### Slide 1 of 320 

# FIFRA Science Advisory Panel Meeting

Prioritization of EDSP
Universe of Chemicals Using Computational Toxicology Tools

Arlington, VA January 29, 2013

### Slide 2 of 320 

# Overview of the Endocrine Disruptor Screening Program

Mary Manibusan, Director Endocrine Disruptor Screening Program Office of Science Coordination and Policy Office of Chemical Safety and Pollution Prevention U. S. Environmental Protection Agency

m anibusan.mary@epa.gov

# EDSP Program Overview:

An Evolutionary Timeline:

 Background and History of the Endocrine Disruptor Screening Program: Mission and
Vision

 EDSP Comprehensive Management Plan: Timeline of Current and Future Activities

 Vision of EDSP21 Work Plan, September 2011

 Implementation of EDSP21

- Proposed EDSP21 Chemical Prioritization Scheme

Slide 3 of 320

# EDSP Mission

To protect public health and wildlife by screening and testing chemicals and taking appropriate
actions for those chemicals that are found to have
endocrine effects.

Slide 4 of 320

# Legislative Mandate

Slide 5 of 320 

#  1996 Federal Food, Drug and Cosmetic Act, section 408(p) Requires the U. S. EPA to develop a screening program using appropriate validated test systems and other scientifically relevant methods to determine whether certain substances may have an effect in humans that is similar to an effect produced by a naturally occurring estrogen, or other such endocrine effect as the Administrator may designate.

 1996 Safe Drinking Water Act Amendments, section 1457 Testing of chemical substances that may be found in sources of drinking water, if substantial human populations may be exposed.

# Endocrine Disruptor Screening and Testing Advisory Committee (EDSTAC)

1998 EDSTAC Recommendations:

 Expand Protection to Include Human Health and Wildlife

 Include Estrogen, Androgen and Thyroid Pathways

 Develop a Two

- Tiered S creening and Testing P rogram:



# Tier 1 Screening for Potential to Interact
Potential to interact with the estrogen, androgen or thyroid hormone
systems 

# Tier 2 Testing to determine Interaction with the endocrine system

If endocrine

- mediated adverse effects then quantify dose

- response relationship

Slide 6 of 320

### Slide 7 of 320 

# EDSP Tier 1 Screening Battery

**In vitro**

Estrogen Receptor (ER) Binding
Estrogen Receptor Transcriptional Activation Assay (ERTA)
Androgen Receptor (AR) Binding
Steroidogenesis

Aromatase 

# In vivo

Uterotrophic (rat)
Hershberger (rat)
Pubertal Female (rat)
Pubertal Male (rat)
Amphibian Metamorphosis Assay (frog)

Fish Short

- Term Reproduction Assay (fish)Synthesis Steroid



### X X X X X Pubertal female **In vivo** 

## In vitro

X ER Transcriptional Activation

X X 

## HPT

X X 

## HPG

X Aromatase (Recombinant)

X Uterotrophic

X X Hershberger

X X X Pubertal male X X Steroidogenesis (H295R) X X AR Binding X X ER Binding 

## E T A

- A E

- E

Amphibian Metamorphosis X X X X X X Fish Reproductive Screen Synthesis Steroid



### X X X X X Pubertal female **In vivo** 

## In vitro

X ER Transcriptional Activation

X X 

## HPT

X X 

## HPG

X Aromatase (Recombinant)

X Uterotrophic

X X Hershberger

X X X Pubertal male X X Steroidogenesis (H295R) X X AR Binding X X ER Binding 

## E T A

- A E

- E

Amphibian Metamorphosis X X X X X X Fish Reproductive Screen 

# EDSP Tier 1 Screening Assays

Slide 8 of 320

### Slide 9 of 320 

# Proposed EDSP Tier 2 Test Methods

**Mammalian**

Mammalian Two

- Generation Reproduction (Rat)
Extended One Generation Reproduction (Rat) 

# Ecological

Avian Multi

- Generation Reproduction (Japanese quail)
Larval Amphibian Growth and Development ( Xenopus laevis)

Fish Multi

- Generation Reproduction ( Medaka )

Invertebrate Multi

- Generation Reproduction ( Mysid and Copepod)

# Summary of EDSP Current Timeline

1998/1999

EDSTAC 1998 Report and formation EDSP



# 2008

- 2010

Validated Tier 1 Screening level assays, Issuance of initial test orders for List 1 and published proposed List 2 chemicals 

# 2011

EDSP21 Work Plan Summary and Weight of Evidence
Document

Slide 10 of 320 

# Tier 1 Test Method Development Tox21 Planning
And Tier 2 tests 2012 Comprehensive Management Plan

# Comprehensive Management Plan

Slide 11 of 320

# Comprehensive Management Plan

 Provides strategic guidance to EPA Staff and Managers for a 5 year time horizon

 Primary Focus on: Operations of EDSP, Test Methods Development, Advancements of Technological Methods

 Supplemental Document on EDSP Universe of Chemicals and General Validation Principles

, Nov. 2012

 Living document that will be evaluated for revision on an annual basis

• Next update October 2013

Slide 12 of 320

# Summary of EDSP Future Timeline

January 2013



# FIFRA SAP on Chemical
Prioritization

Spring

- Summer 2013
FIFRA Sap on Tier 1 data reviews, assay and

battery performance and weight of evidence analyses Spring

- Summer 2013

FIFRA SAP Review of Tier 2 assay validation efforts

Slide 13 of 320 

# Complete
Prioritization Continue Reviews Complete Tier 2
Test Guidelines

# EDSP21 Work Plan

Slide 14 of 320

# EDSP21 Work Plan Objective

 Maximize use of extant data, current and emerging technologies.

 Strategic Testing: Targeted in vivo toxicity screening.

 Use a variety of tools in a multi

- tiered testing and assessment framework.

 Systematically and incrementally incorporate new tools, methodologies and building confidence.

 Advance understanding of key events in toxicity pathways.

Slide 15 of 320

### EPA Research p rovides basis for improving the suite of assays and models to advance chemical prioritization and screening The universe of chemicals passes through each version of the HTP/ in silico pipeline to evaluate chemicals in refined tests, for new pathways, to evaluate, improve, and validate methods.

Building Confidence: “Learn by Doing” Phase 1: Incorporates HTP/ in silico prioritization methods Phase 2: Run subset of current T1S assays indicated by HTP and in silico predictions Phase 3: Full replacement of EDSP T1S Battery Chemicals Of Regulatory

Interest in vitro HTP/ in silico Current EDSP T1S Battery Test+ Near

- Term
PHASE 1

Targeted
EDSP Tier

2 Tests WOE+

WOE

in vitro HTP/ in silico in vitro / in silico to target
EDSP T1S Test+ Intermediate

– Term
PHASE 2 WOE+

WOE

in vitro HTP/ in silico (full replacement of Tier 1 battery) Longer

- Term
PHASE 3 WOE+

WOE

Slide 16 of 320

# EDSP21 Implementation

Key considerations:

 C larity of programmatic goal:

• Determine the order in which to screen chemicals for endocrine activity



#  Define domain of application and regulatory decision
contexts:

• The EDSP Universe of Chemicals to Prioritize for EDSP Screening



#  Build transparent strategy with sound scientific basis:

• OECD (Q)SAR Validation Principles



#  Ensure scientific soundness, rigor and provide an open and transparent process for public outreach

Slide 17 of 320

# EDSP Universe of Chemicals and General Validation Principles, 2012

Slide 18 of 320

# EDSP Universe of Chemicals

 The scope of the authorities established by the statutory provisions in the 1996 FFDCA and SDWA provides a chemical universe for the EDSP.

• Federal Food, Drug and Cosmetic Act, 1996 requires that all pesticide chemicals be screened

• Safe Drinking Water Act Amendment 1996 provides the agency with authority to provide testing for “any other substance that may be found in sources of drinking water if the Administrator determines that a substantial population may be exposed to such substance.”

Slide 19 of 320

# EDSP Universe of Chemicals

Chemical List Number of Compounds

Conventional Active Ingredients 838

Antimicrobial Active Ingredients 324
Biological Pesticide Active Ingredients 287
Non Food Use Inert Ingredients 2,211
Food Use Inert Ingredients 1,536
Fragrances used as Inert Ingredients 1,529
Safe Drinking Water Act Chemicals 3,616

TOTAL 10,341

Slide 20 of 320

# EDSP Tier 1 Data Review:
Current Pace

2009

- 2010

EDSP Issued Initial Tier 1 Test Orders

on 67 chemicals



# 2012

- 2013

Tier 1 Data Being Submitted to the Agency on 52 chemicals 

# 2013

- 2014

Agency Completes Tier 1 Data Reviews

Slide 21 of 320

# “ Punctuated Evolution”: Accelerated Pace

 Based on our current pace and trajectory, it c ould take decades to screen all 10,000 chemicals for potential to interact with the endocrine system

 Recent advances in computational toxicology are heralding an important “evolutionary turning point” and may ignite an accelerated pace of testing

 To address thousands of chemicals for potential to interact with the endocrine system, we must begin developing a more strategic approach to prioritize chemicals for screening

Slide 22 of 320

# Background and History: Prioritization

 1998

- EDSTAC recommended, “that existing QSAR models be derived and supplemented with data from the HTPS assays, thereby expanding the predictive ability of these models”

 1999

- SAP/SAB concluded at that time that HTP assays and (Q)SARs were not sufficiently developed for use in chemical priority setting

• Endorsed research to advance HTP in vitro assay and QSARs for future prioritization efforts



#  2007

- NAS Toxicity Testing in 21 st 

# Century: A Vision and a Strategy

• To integrate all existing knowledge and employ new in silico and in vitro technologies to accelerate the pace of testing



#  2009

- SAP was in strong agreement that the ER expert system is likely to be an important tool to support sorting and prioritizing pesticides for EDSP Tier 1 screening by ER binding mechanism

 2011

- SAP supported the use of the AOP as a conceptual framework for the application of computational tools and recommended the use of the OECD validation principles in evaluating the acceptance and utility of computational tools

Slide 23 of 320

# Proposed Prioritization Method

 Approach based on C urrent and Emerging technologies

• P hysico

- chemical properties, exposure information, together with information from in silico expert systems, read across concepts and low and high throughput in vitro assays

• Prioritization criteria established to be as inclusive as possible, starting with the least resource intensive approach



#  Demonstrated using the ER

- mediated Adverse Outcome Pathway as the “organizing framework”

• ER pathway as the initial example, but prioritization is intended to be used generically for any chemical category based expert system or MIE

– e.g. , Androgen and Thyroid



# • Note: Priorization is not yet fully completed;

– Intended to demonstrate general concepts, principles and methodology



#  OECD (Q)SAR Validation Principles to ensure overall transparency, use of clear and defined endpoint, scientifically robust, anchored by biologically plausible mechanistic understanding

Slide 24 of 320

# EDSP Universe of Chemicals n= 10,341

Chemical
Lists FIFRA Registration Review
Schedule for Active Ingredients (Approx.=1500) SDWA and INERTS (Approx.=9000)

Physico

Chemical Properties

(Approx n=5000) 

# Excluded

Exposure
Potential

SDWA 

# Lower Priority

ER Expert System

High through put
system 

# Prioritized List of Chemicals for EDSP Tier 1 Screening yes

No * Mixtures will be lower priority

no

Yes 

# Considerations of Read

Across and Chemical Categories

Slide 25 of 320

# Order of USEPA Presentations:

1. Application of Physico

- chemical Properties:

• Dr. Ray Kent, OPP


# 2. Adverse Outcome Pathway Approach and Expansion of the ER Expert System Version 2:

• Rick Kolanczyk and Dr. Pat Schmieder , ORD


# 3. Overview of High Throughput ER Binding and Gene Activation Assays and Analysis using Reference Compounds:

• Dr. Richard Judson, ORD


# 4. Preliminary Findings of Comparative Analysis of HTP and ER Expert System Training Set Data:

• Dr. Mike Hornung , ORD


# 5. Category

- based Approach to Strategic Testing to Cover Chemicals of Unknown Binding Potential:

• Rick Kolanczyk and Dr. Pat Schmieder , ORD


# 6. Summary and Synthesis of the overall Prioritization Scheme:

• Dr. Vicki Dellarco , OPP

Slide 26 of 320

### Slide 27 of 320 

# Use of Physicochemical Properties to
Exclude Chemicals from EDSP Screening

Presented by Dr. Ray Kent, Ph.D
Health Effects Division Office of Pesticide Programs Office of Chemical Safety and Pollution Prevention

# EDSP Universe of Chemicals n= 10,341

Chemical
Lists FIFRA Registration Review
Schedule for Active Ingredients (Approx.=1500) SDWA and INERTS (Approx.=9000)

Physico

Chemical Properties

(Approx n=5000) 

# Excluded

Exposure
Potential

SDWA 

# Lower Priority

ER Expert System

High through put
system 

# Prioritized List of Chemicals for EDSP Tier 1 Screening yes

No * Mixtures will be lower priority

no

Yes 

# Considerations of Read

Across and Chemical Categories

Slide 28 of 320

# Physicochemical Properties Overview

 Decisions of whether to screen a chemical for endocrine interaction are made in part based on information about a
chemical’s inherent properties

