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1 Eugene Demchuk Agency for Toxic Substances and Disease Registry Frederick, MD - 08/25/2011 Chemical Toxicity Databases at NCEH/ATSDR
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2 Topics EH Portfolio external dose NHANES internal dose Doch/QSAR: the QSAR Database Of Consistent Health guidance values ~ 60,000,000 synthetic chemicals
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3 Environmental Pollutants 3,000 – 4,000 Information about a Chemical 200,000 records in EH Portfolio Chemicals
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4 EH Portfolio ATSDR’s Integrated Knowledge Base Former
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5 Hazardous Waste Sites
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6 EH Portfolio System Interfaces EH Portfolio MISB Personnel (MS SQL Server) MISB UFMS (MS SQL server) UFMS(unix) GIS EPA TopHat GIS Mapping CERCLIS LOAD Mapping Interface (proposed) Data out via WebService (requested) Demograp hics batch sftp UFMS process Data download
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7 Site / Event Comparison Values Health Studies Substance Publications Cost Recovery ASA Abstracts Toll Free Health Education Contaminants EH Portfolio Relationships Diagram
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11 ATSDR Functions Supported EH Portfolio was deemed Critical or Significant to the following ATSDR Functions: Liaison Function (Washington Office) Budget Development and Justification (Washington Office) State Cooperative Agreement Project Management (DHAC) ATSDR Internal and External Technical Support (DHAC) Development of CERCLA Hazardous Substances Priority List Development of Toxicological Profiles Development of Research Data Needs Mixtures Research Dissemination of Information * Indicates Congressionally Mandated Function
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12 log LOAELs Categorized by Source oral data from Doch/QSAR -8.0 -6.0 -4.0 -2.0 0.0 2.0 log(LOAEL) IRIS OPP ATSDR Others Count 85 13 70 12
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13 National Health and Nutrition Examination Survey (NHANES) NHANES IV survey conducted during 1981-2008 by NCHS Cross-sectional survey designed by NCHS Multi-stage probability sampling design that includes 49 pseudo geographic strata and two Primary Sampling Unit (PSU)
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14 MEC of the NCHS
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15 CDC measures more than 300 environmental chemicals in blood and urine (biomonitoring)
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16 Doch/QSAR the QSAR Database of consistent health guidance values (HGVs) Need: because of large uncertainty error bar on empirical tox data, the data for CQDB have to be carefully selected and classified to avoid possible internal contradictions Components Intended for cross-chemical extrapolation Oral Ingestion Inhalation
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17 Is it possible to extrapolate from a small number of chemicals?
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18 Power Analysis Number of Points in the Training Set R2R2 ALL data
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19 Criteria and Data Evaluation Eliminate developmental toxicity Select most recent assessment Chronic studies preferred over intermediate studies Primary Data Sources ATSDR and IRIS Multiple HGVs RfD, Chronic MRL, Intermediate MRL No HGV EPA-OPP, IPCS-CICADS, Health Canada, RIVM, U.S. Army Consistent HGV
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20 What impacts power? Quantity Uniformity/quality of the data N 0.0
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21 LOAEL ~ Species Decreasing of LOAELs with increasing body weight of tested species.
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22 Oral data in Doch/QSAR PODSpeciesData source 627 data records for 499 unique chemicals 329 Chronic186 Intermediate112 Others (289 unique chem.)(178 unique chem.)
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23 Rat oral chronic LOAELs All oral chronic LOAELs 300400200 456
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24 Rat oral chronic LOAELs All oral chronic LOAELs 300400200 456
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25 Current ATSDR oral LOAEL model Method used:Partial Least Squares Regression Number of compounds:100 Response variable:log LOAEL [mmol/kg] Final predictors used:53 Number of PLS factors:10 Cross-validation:20-fold Cross-validated Q-Square RSSPRESS
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26 32 Validation by bioavailability of ingested aliphatic hydrocarbons “Studies in rats show that absorption of ingested aliphatic hydrocarbons is inversely related to molecular weight, ranging from complete absorption at the lower end of the molecular weight range to about 60% for C14 hydrocarbons, 5% for C28 hydrocarbons, and essentially no absorption for aliphatic hydrocarbons with >32 carbons” Toxicological Profile for Total Petroleum Hydrocarbons, ATSDR, 1999 ATSDR HGV/ LOAEL model shaped similar to mouse LDlo/LD50 experimental data 2814 60% for C145% for C28absorption for no >32
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27 Comparison to MRDD model from ACD/Labs
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28 Current ATSDR Inhalation model (AEGL-1, 8 Hour) Apply the model to: training data (blue) external data (red) The model was trained with 121 compounds and processed 12 of 13 compounds in the external validation set
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29 Current ATSDR Inhalation model (AEGL-2, 8 Hour) Apply the model to: training data (blue) external data (red) The model was trained with 176 compounds and processed 18 of 19 compounds in the external validation set
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30 Current ATSDR Inhalation model (AEGL-3, 8 Hour) Apply the model to: training data (blue) external data (red) The model was trained with 175 compounds and processed 14 of 19 compounds in the external validation set
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31 Message You were shown several databases that are developed at CDC/NCEH/ATSDR One of them, Doch/QSAR consists of carefully selected high-quality toxicity data These data can be used for toxicological cross-chemical extrapolations
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32 Disclaimer The findings and conclusions in this presentation have not been formally disseminated by the Agency for Toxic Substances and Disease Registry and should not be construed to represent any agency determination or policy.
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