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

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

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

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 ICE: Interspecies Correlation Estimations

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

Acute toxicity estimates using interspecies correlations

ICE estimates LC50 from surrogate species LC50 and available species correlation

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.

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 ) ICE: Applications

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

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

How ACE Works

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

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

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

1.Model Validation: Regression analysis 2.Model Refinement: Stepwise regression 3.Model Expansion: Power and number of models 4.QA/QC: Bootstrap validation 5.Defining Assumptions / Developing user guidelines: multivariate analyses 6.New Software ICE Improvement Procedure

1.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

ICE Validation Example < 3x difference > 3x difference

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) 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) Original Current ICE Improvement Procedure Model improvement through addition (species, chemical)

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

Multivariate Analysis mode of action chemical class species life history model fit (yes or no) degrees of freedom model R 2, p-value User Guidance 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 ICE Improvement Procedure

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 < 5x difference > 5x difference

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