• e.g ., pK
a 

# values, molecular weight, reactivity/stability, corrosivity, known functional groups, and charged species



#  EPA may use this information to identify chemicals unlikely to be testable or to exhibit systemic effects relevant to endocrine disruption

 Application of filters based on physicochemical properties
enables EPA to reduce the chemical universe that would
need further evaluation

• As illustrated in the white paper

, from ~10,000 chemicals to ~5000 or
less

Slide 29 of 320

# History of Prioritization

 Advice from Federal Advisory Committees

• e.g. , EDSTAC, SAB/SAP



#  Sept 2005: Federal Register Notice

- Chemical Selection Approach for Initial Screening

• Polymers with number average molecular weight greater than 1000 Daltons

• Strong mineral acids and bases

• Highly reactive (corrosive) chemicals that will destroy tissue at the portal of entry leading to overt toxicity

• Defer mixtures until single chemicals are established

• Excluding chemicals that are no longer produced or used in the United States

• Excluding “positive control” chemicals used for the validation of the screening assays

Slide 30 of 320

# Proposed Exclusion Principles

 Exclusion of polymers greater than 1000 daltons

• Lower priority for mixtures



#  Exclusions based on ionization and electronic charge

• Strong acids and bases

• Charged species at pH 7



#  Exclusions based on chemical reactivity

• Chemicals that are corrosive

• Chemicals that hydrolyze in the environment

Slide 31 of 320

# Exclusions Based On Ionization and Electronic Charge

 Focus of these two criteria are acids and bases, and the salts of acids and bases

 Primary property for deciding whether a chemical is excludable is pK

a 

# , the negative log of the acid dissociation constant

 For acids, the estimated pK
a 

# is for the parent acid

 For bases, the estimated pK
a 

# is for the conjugate acid

Slide 32 of 320

#  Acid is a proton donor

HA  H + 

# + A

- 

# ( e.g acetic acid, HOAc  H + 

# + OAc

- 

# )
Acid dissociation constant K

a 

# = (H + 

# )(A

- 

# ) (HA) pK
a 

# =

- log(K

a 

# )

 Base is a proton acceptor:

B + H + 

#  BH + 

# (e.g. ammonia, NH 3 

# + H + 

#  NH 4 + 

# )
Base dissociation constant K b 

# = (BH + 

# ) (B)(H + 

# )

Base: K
a 

# of the conjugate acid = (B)(H + 

# ) (BH + 

# )

Slide 33 of 320 

# Exclusions Based On Ionization and Electronic Charge

# Exclusions Based On Ionization and Electronic Charge

 Strong acids and bases

• Basis: Concern is for testability of the chemical

– Tissue destruction in animals

– Environmental testing

– interpretation of results?



# • Chemical excluded if the lowest pK

a 

# <2 (acids) or highest pK

a 

# of conjugate acid >11.5 (bases)

• Example

– Phosphoric acid has 3 pK
a 

# s , 1.80, 6.95 and 12.9. The lowest pK

a 

# is less than 2. Exclude

– Guanidine is a strong base. The guanidinium ion is a weak conjugate acid with pK
a 

# of 12.5. Exclude

Slide 34 of 320

# Exclusions Based On Ionization and Electronic Charge

 Charged species at pH 7

• Basis: ER

- binding chemicals tend to be non

- polar

• Excludable if <1% uncharged species at pH 7

• Chemical excluded if the lowest pK

a 

# <5 (acids) or the highest pK

a 

# of the conjugate acid >9 (bases)

• Examples

– Barbituric acid has 3 pK
a 

# s , 3.95, 7.80 and 10.95. The lowest, 3.95 is less than 5, so it is excludable. Direct calculation shows 0.085 % uncharged species at pH 7

– CI Basic violet 14 is a basic dye with 3 pK
a 

# s , 8.85, 3.62 and 2.85 The highest is < 9 so it is not excludable. Direct calculation shows 1.65% uncharged species at pH 7

Slide 35 of 320

# Exclusions Based On Chemical Reactivity

 Chemicals that are corrosive/reactive

• Focus is on chemicals that cause tissue
destruction in vivo or in vitro



#  Chemicals that are unstable and hydrolyze in the environment

• Focus on the environment and chemicals that have a relatively short half

- life

Slide 36 of 320

#  Corrosive chemicals

• On Department of Transportation’s List 8 (DOT8)

• Chemical listed as corrosive on a Material Safety Data Sheet (MSDS)

• Examples

– Phosphoric acid and ammonia

▫ Also excludable as strong acid or base



# – Dodecyltrimethylammonium chloride

▫ A strong cationic detergent



# – Potassium permanganate

▫ A strong oxidizing agent

Slide 37 of 320 

# Exclusions Based On Chemical Reactivity

#  Hydrolyzable chemicals

• Arbitrary cutoff is 40 days, but lowering the half life duration to 1 day made little difference

• Examples of estimated hydrolysis half

- lives

– Isobutyric anhydride

- 0.02 days

– Peroxyoctanoic acid

- 0.67 days

– Methyl 2

- chloropropionate

- 16 days

– Aspirin

- 61 days

Slide 38 of 320 

# Exclusions Based On Chemical Reactivity

# Physico

- chemical Property Exclusions
Are Not Automated

For any chemical excluded under one or more physicochemical criteria, the basis for the exclusion should be reviewed by internal experts to determine whether the exclusion is biologically plausible and scientifically supportable

Slide 39 of 320

# Criterion Parameters Data Sources Boundaries # Chems
Excluded

Too acidic or
basic pK
a 

## of acids or conjugate acids of
bases Chemaxon's

" Chemicalize " predictive
software pK
a 

## < 2 or pK
a 

## of conjugate acid

>11.5 Approx. 700
Excluded

Too reactive
or unstable

in water Hydrolysis half

- life Epi Suite's

HYDROWIN predictive module Eligible for
exclusion if hydrolysis half

life < 40 days Approx. 100
Excluded

Charged at pH 7 pK
a 

## based net negative or positive charge at pH7 Chemaxon's

" Chemicalize " predictive
software Lowest acid pK
a 

## < 5 or highest conjugate acid pK
a 

## >9 Approx. 700
Excluded

Too corrosive Member of a
chemical class with
reactive functional

groups DOT8 list; MSDS
indicates corrosive

to skin, eyes Solid, water
insoluble
chemicals not eligible Approx. 200
Excluded 

# Summary of Physico

- Chemical Properties Exclusion Criteria

Slide 40 of 320

### Slide 41 of 320 

# Adverse Outcome Pathway Approach and Expansion of the ER Expert System Version 2

Dr. Pat Schmieder & Rick Kolanczyk Office of Research and Development National Health and Environmental Effects Research Laboratory
Mid

- Continent Ecology Division

# EDSP Universe of Chemicals n= 10,341

Chemical
Lists FIFRA Registration Review
Schedule for Active Ingredients (Approx.=1500) SDWA and INERTS (Approx.=9000)

Physico

Chemical Properties

(Approx n=5000) 

# Excluded

Exposure
Potential

SDWA 

# Lower Priority

ER Expert System

High through put
system 

# Prioritized List of Chemicals for EDSP Tier 1 Screening yes

No * Mixtures will be lower priority

no

Yes 

# Considerations of Read

Across and Chemical Categories

Slide 42 of 320

# Topics

 History of model development ESv1 (2009 SAP Review)

• Background & Principles



#  Expanding to ESv2

 Assessing Coverage of

EDSP Universe

 Affect of P

- Chem Filtering

Slide 43 of 320

# History: Expert System Development

 SAP review, 2009

• Model Domain

- ER ESv1

• Regulatory Domains

– Coverage: Food

- use Inerts (FI) and Antimicrobials



#  Additional work:

• Automated ESv1

• Expanding Domain

– Coverage: Non food

- use inerts (NFI)

– Further evaluation of additional chemical groups



#  Building ESv2

Slide 44 of 320

# 5 Goals

1) Determine ESv1 coverage of EDSP chemicals to prioritize for T1S (Sec 3)

2) Build ESv2 and determine coverage of EDSP chemicals to prioritize for T1S (Sec3)

3) Identify remaining chemicals with Unknown Binding Potential ( UnkBP ) i.e. , those outside ESv2 model domain (Sec 3)

4) Determine where HTP data covers UnkBP chemicals (Sec 8)

5) Determine if and how HTP data could be used to expand TrSet to

cover UnkBP chemicals. (Sec 4, 5, 6, 7, 8) ESv1 (SAP, 2009)

ESv2

ESv3 

# Moving Incrementally Building from Initial Steps to Address New Challenges EDSP Universe (FI, NFI, Frag , SDWA)

Slide 45 of 320

# Mechanistic Basis of the Expert System

 Adverse Outcome Pathway (AOP) context

 OECD QSAR Principles

 In vitro Assays designed for purpose

Slide 46 of 320

# ER

- mediated Reproductive Impairment Adverse Outcome Pathway

Chemical Effects Across Levels of Biological Organization

In vitro Assay

focus area QSAR
focus

area

Chemical Exposure

Receptor Binding



## ER Binding Liver Cell
Protein Expression



## Vitellogenin
(egg protein transported to ovary) 

## Liver 

## Altered proteins, hormones;

Gonad


## Ova

- testis Sex reversal;

Altered behavior;

Repro. In vivo

MOLECULAR Initiating Event CELLULAR Response TISSUE/ORGAN INDIVIDUAL



## Skewed Sex Ratios;

Yr Class POPULATION



# Toxicity Pathway
Adverse Outcome Pathway

Greater Toxicological Understanding Greater Risk Relevance 

# In vivo Mechanistic linkage between the risk assessment endpoint (ER

- mediated reproductive impairment) and the hazard identification endpoint (MIE: ER binding)

Slide 47 of 320

# ER Binding Affinity: An Indicator of Potential Reproductive Effects

 Mechanistic linkage exists between the risk assessment endpoint (ER

mediated reproductive impairment) and the hazard identification endpoint (ER binding)

 Foundation of the assays used to build the Expert System is an adverse outcome pathway (AOP) ending in reproductive impairment

• The molecular initiating event (MIE) of the pathway is identified (ER binding)

• The expert system identifies which chemical structures can initiate the pathway

• Pathway context provides conceptual model useful for generating testable hypotheses

• Pathway context provides decision

- making rationale for the regulatory community



#  ER

- mediated Adverse Outcome Pathway

• Area of focus consistent with legislative directive

• Chemical binding to the ER is known to have potential to cause adverse effects

• Evidence existed that diverse chemical structures bind ER

Slide 48 of 320

# ER

- mediated Reproductive Impairment Adverse Outcome Pathway

Chemical Effects Across Levels of Biological Organization

In vitro Assay
TrSet
focus area Expert System
focus area

Chemical Exposure

Receptor Binding



## ER Binding Liver Cell
Protein Expression



## Vitellogenin
(egg protein transported to ovary) 

## Liver 

## Altered proteins ( Vtg ) Sex reversal;

Altered behavior;

Repro. In vivo

MOLECULAR Initiating Event CELLULAR Response TISSUE/ORGAN INDIVIDUAL



## Skewed Sex Ratios;

Yr Class POPULATION



# Toxicity Pathway
Adverse Outcome Pathway

Greater Toxicological Understanding Greater Risk Relevance 

# In vivo Mechanistic linkage between the risk assessment endpoint (ER

- mediated reproductive impairment) and the hazard identification endpoint (MIE: ER binding)

Slide 49 of 320

# • Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question? 

# Application of OECD Principles:
Desired Outcomes

• Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?

Slide 50 of 320

# OECD Principles for QSAR Validation

 Well

- Defined Endpoint

– ‘Bioassay Domain’

• Well

- defined biological endpoint

–

– Informing important risk endpoint

–

▫ AOP ending in impaired reproduction; plausible linkage of MIE to higher level adversity



# – Interpreting the measurements

▫ Measurement endpoint and confounding factors



# • Well

- defined chemistry

– Using in vitro assays that allow testing of the types of chemicals (range of properties) found on regulatory inventories

– Understanding of chemical form and concentration in the assays

 Mechanistic interpretation

• Being able to explain the predictions mechanistically

– With respect to chemistry & biology



# • Relationship of predicted parameter to regulatory question

– ER

- mediated Reproductive Impairment AOP



# • Relationship of chemical parameters to biological activity

Slide 51 of 320

#  Defined Model Applicability Domain

• Well

- defined application

– Regulatory question

– priority setting is different than risk assessment

– Expert System model domain coverage well

- defined

▫ Decision tree, logic rules, local in vitro TrSets upon which rules are based



# – Expert System model domain adequately covers the Regulatory C hemical domain

▫ Fooduse pesticidal Inerts (FI) ; Antimicrobials (AM)



#  Appropriate measures of goodness of fit, robustness, ability to predict

• Measures appropriate for a regression model are not appropriate to evaluate an expert system logic rules

– Series of local models, local in vitro TrSets , “unknown” structure compared to tested chemicals



#  Unambiguous algorithm

• Expert Systems

– logic tree, rules/queries, supporting information

Slide 52 of 320 

# OECD Principles for QSAR Validation

# • Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?



# Application of OECD Principles
Desired Outcomes:

• Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?

