure: Endogenous & Xenobiotic Biological Susceptibility:Health and Disease Status, Genetics, Age, Gender What Can Be Learned from Mechanistic Data and Analyses? • Identify mechanism-based sources of human variability/ susceptibility (e.g., background diseases and processes, genetic polymorphisms, age, co-exposures) • Address mechanism-based likelihood of other outcomes • Improve prediction of interactions across environmental and endogenous exposures • Identify mechanistic drivers of response at low-doses Adverse endpoint An individual’s dose response Probability of Effect from Environmental Exposure Environmental Chemical Dose Heterogeneity in Background Exposure and Susceptibility Population dose response Source: National Academy of Sciences Report “Science and Decisions: Advancing Risk Assessment” Adapted from Figure 5-3a (December 2008) Fraction of Population Responding to Environmental Chemical Environmental Chemical Dose 21 6

  8. Focus on Mechanisms of Human Disease • Increases appreciation of individual and population heterogeneity of disease mechanisms • Improves prediction of interactions across environmental exposures • Addresses mechanism-based likelihood of other outcomes • Identifies mechanism-based sources of human variability/susceptibility (e.g., background diseases and processes, genetic polymorphisms, age, co-exposures) • Uses Systems biology level tools and data • Advances high throughput methodologies (microarray, proteomics) • The use of mechanistic data will play a key role in the future of risk assessment to: • Aid in identification of sources of human variability/susceptibility (e.g., background diseases and processes, co-exposures, etc) and early stage disease biomarkers. • Address likelihood of other outcomes • Improve prediction of interactions across environmental and endogenous exposures • Indentify mechanistic drivers of response at low doses.

  9. LTS MTS HTS uHTS Gene-expression batch testing of chemicals for pharmacological/toxicological endpoints using automated liquid handling, detectors, and data acquisition High-Throughput Screening Assays(EPA’s National Center for Computational Toxicology,Office of Research and Development) 1000s/day 10s-100s/yr 10,000s-100,000s/day 10s-100s/day Human Relevance/ Cost/Complexity Throughput/ Simplicity

  10. Cancer ReproTox DevTox NeuroTox PulmonaryTox ImmunoTox Future of Toxicity Testing in vitro testing in silico analysis $Thousands HTS -omics Bioinformatics/ Machine Learning

  11. Chemical Receptors / Enzymes / etc. Direct Molecular Interaction Pathway Regulation / Genomics Cellular Processes Tissue / Organ / Organism Tox Endpoint Toxicity Pathways

  12. Cell lines HepG2 human hepatoblastoma A549 human lung carcinoma HEK 293 human embryonic kidney Primary cells Human endothelial cells Human monocytes Human keratinocytes Human fibroblasts Human proximal tubule kidney cells Human small airway epithelial cells Biotransformation competent cells Primary rat hepatocytes Primary human hepatocytes Assay formats Cytotoxicity Reporter gene Gene expression Biomarker production High-content imaging for cellular phenotype Protein families GPCR NR Kinase Phosphatase Protease Other enzyme Ion channel Transporter Assay formats Radioligand binding Enzyme activity Co-activator recruitment Cellular Assays Assays (n = 467) ToxCast in vitro HTS assays Chemicals (n = 320) Biochemical Assays Judson et al EHP (2010) http://www.epa.gov/ncct/toxcast/ 11

  13. Signature Derivation for Rat Liver Carcinogens 12

  14. Virtual Tissues, Organs and Systems:Linking Exposure, Dosimetry and Response Molecular interactions & fluxes Intra/inter- cellular signaling/ fluxes Cell spatial interactions Lobular / vascular damage Molecular Network Structure & Dynamics Cell Fate Transitions death /division Tissue Morphology changes Liver Injury

  15. Challenges and Opportunities Extrapolation from in vitro to in vivo Recapitulation and modeling of complex cell-cell and tissue interactions. Development of virtual models to describe systems biology Recapitulation of complex behaviors

  16. This strategy focuses on development of: • A pilot implementation of a new approach for risk based decision-making, including characterization of risk management needs, policy relevant questions and implications for NexGen risk assessments; • An operational scale knowledge mining, creation and management system to support risk assessment work and interface with gene environment data bases. • Develop approaches using HT/HC data for toxicity pathways to predict/estimate points of departure for assessment purposes. • Prototype examples of increasingly complex assessments responsive to the risk context and refined through discussions with scientists, risk managers, and stakeholders.

