## Comments on EPA’s White Paper “Integrated Bioactivity and 

## Exposure Ranking: A Computational Approach for the Prioritization and Screening of 

## Chemicals in the Endocrine Disruptor Screening Program”

Richard A. Becker Ph.D. DABT Dec. 3, 2014

### Additional work by EPA, however, should be

considered to improve the scientific basis of the methods used, and to fully document model 

### development and performance. The approach presented in EPA’s IBER Profiling White Paper represents a significant advance in bringing such methods to the forefront 

### We support EPA’s conceptual approach to use activity in screening assays measuring E and A endocrine - related endpoints and to combine this 

### with HT exposure information to provide an improved scientific basis for priority setting

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### Recommendations for the Path Forward:

Enhance Transparency & Refine Methodology

• We understand that the Agency intends to release model codes in the future, but the lack of such information at the present time renders a comprehensive independent verification of modeling by outside experts and peer reviewers very difficult. • ACC’s comments include an analysis prepared for ACC by Dr. Tony Cox; specific comments on the strengths and limitations of the area under the curve (AUC) approach for activity profiling are noted, and recommendations for improvement are made. • We request that the SAP and Agency give due attention to Dr. Cox’ report as the SAP conducts its evaluation and the Agency moves forward to revise the IBER Profiling method for EDSP priority setting . 3Becker et al. 2014. Interpreting Estrogen Screening

Assays in the Context of Potency and Human Exposure Relative to Natural Exposures to Phytoestrogens

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### Assist ACC groups in developing science and

research projects, identifying collaborations and design of strategies for utilization of results in 

### product stewardship & regulatory activities Development and application of Exposure : Activity Ratio (EAR) and Relative Endocrine Exposure Activity Quotient (REEAQ) to ToxCast & T21 Estrogen Assay Results

5 An Exposure:Activity Profiling Method for Interpreting High Throughput Screening Data for Estrogenic Activity – Proof of Concept (Becker et al., 2014 Accepted for Publication in Reg Tox Pharm)

### Assist ACC groups in developing science and

research projects, identifying collaborations and design of strategies for utilization of results in 

### product stewardship & regulatory activities Development and application of Exposure : Activity Ratio (EAR) and Relative Endocrine Exposure Activity Quotient (REEAQ) to ToxCast & T21 Estrogen Assay Results



### • Oral equivalent doses (mg/kg/d) from Wetmore et al. 2012.

• EARs: compare: 

### (1) human exposure estimates (oral, mg/kg/d) to (2) predicted oral equivalent doses (mg/kg/d), corresponding to HTS assay AC50.

• EAR values for GEN are based on steady state plasma levels . 6

### Assist ACC groups in developing science and

research projects, identifying collaborations and design of strategies for utilization of results in 

### product stewardship & regulatory activities 

### Activity Results: ToxCast Estrogen Activity (ATG_ERa_TRANS) Log Scale

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### Assist ACC groups in developing science and

research projects, identifying collaborations and design of strategies for utilization of results in 

### product stewardship & regulatory activities Log Scale 

### Exposure: Activity Ratios (EAR) (ATG_ERa_TRANS)

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### Assist ACC groups in developing science and

research projects, identifying collaborations and design of strategies for utilization of results in 

### product stewardship & regulatory activities Log Scale 

### Relative Endocrine Exposure: Activity 

### Quotient (REEAQ) (ATG_ERa_TRANS)

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### Assist ACC groups in developing science and

research projects, identifying collaborations and design of strategies for utilization of results in 

### product stewardship & regulatory activities 

## Utility of EAR and REEAQ Approaches: Proof of Concept

• R isk (Hazard & Exposure), therefore: prioritization should be (Activity &Exposure )
• EAR and REEAQ provide a scientifically sound approach for placing HTS results into context for priority setting. • GEN as a reasonable benchmark for EAR and REEAQ:

-component of a healthy diet

- [GEN] serum levels in US population available • Potential chemical candidates for deprioritization for screening and testing (e.g. EDSP) might follow: EARchemical << EARGEN (i.e., REEAQ < 1) 10

### Recommendations for the Path Forward:

Taking a Closer Look at the AUC Metric

• The AUC methodology is not sufficiently described in the EPA White Paper (but clarified to a degree by EPA’s 12/2/14 ppts to the SAP). However the non - linear transformation to yield AUC values creates complexity & complicates interpretation & this is compounded when combined with linear exposure estimates to yield IBERs. • Literature values for relative potency in estrogen assays (see EPF comments) indicate many orders of magnitude difference between strong & weak agonists (e.g . genistein is 100 to >10000 less potent than DES). • The scientific rationale for this compression of AUC values is not adequately described or discussed in the EPA White Paper. • The SAP should evaluate these issues and the Agency should address this in its response to comments / revision of the IBER profiling method for EDSP priority setting. 11

### Recommendations for the Path Forward:

Taking a Closer Look at the AUC Metric From: Appendix 1 ER AUC Scores, Reference Chemicals http://www.regulations.gov/contentStreamer?objectId=0900006481911aed&disposition=attachment&contentType=pdf

12 EPA’s DES AUC = 1.01 EPF DES Relative Potency to 17  Estradiol = 1.63E- 1 EPA’s GEN AUC = 0.77 EPF GEN Relative Potency to 17  Estradiol = 1.13E- 5

### Recommendations for the Path Forward:

Taking a Closer Look at the AUC Metric

• A Scientific Confidence Framework for evaluating the AUC methodology (adopted from Cox et al. 2014. Developing scientific confidence in HTS-derived prediction models: Lessons learned from an endocrine case study. Regul. Toxicol. Pharmacol. 69, 443 - 50.

• Analytical Validation
• Qualification
• Utilization

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### Recommendations for the Path Forward:

Taking a Closer Look at the AUC Metric Analytical Validation: Assessment of the biological basis and analytical performance of assays. • Each assay should map to a defined mechanistic endpoint (e.g., a key event in the mode of action or AOP). • Documentation of assay performance characteristics (reliability, sensitivity, and specificity) • A defined chemical domain of applicability • Transparent data sets (to enable independent verification) should be readily available. • Note: This framework was used to form the basis of the draft OECD guidance “Characterizing non -guideline in vitro test methods to facilitate their consideration in regulatory applications” 14

### Recommendations for the Path Forward:

Taking a Closer Look at the AUC Metric Qualification: Assessment of the prediction model derived from the assays . • A defined algorithm for each prediction model. • Appropriate measures of goodness-of-fit, robustness and predictivity of the prediction models (models may be quantitative or qualitative). • Known limitations of each prediction model should be summarized. • Prediction models should be characterized in sufficient detail to facilitate review, reconstruction and independent verification of results. 15

### Recommendations for the Path Forward:

Taking a Closer Look at the AUC Metric Utilization: Contextual and weight-of-evidence analysis of the use (qualitative or quantitative) of the prediction model for a specific purpose. • Defining the intended purpose of the prediction model • Documenting/justifying applications, based on weight of evidence, of the scientific confidence to support the use of the method for specific purposes: • For example: (1 ) priority setting, where the model is used to identify priority substances for more detailed evaluation; (2) chemical categorization for subsequent read - across (3) screening level assessment of a biomarker, where model is used as a surrogate data point for a biochemical endpoint or a biomarker; ( 4) integrated testing strategy, or where the model is used to describe/predict a hazard property in lieu of a traditional tox study ( 5) to predict an adverse outcome . 16Enhancing product stewardship and regulatory decision making through innovative science & research 17 

### • The approach presented in EPA’s IBER Profiling White Paper represents a significant advancement 

### in using HTS and exposure information to support decision making 

### • Additional work by EPA should be considered to improve the scientific basis of the methods used, and to fully document model development and 

### performance. 

# Thank you for your attention