Slide 53 of 320

# ER Expert System

– Effects

- Based Chemical Categories Approach Chemical Similarity

Building Effects

- based Categories: Structural similarity

- context of the biological activity

- ER

- mediated AOP

Multiple ER

- interaction types

- chemicals interacting at different points (‘A’, ‘B’) have different properties

Chemicals sharing similar structural features are grouped if impart same biological activity - chemicals initiating MIE at same point are ‘similar’

Slide 54 of 320

# R 394 E 353 H 524 

# C T 347

HO 

# A B “

A_site only” Interaction

CH 3



# J. Katzenellenbogen Q Oxygen 

# =

- 0.25

Slide 55 of 320

# R 394 E 353 H 524 

# C T 347



# A B “ B_site only” Interaction

H 3 

# C NH 2



# J. Katzenellenbogen Q Oxygen 

# =

- 0.32

Slide 56 of 320

# • Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?



# Application of OECD Principles
Desired Outcomes:

• Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?

Slide 57 of 320

# Usefulness for the Defined Regulatory Purpose

• 

# Prioritizing chemicals from specific inventories

• FI and AM inventories were covered by ESv1

• No steroidal

- type chemical structures

• Low affinity ER interactions

• In vitro assays to build training set ( TrSet ) optimized to detect any indication of binding and gene activation to increase confidence in Nonbinders

• Test to chemical solubility/cytotoxicity

• Additional information used in data interpretation

• Using a effects

- based chemical category approach and read

- across concepts

• Allow extrapolation from smaller number of TrSet chemicals to broader inventory

• RBA to LogK ow 

# relationship within chemical groups

Slide 58 of 320

# • Prioritizing chemicals from specific inventories

• FI and AM inventories were covered by ESv1

• No steroidal

- type chemical structures

• Low affinity ER interactions

• In vitro assays to build training set ( TrSet ) optimized to detect any indication of binding and gene activation to increase confidence in Nonbinders

• Test to chemical solubility/cytotoxicity

• Additional information used in data interpretation

• Using a effects

- based chemical category approach and read

- across concepts

• Allow extrapolation from smaller number of TrSet chemicals to broader inventory

• RBA to LogK ow 

# relationship within chemical groups

Slide 59 of 320 

# Usefulness for the Defined Regulatory Purpose

# • Prioritizing chemicals from specific inventories

• FI and AM inventories were covered by ESv1

• No steroidal

- type chemical structures

• Low affinity ER interactions

• In vitro assays to build training set ( TrSet ) optimized to detect any indication of binding and gene activation to increase confidence in Nonbinders

• Test to chemical solubility/cytotoxicity

• Additional information used in data interpretation

• Using a effects

- based chemical category approach and read

- across concepts

• Allow extrapolation from smaller number of TrSet chemicals to broader inventory

• RBA to LogK ow 

# relationship within chemical groups

Slide 60 of 320 

# Usefulness for the Defined Regulatory Purpose

# Data Example

- Primary in vitro Assay Used: Estrogen Receptor Binding Displacement Assay Cyto rtER rtER Binding

0 10 20 30 40 50 60 70 80 90 100 110 120

-10 -9 -8 -7 -6 -5 -4 -3 -2 Log Concentration (M) E 2 VN

HCP

CRTL HOB

OHP[3H]-E2Binding (%) 

### rtER

Positive Control:
Estradiol Test Chemicals: Negative response

CTRL 

## 0 10 20 30 40 50 60 70 80 90 100 110 120

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 E 2 P

PNEP PNMP

PNBP PNPrP

PIPrP



## Log Concentration (M)[3H]-E2Binding (%)



### Positive Control:
Estradiol Test Chemicals: Positive response



## RBA = relative binding affinity; (a ratio of measured chemical affinity for the ER relative to 17

- beta

- Estradiol = 100%) Log K
ow 

## = Log of octanol/water partition coefficient ); indicator of lipophilicity

Slide 61 of 320

# Data example

– Confirmatory in vitro Assay:
Gene Activation

CTRL 

### 0.00001

0.0001

0.001

0.01

0.1

1 10

-10 -9 -8 -7 -6 -5 -4 -3 -2 PTOP PTAP E2 control



### Log Concentration (M)Vtg mRNA (Fraction of maximum E2efficacy)



### 0.0001

0.001

0.01

0.1 1 10

-10 -9 -8 -7 -6 -5 -4 -3 -2 IAB E 2 control

CTRL



### Log Concentration (M)Vtg mRNA (Fraction of maximum E2efficacy) 

### Positive Control:
Estradiol Positive Control:
Estradiol

Test Chemical: Negative response Test Chemicals: Positive response

Slide 62 of 320-5logM -4logM -3logM -2logM -3.9logM -2.9logM -1.9logM -0.9logM 0.1logM 0 20 40 60 80 100 120 140 160Percent of Nominal Concentration 

# A)

cytosol stocks

-4logM -3logM -2.7logM -2.3logM -2logM -1.7logM -4.9logM -3.9logM -3.6logM -3.2logM -2.9logM 0 20 40 60 80 100 120 140 160Percent of Nominal Concentration 

# C)

cytosol stocks -5logM -4.7logM -4logM -3.7logM -3.9logM -2.9logM -1.9logM -0.9logM 0 20 40 60 80 100 120 140 160Percent of Nominal Concentration 

# B)

cytosol stocks

-4log M -3logM -4.9logM -3.9logM -2.9logM -1.9logM -0.9logM 0 20 40 60 80 100 120 140 160Percent of Nominal Concentration 

# D)

cytosol stocks 

# Chemical Identity and Concentration Measured in ER Binding Assays

Slide 63 of 320

# Total vs. free concentration of p

- octylphenol in an estrogenicity reporter gene assay

Used with permission of J. Hermens, Utrecht University -9 -8 -7 -6 -5 -4 0 100000 200000 300000 400000 5% serum

20% serum

50% serum

log nominal conc. (M)response

-9 -8 -7 -6 -5 -4 0 100000 200000 300000 400000 

### 5% serum

20% serum

50% serum

log free conc. (M)response 

## Nominal / total concentration

Free aqueous concentration 

# Dose Assay total protein affects chemical bioavailability; Total chemical concentration must be increased as assay total protein increases to
achieve a constant free fraction of chemical needed to achieve ER

- mediated gene activation.

Slide 64 of 320

# Assay Total Protein Affects Chemical Bioavailability (Free Fraction)

-11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 10 20 30 40 50 60 70 80 90 100 110



## Concentration (log M)% Specific Binding 

### E2 Phenol

cyto rtER rec rtERα

E2

Phenol

Total
Protein (mg/mL) 4 0.01

RBA (%) 0.000026 0.0025 

# Lower total assay protein, lower applied chemical conc

Higher total assay protein, higher applied chemical conc Same chemical
free fraction displacing 3 

# H

- E2

Slide 65 of 320

# Usefulness for the Defined Regulatory Purpose

Defined Regulatory Purpose:

• Prioritizing chemicals from specific inventories

• FI and AM

• No steroidal

- type chemical structures

• Low affinity ER interactions

• In vitro assays to build training set ( TrSet ) optimized to detect any indication of binding and gene activation to increase confidence in Nonbinders

• test to chemical solubility/cytotoxicity)

• Using a effects

- based chemical category approach and read

- across concepts

• allow extrapolation from smaller number of TrSet chemicals to broader inventory

• RBA to LogK ow 

# relationship within chemical groups

Slide 66 of 3201E

- 06 1E

- 05 0.0001

0.001

0.01

0.1

1 2 3 4 5 6 7 8Relative Binding Affinity

Log Kow Symbols

- Site A chemical groups

- diamonds Symbols

- Site B chemical groups

- triangles 

# Site A

Site B 

# Site A & Site B
Chemicals with RBA > 0.00001%

46 diverse chemicals assayed
with LogK OW 

# <1.3;
all had RBA < 0.00001%

Slide 67 of 320

# • Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?



# Application of OECD Principles
Desired Outcomes:

• Transparency

- Can the QSAR estimate be explained mechanistically?

- How reasonable is an estimate compared with data for similar chemicals?



# • Usefulness

- Are the predictions applicable to all the chemicals of regulatory concern?

- Does the model/expert system answer the regulatory question?



# Predictions were provided for all chemicals on FI & AM inventory ~ 5% of chemicals were prioritized

Slide 68 of 320

#  ER binding affinity interspecies comparisons

 Expanding to additional inventories, other data types, additional endpoints 

# Also addressed in
EPA SAP 2009 Review

Slide 69 of 320

#  ER binding affinity interspecies comparisons

 Expanding to additional inventories, other data types, additional endpoints

Slide 70 of 320 

# Also addressed in
EPA SAP 2009 Review

# ER Relative Binding Affinity (RBA) rat uterine cytosol ER

_ trout liver cytosol ER

55 diverse chemicals

Similar chemical bioavailability (total protein) in each system

0.0001

0.001

0.01

0.1 1 10 100 1000

0.0001 0.001 0.01 0.1 1 10 100 1000 

# ER Relative Binding Affinity (RBA) for 55 Diverse Chemicals

rat uterine cytosol ER

trout liver cytosol ER

Similar chemical bioavailability (total protein) in each system

Slide 71 of 320

# Assay Total Protein Affects Chemical Bioavailability (Free Fraction)

-11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 10 20 30 40 50 60 70 80 90 100 110



## Concentration (log M)% Specific Binding 

### E2 Phenol

cyto rtER rec rtERα

E2

Phenol

Total
Protein (mg/mL) 4 0.01

RBA (%) 0.000026 0.0025 

# Lower total assay protein, lower applied chemical conc

Higher total assay protein, higher applied chemical conc Same chemical
free fraction displacing 3 

# H

- E2

Slide 72 of 3200.00001 0.0001

0.001

0.01

0.1

1

1 2 3 4 5 6 7 8RBA %

log K ow rec rtER rec hER

cyto rtER 

# Log K
ow 

# and RBA for Alkylphenols (A

- type Binders)

Rec rtER

- low total protein Rec hER

- low total protein

Cyto rtER

- high total protein

4

- alkylphenols

Slide 73 of 3200.00001 0.0001

0.001

0.01

0.1

1

1 2 3 4 5 6 7 8RBA (%)

log Kow rec rtERa rec hERa

cyto rtER 

### 4

- alkylanilines 

# Log K
ow 

# and RBA for Alkylanilines (B

- type Binders)

Rec rtER

– low total protein Rec hER

– low total protein

Cyto rtER

– high total protein

Slide 74 of 320

#  ER binding affinity interspecies comparisons

 Expanding to additional inventories, other data types, additional endpoints

Slide 75 of 320 

# Also addressed in
EPA SAP 2009 Review

# History: Expert System Development

 2009 SAP review

• Model Domain

- ER ESv1

• Regulatory Domains

– Coverage: Food

- use Inerts (FI) and Antimicrobials



#  Additional work:

• Automated ESv1

• Expanding Domain Coverage:

• Non Food

- use inerts (NFI)

– further evaluation of additional chemical groups



#  Building ESv2

Slide 76 of 320

### 77 Contains

a Cycle Yes

Log K OW <1.3

“Special

Rule” Applies

Site “A”
Contains Phenol Fragment

Log Kow Range

4

- Alkylanilines ( 1.4

- 5.1)

4

- Alkoxy Anilines ( 2.6

- 3.7)
Phthalates ( 2.5

- 6.8)
Phenones

- (branched) ( 2.7

- 4.8)

4

- Alkyl c yclohexanols ( 2.4

- 3.8)

4

- Alkyl cyclohexanones ( 2.4

- 3.8) *

2

- ; 4

- ; or 2,4,6

- Benzoates (substitution

- dependent Log Kows) Possible Low Affinity

Site A

- Type, Site B

- Type

Site “B” Contains “Specified” Fragment Log Kow Range Alkylphenols (1.5

- 8.0) Alkoxy phenols (2.3

- 4.3)
Parabens (1.9

- 5.4) Salicylates (2.5

- 5.1) Belongs to
known Active

Sub

- class RBA > 0.00001% Yes

No



## VI

Unknown Binding Potential No

Yes

Yes

No Yes

Belongs to
known Active

Sub

- class

Belong to untested class

Unknown Binding Potential Mixed Phenols

No 

## VII No Belongs to
known Inactive
Sub

- class

Log Kow Range

4

- n

- Alkylfluorobenzenes ( 2.3

- 4.9) Alkylphenol (2,6

- subst) ( 4.2)
Benzamides ( 1.7

- 2.1)

Borate Esters (

- 0.5

- 1.0) Benzoates (non

- ring subst) ( 3.6

- 4.2)

Bis

- anilines ( 1.6

- 6.2) Hydrofurans (alcohol & ketone) ( 0.0

- 1.2)
Imidazolidines (

- 0.9

- 0.6)
Isothiazolines ( 0.6

- 2.5)

Mono

- cyclic Hydrocarbons ( 2.7

- 4.6)
Oxazoles (<0.3) Phenones (n

- alkyl) ( 1.6

- 4.1) Pyrrolidiones (

- 0.4

- 3.3)
Sorbitans ( 3.2

- 5.9)

