## Section 3.2.2: Curated Review of Hershberger 

## Literature Section 3.2.4: Demonstration of a CompTox Approach to Evaluating AR Agonist Bioactivity for EDSP Universe

Chemicals Patience Browne Exposure Assessment Coordination and Policy Division Office of Science Coordination and Policy Office of Chemical Safety and Pollution Prevention
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# Presentation Roadmap

Androgen Receptor Bioactivity Introduction Estrogen Receptor Bioactivity Exposure Toxicokinetics/Dosimetry

Integrated Bioactivity Exposure Ranking

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# Major Points of Section  AR computational model is being developed • Following a approach similar to ER model • Expectation is that most androgen -active 

## environmental chemicals will behave as antagonists • Inherent difficulty discriminating antagonist response from cytotoxicity/overt toxicity 

##  EPA evaluated proposed application of computational tools in a fit-for- purpose 

## manner

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# Introduction  Using the same template as ER using computational tools used to evaluate A R bioactivity • 9 assays integrated into a network model 

## • 23 in vitro reference chemicals 

##  AR model will continue to develop as: • In vitro reference chemical set is expanded 

## • In vitro reference chemical potency is included • In vivo reference chemicals are defined

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# Objectives: AR Pathway
 Before using the model of AR bioactivity in EDSP framework, EPA is reviewing the 

## scientific strengths and limitation for each goal outlined in the white paper 1. Prioritize chemicals for further EDSP screening 

## and testing based on estimated bioactivity, 2. Contribute to the weight of evidence evaluation of a chemical’s potential bioactivity, 3. Substitute for specific endpoints in the EDSP Tier 1 battery FIFRA SAP: Integrated Bioactivity Exposure Ranking Dec 2 -5, 2014 Slide 5 of 19

# Proposed Methodological Approach  Use computational tools to model AR bioactivity – focus on antagonism • 6 ToxCast assays relevant to antagonist 

## pathway • Model AUC for R1 (agonist) and R2 (antagonist) activities 

##  Prioritize chemicals in EDSP universe for AR antagonist bioactivity

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# Scientific Confidence Needed



# To Use [Any] New Assay  Are reference chemicals that include a range of structures and potency, accurately 

## detected? • In vitro reference chemicals 

## • In vivo reference chemicals 

##  How well do new methods compare with current methods? • ToxCast versus Tier 1 results

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# Scientific Confidence: Reference Chemicals
 Excellent performance of ToxCast AR AUC 

## scores against in vitro reference chemicals
 Performance of ToxCast AR AUC scores 

## against in vivo reference chemicals - TBD # True Pos 14 # True Neg 8 # False Pos 0 # False Neg 1 PPV 1.0 NPV 0.89 BA 0.97 Sensitivity 0.93 Specificity 1.0

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# Evaluation of Hershberger Assays
 Search published literature  Compare studies with 7 minimum criteria to determine “guideline - like” • Animal model: castrated male rats • Sample size: >4 animals/group for positive results; > 6 animals/group for negative • Test chemical administration: oral gavage or subcutaneous injection. • Dose levels: > 2 does of chemical for agonist portion, > 3 doses of test chemical for antagonist, and appropriate positive and controls for each activity. • Duration of exposure: begin PND 49 to PND 60 and extend for a minimum of 10 days. • Tissues examined: Absolute weights of 5 accessory sex tissue weights 

###  Agonist and antagonist portions of the assay evaluated independently
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# Development of Hershberger Database  All identified chemical/manuscript pairs evaluated by 2 reviewers • ~225 chemical/article combinations 

##  Currently EPA secondary review underway • Hershberger bioassay relatively more complex than the uterotrophic bioassay 

##  Chemicals with >1 positive or negative “guideline- like” study result may be used to 

## establish in vivo reference chemicals

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# Scientific Confidence: Current Methods  How do HTS results compare with ARmediated response in validated Tier 1 assays? Tier 1 Battery AR-specific endpoints

NOTE: Full EDSP Tier 1 battery includes five in vitro and six in vivo assays that provide additional information on a chemical’s potential to interact with the androgen and thyroid, as well as alter steroidogenesis. Tier 1 Screening Battery Endocrine Pathway E + E - A + A - HPG Axis HPT

Axis In vitro A R Binding ■ ■ In vivo Hershberger ■ ■ Pubertal Male ■ ■ ■ ■ Fish Short -term Reproduction (male & female ) ■ ■ ■ ■ ■
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# Comparison of AR Model with Tier 1  Will be conducted when confidence in both in vitro and in vivo reference chemicals is well established • AR antagonist response difficult to discriminate from non -specific toxicity

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##  Chemical Space:

23 410 1444 49 ~ 10,000 56 

# AR Antagonist Bioactivity

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# AR Antagonist Bioactivity

# AR Antagonist Bioactivity

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# Appendix 3: Supplementary Data

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# Evaluating AR Model Performance  New method must be fit for purpose and ideally, perform as well or better than existing method • Possibility of greater sensitivity in HTS due to 

### redundancy of assays

– 9 assays detect multiple points in AR signaling pathway using multiple technologies 

### • AR model performance evaluated with 23 reference 

### chemicals

– T1 AR binding: 10

– T1 Hershberger: 13 

### • More reference chemicals will be include and potency will be defined
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# Evaluating AR Model Performance  Current set of reference chemicals includes many pharmaceuticals designed to target AR • 13 of 23 reference chemicals 

## • Expected to target the AR with high affinity 

##  AR model detects potent reference with a 

## balanced accuracy of 97% • Therefore, AR antagonist AUC scores in the range of reference chemicals very likely to be bioactive 

## • Strong confidence in using model for prioritization

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# Revisiting Objectives: AR Pathway  Before using model of ER bioactivity in EDSP framework, EPA is reviewing the scientific strengths and limitation for each goal outlined in the white paper 1. Prioritize chemicals for further EDSP screening and testing based on estimated bioactivity,

– List 1: 0 agonists, 8 antagonists; ~82% no activity

– List 2: 0 agonists, 6 antagonists; ~91% no activity

– Universe: 0.1% agonists, 7.8% antagonists; ~88% no activity 

### 2. Contribute to the weight of evidence evaluation of a chemical’s potential bioactivity, 3. Substitute for specific endpoints in the EDSP Tier 1 battery
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