  17. NexGen Types of Data Tier 1 10,000s of chemicals Tier 2 1000s of chemicals Tier 3 100s of chemicals • High • Throughput • Molecular Mechanisms of Action • In vitro only bioassay batteries (~73-500 assays) • Network/disease pattern recognition • Metabolism or surrogates • QSAR • Anchored to in vivo data • Bioinformatic data integration • +High Content/Med Throughput • Adds Tissue/Organism Level Integration • Short-term in vivo exposures with in vitro assays • Mammalian species • Alternative species • Primary tissue culture • In silico virtual tissues • In vivo or anchored to in vivo data • Bioinformatic data & knowledge integration • +High Content, Med/Low Throughput • Adds Most Realistic Scenarios • Molecular epidemiology & clinical Studies • Molecular biology + traditional animal bioassay • Environmental exposures • Upstream & phenotypic outcomes • Mechanism of action for multiple stressors • Knowledge integration Increasing Weight of Evidence Screening/Ranking Limited decision-making Regulatory decision-making

  18. Decision Framework for Incorporating High Throughput Data Are there existing assessments (hazard id & dose response), based on in vivo data, that can be utilized? Conduct literature search to determine if new data will significantly alter existing assessment; update if needed. Identify the chemicals of interest, exposure sources and pathways. YES NO Are there in vivo data to inform qualitative hazard? Use (Q)SAR and read-across to predict estimates of risk based on surrogate(s) and/or NO YES Overall WOE for hazard Are there non-in vivo data to inform qualitative hazard? NO YES Conduct high throughput testing with a battery of assays, alternative species What tissues/cell types/toxicity pathways are affected by the chemical in question? • Assemble WOE by: • Proximity to in vivo condition: tissue explants>cells in culture > cell-free assays>in silico • Traditional WOE criteria e.g. multiple studies/laboratories, multiple dose-response. Use existing assessments to anchor in vitro /in silico analyses, if appropriate. Is data sufficient to determine relative potencies or dose-response? • ToxCast/ToxPi and reverse dosimetry • Predictive Phenotyping • Traditional DR modeling (w optional test data) NO YES how • Assess dose-response: • Conduct high throughput testing with a battery of assays • Conduct alternative species &/or targeted in vivo testing (optional) how Relative potencies and/or dose-response • ToxCast/ToxPi and reverse dosimetry • Predictive Phenotyping • Traditional DR modeling (w optional test data) • Goals • Rank/ group chemicals • Assessment of high priority chemicals

  19. Incorporating CSS/Next Generation of Risk Assessment (3-5 yrs) Three Assessment Tiers— Informed by Molecular & System Biology - Responsive to Risk Context Decision-making Predictive Systems Models Input to Decision-making Testing, Research, Assessment Loop IRIS, ISA’s & Multi- Pollutant Assessments Superfund tech center & PPRTV’s PPRTV’s & IRIS • Tier 2 Assessments • Narrow scope decision-making • Limited hazard &/or exposures • Many chemicals (hundreds of chemicals) • High-and medium throughput assays & some systems level integration • Science-based defaults & upper confidence limit risk estimates • Tier 1 Assessments • Screening & prioritization • Unknown hazard but exposures • Thousands of chemicals • High-throughput & QSAR-driven • Minimize false negatives • Tier 3 Assessments • Broad scope, major regulatory decision-making • Highest national hazard & exposures • Few chemicals (dozens) • All feasible, policy-relevant emerging & traditional data • Best estimates of risk & uncertainty analyses Flagged for Additional Analysis Research by NCCT, ORD labs, & partners Testing NTP, REACH, TSCA, etc. 15

  20. The Path to 21st Century Toxicology Toxicity Pathways in Prioritization Toxicity Pathways in Risk Assessment Institutional Transition

  21. The Future of Risk AssessmentSummary • The landscape of risk assessment is changing to an extent that significant modernization of risk assessment is necessary. • These changes are driven largely by advances in understanding the gene environment; the important input and advice from expert science panels; and volumes of new test data from Europe. • These events prompt us to look anew at risk assessment and develop this strategy to thoughtfully position environmental health scientists and assessors for the future and contribute to meaningful change within the larger risk assessment/risk management community. • The goal of this strategy is to map a course forward, focusing on creating 1st approximation NexGen risk assessments, learning from these efforts and, then, refining the next versions based on this new knowledge. • It may take a decade before risk assessment can rely primarily on new advances in science • It is necessary, however, to begin now to address needed changes. 24

  22. Thank you Figure by Jane Ades, Courtesy National Human Genome Research Institute

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