Triazines (

- 0.4

- 3.4) Yes DDT

- Like
Tamoxifen

- Like Multicyclic hydrocarbons Alkylchlorobenzenes Thiophosphate Esters

Yes No

No Yes

RBA > 0.00001% RBA < 0.00001% 

## I

RBA < 0.00001%

Yes No 

## V III

Contains a Charge No

Yes 

## II

Exact match to Mixed Phenols Training Set Structure and
measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes

Unknown Binding Potential Mixed Organics No

Exact match to Mixed Organics Training Set Structure and
measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes Unknown Binding Potential Exact match to Group Training Set Structure
and measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes Alkylaromatic Sulfonic Acids

Log Kow (

- 0.6

- 5.7) Sulfonic Acid Dyes

Log Kow (

- 0.4

- 6.0)

4

- Alkylbenzthiols

Log Kow ( 2.9

- 4.2)
Miscellaneous Functional

Groups w/ Charge Contains a phenolic OH, and additional

OH and/or =0 

## IV

Meets specific distance
criteria for:
Sites “A

- B”;
Sites “A

- C”;
Sites “A

- B

- C”

Contains some attenuating feature,

steric or other

High Affinity
“A

- B”;“A

- C” or “A

- B

- C”
RBA > 0.1%

RBA < 0.00001%

Low Affinity
“A

- B”,“A

- C” or “A

- B

- C”
0.00001% < RBA < 0.1% Strength of
attenuation factors Yes

No

Strong Weak ER ESv1
Start Here:
Chemical List



### Slide 77 of 320

# Automation of the ER Expert System

Built through collaborative effort between EPA, OECD and LMC

Slide 78 of 320

#  Rules based logic decision tree
Yes/No decision based dendroid logic scheme

Slide 79 of 320 

# Automation of the ER Expert System

#  Single chemical profiling or inventory list

Slide 80 of 320 

# Automation of the ER Expert System

#  Single chemical or inventory list

Slide 81 of 320 

# Automation of the ER Expert System

#  Rules defined for nodes specific to chemical groups
Boundaries based upon structural fragments, calculated parameters, test results for rtER

- binding and liver slice gene activation assays

Slide 82 of 320 

# Automation of the ER Expert SystemCAS 65405

- 77

- 8 LogKow 4.28

cis

- 3

- Hexenyl salicylate



### Slide 83 of 320

### Training Set for: Aniline (RBA<0.00001%), and 4,n

- alkylanilines 1.3<LogKow<5.1

Notes on Interpretation : Aniline and a series of 4,n

- alkylanilines were tested for rainbow trout ER affinity and gene activation. Aniline (LogKow=0.90) did not bind while 4,n

- methyl

- , ethyl

- , propyl

- , butyl

- , pentyl

- , and octylaniline all bound rtER. Additionally, 4,t

- butylaniline al so bound rtER. All 8 alkylanilines also induced VTG mRNA in trout liver slices. Therefore, 4

- alkylanilines of LogKow between 1.3 and 5.2 would be predicted to bind with a high degree of confidence; 4,t

- substituted alkylanilines in this LogKow range are also likely to bind.

Alkylanilines of Log Kow > p,n

- octylaniline (5.12), or with ortho

- or meta

- alkylsubstituents are outside of the domain of the tr aining set. LogKow = 4.06 est
CAS# N H 2

C H 3 LogKow = 3.05 m
CAS# 104

- 13

- 2
RBA = 0.00040 N H 2 C H 3

LogKow = 1.96 m
CAS# 589

- 16

- 2
RBA = 0.000047 N H 2 C H 3

LogKow = 2.40 m

CAS# 2696

- 84

- 6
RBA = 0.00011 C H 3 N H 2 C H 3 N H 2

LogKow = 1.39 m
CAS# 106

- 49

- 0
RBA = 0.000007

LogKow = 5.12 est C H 3 N H 2

CAS# 16245

- 79

- 7
RBA = 0.00089 LogKow=3.39 m
CAS# 33228443
RBA = 0.0011 Log Kow = 4.06 est
CAS# 33228454
RBA=0.0015 N H 2

C H 3 N H 2

C H 3 N H 2

LogKow = 0.90 m
CAS# 62533
RBA<0.000001%

LogKow = 2.70 m
CAS# 769926
RBA=0.000098 C H 3

C H 3

C H 3 N H 2 

### Training Set for related group: 4,t

- alkylanilines:

1E

- 06 1E

- 05 0.0001

0.001

0.01

0.1

1 3 5 7RBA

Log Kow



### Slide 84 of 320

# History: Expert System Development

 SAP review, 2009

• Model Domain

-

• Regulatory Domains

– Coverage: Food

- use Inerts (FI) and Antimicrobials



#  Additional work:

• Automated ESv1

• Expanding Domain Coverage:

– Non food

- use inerts (NFI)

– further evaluation of additional chemical groups



#  Building ESv2

Slide 85 of 320

# ER Expert SystemV1 (SAP, 2009) in vitro TrSet was built to cover:

- Food

- use inerts (FI)

- Antimicrobial pesticides (AM )

ER Expert SystemV2 started in 2009 as an expansion of ESv1 to cover:

- ~1500 non food

- use inert (NFI) ingredients in pesticides (2009 NFI list)

- in vitro results available early 2012 were coded into ESv2 

# Expanding Expert System To Cover a New Regulatory Chemical Domain

Steps used to develop ESv1 (pre

- 2009) are used to expand to ESv2 :

- Acquire specific inventories requiring prioritization (NFI 2009)

- Characterize structures in the inventories

- Chemical Substance Sorting And Structural Verification (SAP, 2009)

- Assess initial coverage by ESv1 to focus on UnkBP chemicals

- chemicals in known classes but outside tested LogKow range

- identify new groups in Mixed Phenols & Mixed Organics

- Strategically expand knowledgebase (KB) of ER binding ( in vitro TrSet ) to cover new chemicals/chemical categories

- use optimized assays for detecting low affinity binding

Slide 86 of 320

# Looking for New Groups in Mixed Phenols & Mixed Organics

 Collect those structures with multiple functionalities not classified under well defined nodes

 May encounter specific functionalities that will render a specific structure positive or negative to ER

- binding

 Generate and test hypotheses

• Iterative process

Slide 87 of 320

# Common Structures (Analogs) Grouped from Mixed Phenols

LogKow = 3.79 CLogP
CAS# 131

- 57

- 7 O

O H O C H 3

LogKow = 0.80 CLogP
CAS# 4065

- 45

- 6 O

O H O C H 3 S O O O H

LogKow = 2.20 CLogP
CAS# 131

- 55

- 5 O

O H O H

O H O H

LogKow = 3.01 msrd

CAS# 131

- 56

- 6 O

O H O H

LogKow = 7.29 CLogP
CAS# 1843

- 05

- 6 O

O H O C H 3 

# Inventory

– Antimicrobials; Food

- use Inerts; Non

- Food Use Inerts (2009)

Approach: 1) Group chemicals with structural similarity

O
OH 

# 2

- Hydroxybenzophenone

Not Phenol, Ketone, Alkoxyphenol , or Sulfonic acid 2) Look for largest common structural fragment

Slide 88 of 320

## a) Q: Does the root structure HBO (non

- inventory) bind to rbtER ? 3) Strategic selection of chemicals for testing in assays

b) tested HBO

– positive for binding to rtER c) Q: Effect of an additional hydroxy

- group on the A

- ring? d) tested DHDPK

– positive for binding to rtER e) Q: Effect of multiple hydroxylation on both rings? f) tested THBP

– positive for binding to rtER g) Q: Effect of 4

- methoxy

- group in place of phenol? h) tested HMBP

– positive for binding to rtER
i ) Q: Effect of longer alkyloxy

- chain? j) tested HOB

– negative for binding to rtER k) Q: Effect of sulfonate?

4) Conclusion: 2

- Hydroxybenzophenones are a positive group; exceptions are when some degree of attenuation exists. HOB

– steric hinderance invoked by long alkyl chain. BHMB

- pKa (phenol)=7.57, pKa ( sulfonoxy )=

- 2.42, charged species.


# 2

- Hydroxy Benzophenones (new group out of Mixed Phenols)

Rainbow Trout Training Set O
OH

HOB LogKow = 7.29 CLogP
CAS# 1843

- 05

- 6

RBA = NB

O

O H O C H 3

THBP LogKow = 2.20 CLogP
CAS# 131

- 55

- 5
RBA = 0.1077 O

O H O H

O H O H

DHDPK LogKow = 3.01 msrd

CAS# 131

- 56

- 6
RBA = 0.032 O

O H O H

HBO LogKow = 3.52 msrd

CAS# 117

- 99

- 7
RBA = 0.00097 O

O H

BHMB LogKow = 0.80 CLogP
CAS# 4065

- 45

- 6

RBA = NB O

O H O C H 3 S O O O H

HMBP LogKow = 3.79 CLogP
CAS# 131

- 57

- 7
RBA = 0.001013 O

O H O C H 3 

## l) tested BHMB

- negative for binding to rtER

Slide 89 of 320

# Phenones

O

C H 3 O

C H 3



# Rainbow Trout Training Set

ACP LogKow = 1.63 msrd

CAS# 98

- 86

- 2 HXP LogKow = 3.64 KWIN
CAS# 942

- 92

- 7 HP LogKow = 4.13 KWIN
CAS# 1671

- 75

- 6 pMBA LogKow = 2.26 KWIN
CAS# 104

- 87

- 0

C H 3 O

ACP LogKow = 1.63 msrd

CAS# 98

- 86

- 2 pMBA LogKow = 2.26 KOWWIN
CAS# 104

- 87

- 0 O

C H 3

LogKow = 1.47 msrd

CAS# 100

- 52

- 7 LogKow = 5.70 CLogP
CAS# 21145

- 77

- 7 LogKow = 5.70 CLogP
CAS# 1506

- 02

- 1 C H 3 C H 3 C H 3 C H 3 C H 3 C H 3

C H 3 O O

C H 3 C H 3 C H 3 C H 3 C H 3 C H 3

C H 3 O C H 3 C H 3 C H 3 O

C H 3 C H 3 O

C H 3 C H 3 O

C H 3

C H 3

IBP LogKow = 2.73 msrd

CAS# 611

- 70

- 1 MPPK LogKow = 3.00 msrd

CAS# 938

- 16

- 9 IVP LogKow = 3.07 KWIN
CAS# 582

- 62

- 7



# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009) O

C H 3 C H 3 O

C H 3

C H 3 O

TPH LogKow = 4.84 KOWWIN
CAS# 2844

- 09

- 9



### Slide 90 of 320O

C H 3 O

C H 3



# Rainbow Trout Training Set

ACP LogKow = 1.63 msrd

CAS# 98

- 86

- 2

RBA = NB HXP LogKow = 3.64 KWIN
CAS# 942

- 92

- 7

RBA = NB HP LogKow = 4.13 KWIN
CAS# 1671

- 75

- 6

RBA = NB pMBA LogKow = 2.26 KWIN
CAS# 104

- 87

- 0

RBA = NB

C H 3 O

ACP LogKow = 1.63 msrd

CAS# 98

- 86

- 2

RBA = NB pMBA LogKow = 2.26 KOWWIN
CAS# 104

- 87

- 0

RBA = NB O

C H 3

LogKow = 1.47 msrd

CAS# 100

- 52

- 7 LogKow = 5.70 CLogP
CAS# 21145

- 77

- 7 LogKow = 5.70 CLogP
CAS# 1506

- 02

- 1 C H 3 C H 3 C H 3 C H 3 C H 3 C H 3

C H 3 O O

C H 3 C H 3 C H 3 C H 3 C H 3 C H 3

C H 3 O C H 3 C H 3 C H 3 O

C H 3 C H 3 O

C H 3 C H 3 O

C H 3

C H 3

IBP LogKow = 2.73 msrd

CAS# 611

- 70

- 1

RBA = 0.000074 MPPK LogKow = 3.00 msrd

CAS# 938

- 16

- 9

RBA = 0.000092 IVP LogKow = 3.07 KWIN
CAS# 582

- 62

- 7

RBA = 0.000070



# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009) O

C H 3 C H 3 O

C H 3

C H 3 O

TPH LogKow = 4.84 KOWWIN
CAS# 2844

- 09

- 9

RBA = 0.0012 

### Slide 91 of 320 

# Phenones

# Phenones

- Branched

C H 3 C H 3 C H 3 O

C H 3 C H 3 O

C H 3 C H 3 O

C H 3 C H 3 O

C H 3

C H 3 

# Rainbow Trout Training Set

IBP LogKow = 2.73 msrd

CAS# 611

- 70

- 1

RBA = 0.000074 MPPK LogKow = 3.00 msrd

CAS# 938

- 16

- 9

RBA = 0.000092 IVP LogKow = 3.07 KOWWIN
CAS# 582

- 62

- 7

RBA = 0.000070 TPH LogKow = 4.84 KOWWIN
CAS# 2844

- 09

- 9

RBA = 0.0012



# Phenones (n

- alkyl)

