Development and Improvement of ICE/ACE for Predictive Toxicology

1. Sandy Raimondo Mace G. Barron Office of Research and Development/NHEERL Gulf Ecology Division 2 November 2005 Development and Improvement of ICE/ACE for Predictive Toxicology

2. Overview • Background: ICE/ACE development • Current Research: ICE/ACE Validation and Improvement

3. ICE and ACE Software Development Developed by Sonny Mayer (GED) and Colleagues ICE (Interspecies Correlation Estimation) Estimates acute toxicity for a species, genus or family from a surrogate species ACE (Acute to Chronic Estimation) Estimates chronic toxicity from raw acute toxicity data

4. ICE:Interspecies Correlation Estimations • Significance: • Addresses second largest source of variation in toxicity data – variation of species within a chemical • Fills data gaps by estimating toxicity of untested species

5. How ICE works Uses existing correlations of toxicity values (LC50, LD50)between a surrogate species and a predicted taxa (species, genus, or family) LC50: concentration that kills 50% of organisms LD50: dose that kills 50%

6. Acute toxicity estimates using interspecies correlations

7. ICE estimates LC50 from surrogate species LC50 and available species correlation

8. Current ICE Uses: EPA Program Offices • Office of Water (OW): draft Ambient Water Quality Criteria (AWQC) guidelines, endangered species • Office of Pesticide Programs (OPP): qualitative use in risk assessment currently being implemented.

9. ICE: Applications Ecological Risk Assessment (ERA) • Generate species sensitivity distribution • Define risk management level Endangered Species Risk Assessment • Surrogate test species are toxicologically representative of endangered species (Mayer et al.) • ICE can be used to estimate toxicity to T&E species using existing correlations (147 LC50s; 20 species)

10. ACE:Acute to Chronic Estimations Significance: Provides estimated chronic toxicity for species with only acute data Acute: ie.96-hour LC50/ LD50 Chronic: long-term, sublethal

11. ACE:Acute to Chronic Estimations Application: • Reduced reliance on acute to chronic ratios based on multiple species and chemicals • Being considered by OPP for qualitative use in risk assessment

12. How ACE Works

13. ACE Chronic Mortality Prediction Uses raw survival data to estimate chronic mortality Linear Regression Analysis (LRA) Accelerated Life Testing (ALT)

14. Limitations of ICE and ACE • validation and uncertainty (ICE, ACE) • data poor (e.g., ICE wildlife) • flexibility-power (ICE)

15. Future Direction of ICE/ACE Expand Datasets (QA/QC) ICE ACE Validation, Refinement, Expansion Validation New Software Improved Tool Functionality

16. ICE Improvement Procedure • Model Validation: Regression analysis • Model Refinement: Stepwise regression • Model Expansion: Power and number of models • QA/QC: Bootstrap validation • Defining Assumptions / Developing user guidelines: multivariate analyses • New Software

17. ICE Improvement Procedure • Model Validation: Assessment of existing significant correlations Aquatic ICE models (P<0.01) • Species: 565 • Genus: 195 • Family: 291 Validation dataset for aquatics Ambient Water Quality Criteria (AWQC) data • 88 chemicals (12 pesticides) • 279 species • 1458 new data points

18. < 3x difference > 3x difference ICE Validation Example

19. ICE Improvement Procedure 2. Model Refinement Stepwise Regression • Finds the best fit model • Quality of data • Power of model • Mode of action Model improvement through reduction (filter by MOA, species, data quality)

20. ICE Improvement Procedure 3. Model Expansion Increase power of the models • Many existing models have N=3 • More data increases likelihood of significant correlations Increase the number of significant correlations ICE Wildlife Correlations (P ≤ 0.01) OriginalCurrent 62 152 Model improvement through addition (species, chemical)

21. ICE Improvement Procedure 4. QA/QC of all refined and improved models Bootstrap validation of all improved models • data points are randomly removed • model is recreated • removed data are used to validate model • up to 1000 replicates

22. ICE Improvement Procedure Multivariate Analysis • mode of action • chemical class • species • life history • model fit (yes or no) • degrees of freedom • model R2, p-value User Guidance

23. ICE Improvement Procedure 6. Updated Software (2007) Selectable datasets Interactive program user can enter in new dataset for species not in ICE (ie. endangered species) and ICE will build predictive model based on internal data Broader applicability Wider user base

24. < 5x difference > 5x difference ACE Validation and User Guidance Validate using expanded dataset • Original validation used 30 fish acute: chronic data pairs • Expanded validation dataset >150 datasets Define where models are robust • MOA • Chemical Classes • Species Develop new user guidance • Multivariate Analyses • Improve value to user

25. 2006 Anticipated Products & Outcomes: • Manuscript: Wildlife Toxicity Estimation • Manuscript: Validation of ICE • Manuscript: Validation of ACE • Technology transfer 2007: Updated ICE Software