C H 3 O O

C H 3 O

C H 3 

# Rainbow Trout Training Set

ACP LogKow = 1.63 msrd

CAS# 98

- 86

- 2

RBA = NB HXP LogKow = 3.64 KOWWIN
CAS# 942

- 92

- 7

RBA = NB HP LogKow = 4.13 KOWWIN
CAS# 1671

- 75

- 6

RBA = NB pMBA LogKow = 2.26 KOWWIN
CAS# 104

- 87

- 0

RBA = NB O

C H 3

C H 3 O

ACP LogKow = 1.63 msrd

CAS# 98

- 86

- 2

RBA = NB pMBA LogKow = 2.26 KOWWIN
CAS# 104

- 87

- 0

RBA = NB O

C H 3

LogKow = 1.47 msrd

CAS# 100

- 52

- 7 LogKow = 5.70 CLogP
CAS# 21145

- 77

- 7 LogKow = 5.70 CLogP
CAS# 1506

- 02

- 1 C H 3 C H 3 C H 3 C H 3 C H 3 C H 3

C H 3 O O

C H 3 C H 3 C H 3 C H 3 C H 3 C H 3

C H 3 O 

# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009) Slide 92 of 320

# Expansion of ESv1 to ESv2

– Proposed New Groups Extracted from Mixed Phenols

N N

OH 

## Naphthalenol

- Azophenyl

N

N N OH 

## Benzotriazole Phenol

O
OH 

## 2

- Hydroxy Benzophenone

OH N CH 3 H 3 C 

## Dimethylamino Phenol

S O O

HO

OH S O O

HO

OH R1 R1

R1 R1 

## Phenolsulfophthalein & Hindered

O O O

OH

HO O O O

OH

HO R1 R1

R1 R1 

## Fluorescein & Hindered

Slide 93 of 320

# Benzotriazole Phenol

Rainbow Trout Training Set

Non

- Food Use Inerts (2009) Inventory BMBP LogKow = 7.63 CLogP
CAS# 3147

- 75

- 9

RBA = NB

LogKow = 7.03 CLogP
CAS# 3896

- 11

- 5 HMP LogKow = 4.31 CLogP
CAS# 2440

- 22

- 4

RBA = NB N N O H

C H 3 N C H 3 C H 3 C H 3 O H

N

N Cl N

C H 3

LogKow = 8.00 CLogP
CAS# 23328

- 53

- 2 LogKow = 8.00 CLogP
CAS# 25973

- 55

- 1 N N O H C H 3

C H 3 N C H 3 C H 3 O H

N

N N

C H 3 C H 3

C H 3 C H 3

LogKow = 5.81 CLogP
CAS# 84268

- 33

- 7 C H 3 C H 3 C H 3 O H

N

N N

O O C H 3 N N O H

C H 3
C H 3

C H 3

C H 3

C H 3 N

BMBP LogKow = 7.63 CLogP
CAS# 3147

- 75

- 9

RBA = NB N N O H

C H 3 N

HMP LogKow = 4.31 CLogP
CAS# 2440

- 22

- 4

RBA = NB N N O H

C H 3
C H 3

C H 3

C H 3

C H 3 N N

N N OH



### Slide 94 of 320

# Phenolsulfonphthaleins

Rainbow Trout Training Set

Non

- Food Use Inerts (2009) Inventory

LogKow = 2.78 msrd

CAS# 76

- 59

- 5 C H 3
Br

O H

C H 3 C H 3 C H 3

Br

O

H

C H 3 C H 3 O S O O

Br

O H Br S O

O

O

Br

O H
Br

BPB LogKow = 4.88 msrd

CAS# 115

- 39

- 9

RBA = NB PR LogKow = 3.02 msrd

CAS# 143

- 74

- 8

RBA = 0.000101 O H S O

O

O

O H Br

O H Br S O

O

O

Br

O H
Br

BPB LogKow = 4.88 msrd

CAS# 115

- 39

- 9

RBA = NB PR LogKow = 3.02 msrd

CAS# 143

- 74

- 8

RBA = 0.000101 O H S O

O

O

O H S O O

HO

OH

S O O

HO

OH R1 R1

R1 R1



### Slide 95 of 320

# Expansion of ESv1 to ESv2

– Proposed New Groups Extracted from Mixed Organics

Phosphorous Acid

Esters Phosphoric Acid

Esters

Amino Anthracenediones Morpholines

Sugars Alcohols

P O

O O R1

R1

R1 P O

O O R1

R1 R1 O

O

O NH 2

NH 2 OH

O

OH HO HO OH

O

HO HO HO HO HO

OH

OH HO HO O

O O

HN " R1 OH H N CH 3

O 

## Acetanilides

Anhydrides

H 3 C O CH 3 O O



### Slide 96 of 320

# Amino Anthracenedione

O O

N H

C H 3 N H C H 3 

# Rainbow Trout Training Set

Non

- Food Use Inerts (2009) Inventory QGS LogKow = 8.00 KowWin
CAS# 128

- 80

- 3

RBA = NB O O

N H 2

N H 2
DAAQ LogKow = 3.00 msrd

CAS# 128

- 95

- 0

RBA = NB SBII LogKow = 7.20 KowWin
CAS# 17354

- 14

- 2

RBA = NB O O

N H C H 3

N H

C H 3

O

O

N H

O

O N H

LogKow = 7.73 KowWin
CAS# 81

- 77

- 6

LogKow = 1.94 msrd

CAS# 2475

- 46

- 9 O

O

N H

C H 3 N H O H

LogKow = 4.98 KowWin
CAS# 27354

- 18

- 3 O O

N H 2

N H 2 DAAQ LogKow = 3.00 msrd

CAS# 128

- 95

- 0

RBA = NB O

O

N H

C H 3 C H 3

LogKow = 5.38 KowWin
CAS# 4395

- 65

- 7 O O N H 2

N H

LogKow = 6.07 KowWin
CAS# 14233

- 37

- 5 O

O N H C H 3

C H 3 N H C H 3 C H 3

SBII LogKow = 7.20 KowWin
CAS# 17354

- 14

- 2

RBA = NB O O

N H C H 3

N H

C H 3

O O

N H

C H 3 N H C H 3

QGS

LogKow = 8.00 KowWin
CAS# 128

- 80

- 3

RBA = NB LogKow = 8.00 KowWin
CAS# 6737

- 68

- 4 LogKow = 8.00 KowWin
CAS# 29887

- 08

- 9 LogKow = 8.00 KowWin
CAS# 116

- 75

- 6 O

O

N H

C H 3 N H C H 3 O

O

N H

C H 3

C H 3 C H 3 N H

C

H 3 C H 3

C H 3

O

O

N H

C H 3 C H 3 N H C H 3 C H 3 O

O NH 2

NH 2 

### Slide 97 of 320

# Phosphoric Acid Ester

O

O O P

O O P

O O

O

C H 3 C H 3 

# Rainbow Trout Training Set

Non

- Food Use Inerts (2009) Inventory

O

O O P

O O P

O O

O

C H 3 C H 3

O P

O O H

O C H 3

O P

O O O C H

3 C H

3

O P

O O O C H 3

LogKow = 1.26 clogP CAS# 69867

- 71

- 6 LogKow = 6.30 clogP CAS# 29761

- 21

- 5 LogKow = 6.43 clogP CAS# 14167

- 87

- 4 TPPa LogKow = 4.59 msrd CAS# 115

- 86

- 6 RBA = 0.001048 EHDPP LogKow = 5.73 msrd CAS# 1241

- 94

- 7 RBA = 0.001913

EHDPP LogKow = 5.73 msrd CAS# 1241

- 94

- 7 RBA = 0.001913 TPPa LogKow = 4.59 msrd CAS# 115

- 86

- 6 RBA = 0.001048 O P O H

O O

PHOS LogKow = 1.05 clogP CAS# 838

- 85

- 7 RBA = NB 

## P O

O O R1

R1 R1 O

LogKow = 8.00 KOWWIN CAS# 78

- 33

- 1 C H 3 C H 3 C H 3

O P O

O

C H 3

C H 3 C H 3 O C H 3

C H 3 C H 3



### Slide 98 of 320

### 99 Contains

a Cycle Yes

Log K OW <1.3

“Special

Rule” Applies

Site “A”
Contains Phenol Fragment

Log Kow Range

4

- Alkylanilines ( 1.4

- 5.1)

4

- Alkoxy Anilines ( 2.6

- 3.7)
Phthalates ( 2.5

- 6.8)
Phenones

- (branched) ( 2.7

- 4.8)

4

- Alkyl c yclohexanols ( 2.4

- 3.8)

4

- Alkyl cyclohexanones ( 2.4

- 3.8) *

2

- ; 4

- ; or 2,4,6

- Benzoates (substitution

- dependent Log Kows) Possible Low Affinity

Site A

- Type, Site B

- Type

Site “B” Contains “Specified” Fragment Log Kow Range Alkylphenols (1.5

- 8.0) Alkoxy phenols (2.3

- 4.3)
Parabens (1.9

- 5.4) Salicylates (2.5

- 5.1 ) 2

- Hydroxy Benzophenones Phenolsulfophthaleins
Fluoresceins Belongs to
known Active

Sub

- class RBA > 0.00001% Yes

No



## VI

Unknown Binding Potential No

Yes

Yes

No Yes

Belongs to
known Active

Sub

- class

Belong to untested class

Unknown Binding Potential Mixed Phenols

No 

## VII No Belongs to
known Inactive
Sub

- class

Log Kow Range

4

- n

- Alkylfluorobenzenes ( 2.3

- 4.9) Alkylphenol (2,6

- subst) ( 4.2)
Benzamides ( 1.7

- 2.1)

Borate Esters (

- 0.5

- 1.0) Benzoates (non

- ring subst ) ( 3.6

- 4.2)

Bis

- anilines ( 1.6

- 6.2) Hydrofurans (alcohol & ketone) ( 0.0

- 1.2)
Imidazolidines (

- 0.9

- 0.6)
Isothiazolines ( 0.6

- 2.5)

Mono

- cyclic Hydrocarbons ( 2.7

- 4.6)
Oxazoles (<0.3)
Phenones (n

- alkyl) ( 1.6

- 4.1) Pyrrolidiones (

- 0.4

- 3.3)
Sorbitans ( 3.2

- 5.9)

Triazines (

- 0.4

- 3.4 ) Dimethylamino Phenols Naphthalenol Azophenyls
Benzotriazole Phenols Sugars
Alcohols Morpholines
Acetanilides
Amino Anthracenedione Phosphorous Acid Esters Yes DDT

- Like
Tamoxifen

- Like Multicyclic hydrocarbons Alkylchlorobenzenes Thiophosphate Esters Phosphoric Acid Esters

Yes No

No Yes

RBA > 0.00001% RBA < 0.00001% 

## I

RBA < 0.00001%

Yes No 

## V III

Contains a Charge No

Yes 

## II

Exact match to Mixed Phenols Training Set Structure and
measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes

Unknown Binding Potential Mixed Organics No

Exact match to Mixed Organics Training Set Structure and
measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes Unknown Binding Potential Exact match to Group Training Set Structure
and measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes Alkylaromatic Sulfonic Acids L og Kow (

- 0.6

- 5.7) Sulfonic Acid Dyes Log Kow (

- 0.4

- 6.0)

4

- Alkylbenzthiols Log Kow ( 2.9

- 4.2 ) Carboxylic Acid Functional Group Phosphoric Acid Functional Group Quat Amine Functional Group Sulfonic Acid Functional Group
Miscellaneous Functional Groups w/ Charge Anhydrides Contains a phenolic OH, and additional

OH and/or =0 

## IV

Meets specific distance
criteria for:
Sites “A

- B”;
Sites “A

- C”;
Sites “A

- B

- C”

Contains some attenuating feature,

steric or other

High Affinity
“A

- B”;“A

- C” or “A

- B

- C”
RBA > 0.1%

RBA < 0.00001%

Low Affinity
“A

- B”,“A

- C” or “A

- B

- C”
0.00001% < RBA < 0.1% Strength of
attenuation factors Yes

No

Strong Weak ER ESv2
Start Here:
Chemical List



### Slide 99 of 320ACS LogKow =

- 1.00 KOWWIN
CAS# 50

- 81

- 7

RBA = NB O O H O H O H

O H O H

LogKow =

- 1.00 KOWWIN
CAS# 89

- 65

- 6 O O H O H O H

O H O H

LogKow =

- 1.00 KOWWIN
CAS# 134

- 03

- 2 O O H O - O H

O H O H Na +

LogKow =

- 1.00 KOWWIN
CAS# 6381

- 77

- 7 O O H O - O H

O H O H Na +

LogKow =

- 0.91 KOWWIN
CAS# 27277

- 00

- 5 O

C H 3 N N

N H

N H N C H 3

CAF LogKow =

- 0.07 msrd

CAS# 58

- 08

- 2

RBA = NB O N C H 3

O

N C H 3 N

N

C H 3 URA LogKow =

- 1.00 KOWWIN
CAS# 69

- 93

- 2

RBA = NB O N H

O

N H N H O

N

H

GCU LogKow =

- 1.00 KOWWIN
CAS# 496

- 46

- 8

RBA = NB O

N H N H

O

N H N H

6BPu LogKow = 1.57 msrd

CAS# 1214

- 39

- 7 N H N

N

N H N

LogKow =

- 1.23 msrd

CAS# 58

- 61

- 7

N H 2 N O H
O H

O H O N

N N 

# (A) Ascorbic Acid Analogs; Caffeine Analogs

Vitamin C

– ascorbic acid

Caffeine

Slide 100 of 320O C H 3

C H 3 C H 3 IPN LogKow = 1.70 msrd

CAS# 78

- 59

- 1

RBA = NB HMPY LogKow = 0.02 msrd

CAS# 118

- 71

- 8

RBA = NB O O H C H 3 O

DHAA LogKow = 0.78 KOWWIN
CAS# 520

- 45

- 6

RBA = NB O C H 3 O O H

C H 3 O

DMXC LogKow = 1.67 KOWWIN
CAS# 487

- 06

- 9

RBA = NB O C H 3 O C H 3 O O

LogKow = 0.57 KOWWIN
CAS# 4437

- 85

- 8 O O C H 3

O

LogKow =

- 0.41 msrd

CAS# 108

- 32

- 7 O O C H 3

O LogKow = 2.52 msrd

CAS# 6485

- 40

- 1 O C H 3

C H 2

C H 3 

# (B) Aldehyde Analogs; Ketone Analogs

HCIN LogKow = 4.82 KOWWIN
CAS# 101

- 86

- 0
RBA = 0.001755 O

C H 3

LogKow = 4.33 KOWWIN
CAS# 122

- 40

- 7 O

C H 3 DAM LogKow = 4.21 KOWWIN
CAS# 23696

- 85

- 7
RBA = 0.001138 C H 3 C H 3 O C H 3 C H 3

MION LogKow = 4.84KOWWIN
CAS# 1335

- 46

- 2
RBA = 0.0008063 C H 3 C H 3 C H 3 O

C H 3 C H 3 C H 3 O C H 3 C H 3

C H 3 C H 3

AIM

– ER

- binding component of ALD mixture LogKow = 4.84 KOWWIN
CAS# 127

- 51

- 5

RBA = 0.001224

CIN LogKow = 1.90 msrd

CAS# 104

- 55

- 2

RBA = NB O C H 3 O

LogKow = 2.18 msrd

CAS# 122

- 57

- 6 LogKow = 4.36 KOWWIN
CAS# 80

- 54

- 6 C H 3 C H 3

C H 3 C H 3

O 

# Aldehyde

– Ketone ****

Slide 101 of 320LogKow = 3.04 KOWWIN CAS#
120

- 55

- 8 O

O

O

O

O DPD LogKow = 2.51 KOWWIN
CAS# 120

- 46

- 7

RBA = NB O O O O

O

O

O

O TGD LogKow = 2.77 KOWWIN
CAS# 120

- 56

- 9

RBA = NB LogKow = 3.73 KOWWIN CAS#
19224

- 26

- 1 O

O C H 3 O

O O

O

O C H 3

C H 3 O O

PDB LogKow = 3.88 KOWWIN
CAS# 27138

- 31

- 4

RBA = NB

LogKow =

- 0.30 KOWWIN
CAS# 75

- 21

- 8 

# O

LogKow = 0.86 KOWWIN
CAS# 106

- 88

- 7 C H 3 O

NGDE LogKow = 0.23 KOWWIN
CAS# 17557

- 23

- 2

RBA = NB C H 3 C H 3 O O

O O 

# (C) Di

- ketone Analogs; Di

- carboxy Ester Analogs; Epoxides

Di

- ketone & Di

- carboxy ester:

Epoxides:

Slide 102 of 320LogKow = 2.31 KOWWIN
CAS# 98

- 94

- 2 N

C H 3 C H 3

LogKow = 3.98 CLogP
CAS# 4107

- 98

- 6 N

C H 3 C H 3 C H 3 C H 3

LogKow = 8.00 KOWWIN
CAS# 67

- 97

- 0 C H 2 C H 3

C H 3

C H 3 C H 3 O H H H

LogKow = 8.00 KOWWIN
CAS# 1406

- 16

- 2 C H 2 C H 3 C H 3

C H 3 C H 3

O H H

H

O Cl

Cl N

O DOS LogKow = 1.94 KOWWIN
CAS# 71526

- 07

- 3

RBA = NB LogKow = 2.25 KOWWIN
CAS# 52836

- 31

- 4 O Cl Cl

N

C H 3 C H 3

O

C H 3

LogKow = 2.12 msrd

CAS# 121776

- 33

- 8 N

O Cl Cl C H 3 C H 3 O

O 

# (D) Reactive Peroxides; Vitamin E Analogs; Dichloroacetyl Oxazolidine;

Tert

- amine

DAA LogKow = 5.27 KOWWIN
CAS# 2481

- 94

- 9

RBA = NB N N N C H 3

C H 3

LogKow = 2.89 KOWWIN
CAS# 614

- 45

- 9 O O O

C H 3 C H 3

C H 3



## Reactive Peroxides LogKow = 3.46 msrd

CAS# 94

- 36

- 0

O O O

O

LogKow = 8.00 KOWWIN
CAS# 58

- 95

- 7 C H 3 O C H 3

O C H 3 C H 3

C H 3 C H 3 C H 3

C H 3 C H 3

O



## Vitamin E acetate Vitamin E

Di

- Chloroacetyl Oxazolidine Tert

- amine

Slide 103 of 320BZC LogKow = 1.86 msrd

CAS# 94

- 09

- 7

RBA = ?? O N H 2

O C H 3

EAB LogKow = 2.57 msrd

CAS# 87

- 25

- 2
RBA = 0.00005877 O N H 2

O C H 3

O O Si O
Si O Si C H 3 C H 3

C H 3 C H 3

C H 3 C H 3 C H 3

OCS LogKow = 5.10 msrd

CAS# 556

- 67

- 2

RBA = NB LogKow = 5.71 KOWWIN
CAS# 541

- 02

- 6 C H 3 Si
C H 3 O

Si C H 3 C H 3 O Si C H 3 C H 3

O Si C H 3 C H 3

O

Si C H 3 C

H 3 O

PAS LogKow = 1.78 msrd

CAS# 66

- 71

- 7

RBA = NB N

N

IND LogKow = 2.14 msrd

CAS# 120

- 72

- 9
RBA = 0.00009847 N H

LogKow = 0.92 msrd

CAS# 120

- 94

- 5 N C H 3 

# (E) Silicon; Nitrogen Heterocycles; etc...

LogKow = 4.04 KOWWIN
CAS# 2110

- 18

- 1 N LogKow = 7.15 KOWWIN
CAS# 2116

- 84

- 9 Si O Si C H 3 C H 3

C H 3

O Si C H 3

C H 3 C H 3

O Si C H 3

C H 3 C H 3 LogKow = 4.03 KOWWIN
CAS# 14576

- 08

- 0 C H 3 C H 3 C H 3

O C H 3 C H 3 C H 3

O H C H 3

AT LogKow = 2.79 msrd

CAS# 98

- 55

- 5

RBA = NB



# Nitrogen

- heterocycles silicon

Slide 104 of 320

# (F) Mixed Phenol Analogs

HCP LogKow = 1.35 msrd CAS# 99

- 93

- 4 RBA = NB LogKow = 1.92 msrd CAS# 118

- 93

- 4 C H 3 O O H

C H 3 O O H

VN LogKow = 1.21 msrd CAS# 121

- 33

- 5 RBA = NB O H O C H 3 O

LogKow = 1.61 msrd CAS# 121

- 32

- 4 O H O C H 3 O

HQ LogKow = 0.59 msrd CAS# 123

- 31

- 9 RBA = NB LogKow = 0.80 msrd CAS# 108

- 46

- 3 O H O H

O H O H PO LogKow =

- 0.72 msrd CAS# 65

- 23

- 6 RBA = NB C H 3 O H O H

O H

N
C H 3 O H O H

O H

N +

H Cl LogKow =

- 0.72 msrd CAS# 58

- 56

- 0



### Slide 105 of 320

### 106 Contains

a Cycle Yes

Log K OW <1.3

“Special

Rule” Applies

Site “A”
Contains Phenol Fragment

Log Kow Range

4

- Alkylanilines ( 1.4

- 5.1)

4

- Alkoxy Anilines ( 2.6

- 3.7)
Phthalates ( 2.5

- 6.8)
Phenones

- (branched) ( 2.7

- 4.8)

4

- Alkyl c yclohexanols ( 2.4

- 3.8)

4

- Alkyl cyclohexanones ( 2.4

- 3.8) *

2

- ; 4

- ; or 2,4,6

- Benzoates (substitution

- dependent Log Kows) Possible Low Affinity

Site A

- Type, Site B

- Type

Site “B” Contains “Specified” Fragment Log Kow Range Alkylphenols (1.5

- 8.0) Alkoxy phenols (2.3

- 4.3)
Parabens (1.9

- 5.4) Salicylates (2.5

- 5.1 ) 2

- Hydroxy Benzophenones Phenolsulfophthaleins
Fluoresceins Belongs to
known Active

Sub

- class RBA > 0.00001% Yes

No



## VI

Unknown Binding Potential No

Yes

Yes

No Yes

Belongs to
known Active

Sub

- class

Belong to untested class

Unknown Binding Potential Mixed Phenols

No 

## VII No Belongs to
known Inactive
Sub

- class

Log Kow Range

4

- n

- Alkylfluorobenzenes ( 2.3

- 4.9) Alkylphenol (2,6

- subst) ( 4.2)
Benzamides ( 1.7

- 2.1)

Borate Esters (

- 0.5

- 1.0) Benzoates (non

- ring subst ) ( 3.6

- 4.2)

Bis

- anilines ( 1.6

- 6.2) Hydrofurans (alcohol & ketone) ( 0.0

- 1.2)
Imidazolidines (

- 0.9

- 0.6)
Isothiazolines ( 0.6

- 2.5)

Mono

- cyclic Hydrocarbons ( 2.7

- 4.6)
Oxazoles (<0.3)
Phenones (n

- alkyl) ( 1.6

- 4.1) Pyrrolidiones (

- 0.4

- 3.3)
Sorbitans ( 3.2

- 5.9)

Triazines (

- 0.4

- 3.4 ) Dimethylamino Phenols Naphthalenol Azophenyls
Benzotriazole Phenols Sugars
Alcohols Morpholines
Acetanilides
Amino Anthracenedione Phosphorous Acid Esters Yes DDT

- Like
Tamoxifen

- Like Multicyclic hydrocarbons Alkylchlorobenzenes Thiophosphate Esters Phosphoric Acid Esters

Yes No

No Yes

RBA > 0.00001% RBA < 0.00001% 

## I

RBA < 0.00001%

Yes No 

## V III

Contains a Charge No

Yes 

## II

Exact match to Mixed Phenols Training Set Structure and
measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes

Unknown Binding Potential Mixed Organics No

Exact match to Mixed Organics Training Set Structure and
measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes Unknown Binding Potential Exact match to Group Training Set Structure
and measured RBA RBA > 0.00001%

RBA < 0.00001%

No Yes Alkylaromatic Sulfonic Acids L og Kow (

- 0.6

- 5.7) Sulfonic Acid Dyes Log Kow (

- 0.4

- 6.0)

4

- Alkylbenzthiols Log Kow ( 2.9

- 4.2 ) Carboxylic Acid Functional Group Phosphoric Acid Functional Group Quat Amine Functional Group Sulfonic Acid Functional Group
Miscellaneous Functional Groups w/ Charge Anhydrides Contains a phenolic OH, and additional

OH and/or =0 

## IV

Meets specific distance
criteria for:
Sites “A

- B”;
Sites “A

- C”;
Sites “A

- B

- C”

Contains some attenuating feature,

steric or other

High Affinity
“A

- B”;“A

- C” or “A

- B

- C”
RBA > 0.1%

RBA < 0.00001%

Low Affinity
“A

- B”,“A

- C” or “A

- B

- C”
0.00001% < RBA < 0.1% Strength of
attenuation factors Yes

No

Strong Weak ER ESv2
Start Here:
Chemical List



### Slide 106 of 320

# Topics

 History of model development ESv1 (2009 SAP Review)

• Background & Principles



#  Expanding to ESv2

 Assessing Coverage of

EDSP Universe

 Affect of P

- Chem Filtering

Slide 107 of 320

# 5 Goals

1) Determine ESv1 coverage of EDSP chemicals to prioritize for T1S (Sec 3)

2) Build ESv2 and determine coverage of EDSP chemicals to prioritize for T1S (Sec3)

3) Identify remaining chemicals with Unknown Binding Potential ( UnkBP ) i.e. , those outside ESv2 model domain (Sec 3)

4) Determine where HTP data covers UnkBP chemicals (Sec 8)

5) Determine if and how HTP data could be used to expand TrSet to

cover UnkBP chemicals. (Sec 4, 5, 6, 7, 8) ESv1 (SAP, 2009)

ESv2

ESv3 

# Moving Incrementally Building from Initial Steps to Address New Challenges EDSP Universe (FI, NFI, Frag , SDWA)

Slide 108 of 320

# INERTS

- Food

- use inerts list (FI 2012)

- Non food

- use Inerts 2012 list (NFI 2012)

- Fragrances used in inerts list ( Frag 2012)

SDWA

- Overlap with INERTS lists (FI, NF, Frag )

- SDWA list Only 

# Composition of EDSP Universe

Slide 109 of 320

# 5975 Discrete Structures; prior to p

- chem filtering

- 43% Inerts (FI, NF, Frag & some SDWA)

- 57% on SDWA list only 

# EDSP Universe by Use Classes

INERTS Category SDWA also non - SDWA

Use Class # chems #chems **% of Category**  FI NF Frag

Fooduse Inert ONLY 440 201 46 239

Fooduse & Fragrance 50 46 92 4

Fooduse All total= 490

Nonfood use only 989 444 45 545

Nonfood & Fragrance 152 111 73 41

Nonfood All Total= 1141

Fragrance only 963 227 24 736

Fragrance Total= 1165

All INERTS= 2594

INERTS also SDWA = 1029 40

INERTS non

- SDWA= 1565

SDWA only= 3381

All SDWA= 4410

Total Inventory= 5975



### Slide 110 of 320ER ESv2 All INERTS SDWA only INERT+SDWA

5975 Inventory #chem % #chem % %

RBA<0.00001% 1785 69 2321 69 4106 69

RBA>0.00001% 87 3 78 2 165 3

Predicted= 1872 72 2398 71 4271 71

UNK BP 722 28 982 29 1704 29

Totals = 2594 3381 5975 

# ESv2 Predictions

Slide 111 of 320 

# - 71% Coverage of 5975 overall (68% for ESv1 )

- Similar coverage whether INERTS, or SDWA OnlyER ESv2 All INERTS SDWA only INERT+SDWA

5975 Inventory #chem % #chem % %

RBA<0.00001% 1785 69 2321 69 4106 69

RBA>0.00001% 87 3 78 2 165 3

Predicted= 1872 72 2398 71 4271 71

UNK BP 722 28 982 29 1704 29

Totals = 2594 3381 5975



### Slide 112 of 320 

# ESv2 Predictions

- 71% Coverage of 5975 overall (68% for ESv1 )

- Similar coverage whether INERTS, or SDWA Only

- 1872 INERTS (72%)ER ESv2 All INERTS SDWA only INERT+SDWA

5975 Inventory #chem % #chem % %

RBA<0.00001% 1785 69 2321 69 4106 69

RBA>0.00001% 87 3 78 2 165 3

Predicted= 1872 72 2398 71 4271 71

UNK BP 722 28 982 29 1704 29

Totals = 2594 3381 5975 

# - 71% Coverage of 5975 overall (68% for ESv1 )

- Similar coverage whether INERTS, or SDWA Only

- 1872 INERTS (72%)

- 2398 SDWA Only (71%)

Slide 113 of 320 

# ESv2 PredictionsER ESv2 All INERTS FI FI FI FI NF NF NF NF Frag Frag Frag Frag SDWA Only INERT+SDWA

5975 Inventory #chem % only + Frag Total Total
% only + Frag Total Total
% Only Only
% ALL All % #chem % %

RBA<0.00001% 1785 69 425 47 472 96 854 84 938 82 375 39 506 43 2321 69 4106 69

RBA>0.00001% 87 3 2 3 5 1 29 14 43 4 39 4 56 5 78 2 165 3

Predicted= 1872 72 477 97 981 86 414 43 562 48 2399 71 4271 71

UNK BP 722 28 13 0 13 1 106 54 160 14 549 57 603 52 982 29 1704 29

Totals = 2594 440 50 989 152 963 3381 5975

Use Class
Total= 490 1141 1165 

# ESv2 Domain Coverage by Use Class

- 97% coverage of Fooduse , 477 chemicals

- 86% coverage of Nonfooduse , 981 chemicals 72% All INERTS

- 43% coverage of Fragrances (not FI or NF), 414 chemicals

- 71% coverage of SDWA that are not also INERTS, 2399 chemicals

- Overall, 4271 chemicals (71%)

- Largest increase from ESv1 (80%) coverage is in NF, as expected

- Modest increased in coverage for most groups as initial coverage was good

Slide 114 of 320

# ESv2 Predicted % Binders and NonBinders

ER ESv2 All INERTS

Fooduse Nonfooduse Fragrance SDWA only INERT + SDWA

5975 Inventory #chem % only +Frag Ttl % only + Frag Ttl % only % ALL % #chem % %

Nonbinder 1785 95 425 47 472 99 854 84 938 96 375 91 506 90 2321 97 4106 96

Binder 87 5 2 3 5 1 29 14 43 4 39 9 56 10 78 3 165 4

Total= 1872 477 981 414 562 2399 4271 

## - Overall, 4% Binders INERTS:

- 1% Fooduse

- 4% Nonfood use

- 10% Fragrances SDWA Only

- 3%

Slide 115 of 320

### Expert System Category Nonbinders Binders UNK BP

# chems # chems # chems II. ‘ Contains a Charge’
Anhydrides 15 0 0

III. ‘Belongs to Known Inactive Subclass’

Dimethylamino Phenols 5 0 0 Naphthalenol

- Azophenyls 21 0 0
Benzotriazole Phenols 9 0 0 Sugars 22 0 0
Alcohols 29 0 27 Morpholines 19 0 0
Acetanilides 4 0 0
Mixed Acetanilides 7 0 7
Amino Anthracenediones 13 0 0 Phosphorous Acid Esters 13 0 0

V. ‘Special Rules Apply’
Phosphoric Acid Esters 0 19 0

VI. ‘Site A

– Contains a Phenol Fragment’

2

- Hydroxy Benzophenones 0 6 0 Phenolsulfophthaleins 0 1 0
Hindered Phenolsulfophthaleins 2 0 0
Fluoresceins 0 2 0
Hindered Fluoresceins 3 0 0 

# 14 New Chemical Groups in ESv2

Slide 116 of 320

# Distribution of 1704 Unk BP Chemicals Among ESv2 Groups

- Distributed across ES categories and chemicals
groups

- Majority are Mixed Organics,
then Mixed Phenols

Slide 117 of 320 ESv2 Category and Chemical Group # chem % of 1704 I. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9

III. Belongs to a known Inactive class Alcohols ( LogKow >3.4) 27 1.6
Mono

- cyclic Hydrocarbons [ LogKow <2.5,>6.4] 13 0.8 Triazines [ LogKow >4.1] 9 0.5 Benzoates (non

- ring Subst )[ LogKow <3.0,>4.3] 6 0.4 Sorbitans [ LogKow <3.1,>5.9] 4 0.2 Imidazolidines [LogKow>0] 3 0.2
Benzamides [ LogKow <2.1,>2.8] 1 0.1
Bis

- Anilines [LogKow<2.1,>6.4] 1 0.1 Phenones (n

- alkyl)[LogKow>4.2] 1 0.1 Pyrrolidiones [LogKow>3.4] 1 0.1 **III. Known Inactives Subtotal=** 66 3.9 V. Special Rule applies Multi Cyclic Hydrocarbons Unknown Binding Potential 67 3.9 Thiophosphate Esters Unknown Binding Potential 14 0.8 Alkylbromobenzene 7 0.4 **V. Special Rules Subtotal=** 88 5.2 VI. Site "A": Contains a Phenol fragment
Mixed Phenol

- Unknown Binding Potential 133 7.8 Alkoxyphenols [LogKow >4.1] 1 0.1 **VI. Site "A" Subtotal=** 134 7.9

VII. Site "B": Contains "Specified" fragment Mixed Organics

- Unknown Binding Potential 1368 80.3

2

- Alkylanilines 7 0.4 Mixed Acetanilides (LogKow>1.3) 7 0.4 Phenones cyclo

- substituted

- Unknown Binding Potential 6 0.4 Multi subst. Alkylanilines 5 0.3 Alkylcyclohexanols LogKow>4.4 or >2.6 & <3.5 4 0.2
3

- Alkylanilines 2 0.1

2

- ;4

- ; or2,4,6

- Benzoates Unknown Binding Potential 1 0.1
**VII. Site "B" Subtotal=** 1400 82.2
**Unk Binding Potential Total=** 1704

# Topics

 History of model development ESv1 (2009 SAP Review)

• Background & Principles



#  Expanding to ESv2

 Assessing Coverage of

EDSP Universe

 Affect of P

- Chem Filtering

Slide 118 of 320A). ES Chemical Classification ES Prediction 

### # chems **%**

Alkylphenols RBA>0.00001% 

### 2 0.19

Acyclic_Perfluoro (RBA>0.00001%) RBA>0.00001% 

### 3 0.29

Acyclic Perfluoro (UnkBP) UnkBP 

### 5 0.49

Mixed Organics

- UnkBP UnkBP 

### 63 6.13

Mixed Phenol

- UnkBP UnkBP 

### 4 0.39

Triazines [LogKow>4.1] UnkBP 

### 2 0.19

Subtotal= 

### 79 8

All remaining Filtered Groups Chemicals RBA<0.00001% 

### 949 92

Total = 

### 1028 100 

# ESv2 Predictions for 1028 Chemicals Excluded by P

- chem Filters

1%

99% - P

- chem filters are all subject to further examination

- 99% are predicted Nonbinders (92%) or UnkBP (7%)

- 1% identified for initial focus of Chemistry Expert Group

Slide 119 of 320Excluded Remain in by Filters 4947 B). ES Chemical Classification ES Prediction #chems # chems
Acyclic_Alcohol RBA<0.00001% 27 267
Acyclic_Amines RBA<0.00001% 19 98
Acyclic_Carboxy Ester RBA<0.00001% 54 393
Acyclic_Carboxylic Acid RBA<0.00001% 68 313
Acyclic_Phosphonic Acid RBA<0.00001% 6 0
Acyclic_Sulfate RBA<0.00001% 52 0
Acyclics_Quat Amine RBA<0.00001% 5 15
Acyclics_Other RBA<0.00001% 128 746
Alkylaromatic Sulfonic Acids RBA<0.00001% 45 0
Alkylphenols (2,6

- subst) RBA<0.00001% 1 35
Amino Anthracenedione ( LogKow >3.0) RBA<0.00001% 1 12
Anhydrides RBA<0.00001% 1 14

Bis

- Anilines [2.1<= LogKow <=6.4] RBA<0.00001% 1 8
Carboxylic Acid Functional Group RBA<0.00001% 38 187
Hydrofurans [ LogKow <=6.1] RBA<0.00001% 1 22

Imidazolidines [ LogKow <=0] RBA<0.00001% 1 5
Inorganic RBA<0.00001% 197 143
Log Kow Cut

- off <1.3 RBA<0.00001% 31 358
Miscellaneous Charged Atom RBA<0.00001% 2 19
Mixed Organics

- Exact Match (RBA<0.00001%) RBA<0.00001% 2 52

Mixed Phenol

- Exact Match (RBA<0.00001%) RBA<0.00001% 1 6

Mono

- cyclic Hydrocarbons [2.5<=LogKow<=6.4] RBA<0.00001% 2 64
Morpholine RBA<0.00001% 1 18
Naphthalenol_Azophenyl RBA<0.00001% 2 19
Phenolsulfonphthaleins hindered RBA<0.00001% 1 1
Phosphoric Acid Functional Group RBA<0.00001% 19 0
Quat Amine Functional Group RBA<0.00001% 4 26
Sugars RBA<0.00001% 2 20
Sulfonic Acid Dyes RBA<0.00001% 135 8
Sulfonic Acid Functional Group RBA<0.00001% 98 0
Triazines [LogKow<=4.1] RBA<0.00001% 4 24 949 

# ESv2_ Predicted Nonbinders Chemicals Excluded by P

- chem Filters

- Wide range of chemical categories

- Many chemicals in same classes are not excluded

Slide 120 of 320INERTS SDWA also non - SDWA

Use Class #chems #chems **%** FI NF Frag FI only 262 127 46 135 FI & Frag 46 43 92 3

FI total= 308

NF only 687 332 45 355 NF & Frag 148 107 73 41

NF Total= 835

Frag only 937 222 24 715 Frag Total= 1131

All INERTS= 2080 831 40 INERTS non

SDWA= 1249 SDWA only= 2877

All SDWA= 3710 Total Inventory= 4957 

# EDSP Universe after Application of Proposed p

- chem Filters

Total = 4957

- INERTS decrease from 2594 to 2080

- SDWA Only decrease from 3381 to 2877

Slide 121 of 320

# ESv2 Predictions for 4957 After Application of Proposed P

- chem Filter

ER ESv 2 All INERTS FI FI FI FI NF NF NF NF Frag Frag Frag Frag SDWA only

4957 Inventory #chem % only + Frag Total % pred only + Frag Total % pred only % pred ALL % pred #chem % pred



### Nonbinders 1293 62 248 43 291 94 560 80 640 77 362 39 485 43 1864 65

Binders 87 4 2 3 5 2 29 14 43 5 39 4 56 5 78 3

Predicted= 1380 66 296 96 683 82 401 541 48 1942 67

UNK BP 700 34 12 0 12 98 54 152 536 590 935

Totals = 2080 262 46 687 148 937 2877

Use Class
Total= 604 1518 1672 

# - Since 949 chemicals with Predictions were removed by filter, apparent coverage decreases; number of Binders remain same

- 1380 INERTS covered, was 1872 pre

- filter

- 1942 SDWA Only, was 2398 pre

- filter

Slide 122 of 320

### ER ESv2 All INERTS FI FI FI FI NF NF NF NF Frag Frag Frag Frag SDWA only

#chem % only + Fra
g Total % only +Fra
g Total % only % ALL % #chem %

Nonbinders 1293 94 248 43 291 98 560 80 640 94 362 90 485 90 1864 96

Binders 87 6 2 3 5 2 29 14 43 6 39 10 56 10 78 4

Total= 1380 296 683 401 541 1942 

# ESv2 Predictions for 4957 Post

- Filtered by Use Class

- 6% of INERTS overall are predicted Binder

- 2 % Fooduse

- 6% Nonfood use

- 10% of Fragrances are predicted Binders

- 4% of SDWA Only are predicted Binders

Slide 123 of 320ER ESv2 All INERTS SDWA only INERT+SDWA

4957 Inventory #chem % #chem % #chem %

RBA<0.00001% 1293 62 1864 65 3157 64

RBA>0.00001% 87 4 78 3 165 3

Predicted= 1380 66 68 67

UNK BP 700 34 935 32 1635 33

Totals = 2080 2877 4957 

# Overall results for 4957 Filtered Inventory using ESv2

Slide 124 of 320

# SUMMARY

 ER Expert System Development

• Effects

- Based Chemical Categories Approach

• Designed around ER

- mediated AOP

• OECD QSAR Principles



#  Expanded to cover additional inventories

Slide 125 of 320

#  Before p

- chem filter

• ESv2 covered 71% of EDSP Universe of 5975 before filtering

• 165 Chemicals predicted to Bind ER

• 1704 chemicals with UnkBP distributed across multiple chemical groups

Slide 126 of 320 

# SUMMARY

 After p

- chem filter

• ESv2 covered 67% of EDSP Universe of 4957 after Preliminary filtering

• 165 Chemicals predicted to Bind ER

• 1635 chemicals with UnkBP distributed across multiple chemical groups

# 5 Goals

1) Determine ESv1 coverage of EDSP chemicals to prioritize for T1S (Sec 3)

2) Build ESv2 and determine coverage of EDSP chemicals to prioritize for T1S (Sec3)

3) Identify remaining chemicals with Unknown Binding Potential ( UnkBP ) i.e., those outside ESv2 model domain (Sec 3)

4) Determine where HTP data covers UnkBP chemicals (Sec 8)

5) Determine if and how HTP data could be used to expand TrSet to

cover UnkBP chemicals. (Sec 4, 5, 6, 7, 8) ESv1

ESv2

ESv3 

# Building from Initial Steps to Address New Challenges Moving Incrementally

Slide 127 of 320

### Slide 128 of 320 

# Overview of High Throughput ER Binding and Gene Activation Assays and Analysis using Reference Compounds

Dr. Richard Judson Office of Research and Development National Center for Computational Toxicology

# EDSP Universe of Chemicals n= 10,341

Chemical
Lists FIFRA Registration Review
Schedule for Active Ingredients (Approx.=1500) SDWA and INERTS (Approx.=9000)

Physico

Chemical Properties

(Approx n=5000) 

# Excluded

Exposure
Potential

SDWA 

# Lower Priority

ER Expert System

High through put
system 

# Prioritized List of Chemicals for EDSP Tier 1 Screening yes

No * Mixtures will be lower priority

no

Yes 

# Considerations of Read

Across and Chemical Categories

Slide 129 of 320

# HTP Overview

 Introduction / ER HTP Assay Battery

 ER HTP Assays

• ER Binding Assays

• Transactivation Assays



#  Chemical Selection and Processing

 Data Analysis/Interpretation Methodology

 Assay Performance

• Reference chemicals

• Other performance evaluations

Slide 130 of 320

# Goals and Definitions

 Goal of this effort:

• Answer the question: “Does this chemical interact with the estrogen receptor in vitro?”

• U se data from a battery of assays

• Information will be combined using pathway models



#  EPA ORD is evaluating a large battery of endocrine pathway HTP assays

 Part of ToxCast and Tox21 programs

• ToxCast: EPA program to evaluate the use of hundreds of high

- throughput assays for prioritization and other
purposes

• Tox21: Cross agency program with same goals (EPA, NTP, NIH, FDA

Slide 131 of 320

# ER Focused HTP Assays

 For this SAP, 8 ER assays were selected to illustrate approaches to data acquisition, analysis and evaluation (21 total ER assays being evaluated)

• Conducted by contract labs and NIH Chemical Genomics Center (NCGC)



#  ER assays are subset of ~900 total ToxCast assays

• Large assay x chemical space requires the use of uniform protocols

• ToxCast designed to screen chemicals up to concentrations expected from environmental exposure

Slide 132 of 320 

# ChemicalsAssays



## 8200 1800 900

21 ER 

# All HTP data and analyses are preliminary at this time

# Section: HTP Assay Overview

 Brief Introduction to the 8 high

- throughput assays

 All details are found in Appendix F

 High

- throughput assay:

• Assays can process 1000

- 100000 chemicals response at a time

• Run in microtiter plates (24

- 1536

- well)

• Typically using robotics

• Single or multiplexed readouts

Slide 133 of 320



# Example data from NCGC: 30,000 samples processed in 1 week

# Pro

- ligand

ER Active ligand

Cofactor

ER

- regulated gene expression

Cell proliferation Oxidative

stress pathways Non

- ER

- mediated cell proliferation pathways Non

- ligand

mediated
activation of ER activity

Attagene Attagene, NCGC, Odyssey Thera ACEA Odyssey
Thera Odyssey
Thera

Novascreen 

# Using Multiple Lines of Evidence Across Pathway to Test for ER Activity

Attagene assays
have metabolic capacity

Slide 134 of 320

# HTP ER Binding Assays

 3 Assays ( Novascreen , Caliper)

• Human: full length ER, from MCF7 breast cancer cell line

• Bovine: full length ER, from bovine uterus membrane

• Mouse: recombinant murine ER

- alpha ligand binding domain



#  Standard radioligand displacement assays

 Initial Screening (25 μ M, follow

- up with concentration response



# – Single replicate, 8 points (0.02

- 50 μ M)

– Most reference chemicals (positive and negative) run in triplicate

135 

### Slide 135 of 320 

## Appendix F Slide 135 of 320

# NCGC Beta

- lactamase Transactivation (BLA) Agonist Assay

 Assay conducted by NCGC

 Mammalian one

- hybrid system: HEK293T cells stably transfected

• beta

- lactamase

• human ERa ligand

- binding domain fused to a GAL4 DNA binding domain.



#  Should only report ERa activity unless there is heterodimerization with endogenous Erb

 15 concentrations: 92 μ M

– 6 nM

 Blue and green channels measured; response is blue/green ratio

Slide 136 of 320 

## Appendix F

# NCGC Luciferase BG1
Transactivation Agonist Assay

 Conducted by NCGC

 ER responsive human ovarian adenocarcinoma cell line, BG

- 1Luc4E2

• stably transfected with a firefly luciferase reporter construct under control of four estrogen response elements placed upstream of the mouse mammary tumor virus promoter.



#  Cell line from Mike Dennison (UC Davis)

 BG

- 1 cells endogenously express both ERα and ERβ ; ratio not known.

 Reporter gene product: luciferase enzyme: one

- step luciferase assay

 15 concentrations: 92 μ M

– 6 nM

 Lower

- throughput version of BG1 Luc ER TA assay recently validated by OECD
and ECCVAM

Slide 137 of 320 

## Appendix F

# NCGC Assay Plate Layout

Slide 138 of 320

# NCGC Plate Layout

– Concentration

- response series

Slide 139 of 320 

# 15

- point concentration

response series

# OT Luciferase Transactivation Agonist Assay

 Conducted by Odyssey Thera (OT)

 S table CHO

- K1 cell line expressing full length human ERa along with a luciferase reporter gene controlled by estrogen response element placed upstream of the mouse mammary tumor virus promoter

 Reporter gene product:

• Luciferase enzyme with signal read by a one

- step luciferase assay.

• Bioluminescence read using a CCD reader.



#  10 concentrations: 3 nM

- 100 μ M

Slide 140 of 320 

## Appendix F

# Attagene Multiplexed Transcription Factor Agonist Assays

 Conducted by Attagene Inc.

 Modulation of TF activity in human hepatoma HepG2 cells

 Multiplexed reporter gene assay

• cis 52 assays (response element driving reporter)

• trans 29 assays (GAL4

- NR_LBD driving reporter) “ligand detection”

 7

- 9 concentrations: 0.1

- 200 μ M (Highest concentration for any HTP assay)

 Cells harvested, RNA isolated, processed for reporter gene quantitation

Slide 141 of 320 

## Appendix F

# Attagene Technology Cis: AhR

Appendix F Slide 142 of 320

# Chemical Selection and Processing

 ToxCast and Tox21 chemicals were nominated by multiple stakeholders, including EDSP program

• Examples: All SDWA and FIFRA chemicals, TSCA categories, BFRs, Reference chemicals, “alternatives”

• Only about 30% of nominated chemicals could be procured in high purity



#  Chemicals procured through contract lab (CFI)

 Standard protocol:

• Purity >90% required for purchase (80% of samples have >95% purity on CoA )

• Solubilized at 20 mM in DMSO

• Aliquoted into 96

- well plates and frozen

• Shipped to assay labs where serial dilutions are performed



#  Follow

- up analytical QC

• Master plates (20 mM) are checked for identity and purity

• Analysis run on fresh plates and plates left at room temp. for 4 months

• About 30% of QC results are currently available

Slide 143 of 320 

## Section 4: Page 49 and Appendix D

# HTP Data Analysis Overview

 Complexity of data requires robust informatics process

• Data generated by ~15 labs in multiple formats over 3 years

• Multiple data processing methods need to be used

• All methods used are standard in HTP field

• Total ToxCast data set is 28M data points, 1.5M chemical

- assay

curves



#  8

- Level process shown on next slide

• Assays treated almost identically after normalization

• Results are converted to a common format

• Data is stored in ToxMiner database for online browsing

– ToxCast Phase I: http://actor.epa.gov/actor/faces/ToxCastDB/Home.jsp

– All data and software for the high

- throughput assays will be made publicly available during 2013



# • Full transparency

– other researchers can reanalyze all data

Slide 144 of 320 

## Sections 4 and 5: Page 50

# ToxCast Data Analysis Pipeline

Slide 145 of 320 

# 1 2 3 4

Source Raw
Data Files Mapped Raw
Data Files Normalized
Data Files

Curve

- fitting

Hit

- calling Systematic
Alterations Manual
Alterations Outlier Detection

Data Correction 100% PC

0% DMSO 

## Conc

- Resp
Data Files

100% PC

0% DMSO 0.1uM 100uM



# 5 6 7 8

Page 50

# Curve

- Fitting and Hit

- Calling

 A four parameter Hill function is fit to the concentration

- response data using the nls package in R (release 2.14.2) and the port algorithm

 For each chemical

- assay pair, the concentration inducing a half

- maximal response (AC 50 

# ) is derived from the fitted model.

 For a given assay, a chemical is considered a hit if

• it achieves an AC 50



# • the R 2 

# of the model is at least rsq.cutoff , and

• the Emax and T parameter are greater than the resp.cutoff

.

• resp.cutoff :

– 10 MAD (median absolute deviation) around baseline: low conc points



#  For samples tested in technical replicate, the response values are pooled and fit with a single Hill slope to obtain one summary assay call for each substance

Slide 146 of 320 

## Page 50

### Slide 147 of 320 

# Example of Curve Fit

resp.cutoff E2 curve Cytotoxicity curve

Test chemical curve (whiskers= ± 1 SD)

LEC: First conc> resp.cutoff AC50 Masked outliers

Hill

- curve parameters with confidence
intervals

Hill Model: Response=B+(T

- B)*(Conc**W/(AC 50 

# **W +Conc**W))

Page 57

# HTP Data Interpretation: Systematic Classification Process Slide 148 of 320



## ACTIVE

INACTIVE ACTIVE

INACTIVE SETASIDE

DISCARD ACTIVE

INACTIVE Levels 1...5

Level 6 calls

• One chemical at a time

• Use ER assay data only Level 7 calls

• One chemical at a time

• Use auxiliary data ( chemical

purity, cytotoxicity, flare

, autofluorescence, etc.) Chemical Clusters SETASIDE

Level 7 calls

• Look across chemicals

• Use chemical class /

category information


# DISCARD = only for low chemical purity SETASIDE = Requires manual review Page 71

# Example Rule

– Attagene Cell Stress

Slide 149 of 320 

# Included in multiplexed assays are 3 cell stress (including oxidative) endpoints

At higher concentrations cells approaching cytotoxicity often
exhibit non

- receptor mediated

responses.

F ilter out AC 50 

# values above this threshold, or above where a large number of receptor responses turn

on (“Activity Burst”)

Page 52

# Example Rule

- Cytotoxicity

Slide 150 of 320 

# Cytotoxicity in Tox21 transactivation assays (Rules 5, 6): In any cell

- based assay, cytotoxicity can lead to apparent activity in the assay that is not receptor mediated.

The Tox21 BLA assay readout is ratio of two channels, and cytotoxicity can alter one of the channels (the denominator) so that the ratio anomalously rises.

Therefore, ACTIVE calls in Tox21 BLA below or near the cytotoxicity AC 50 

# are changed to SETASIDE.

Page 66

# Example Rule: Autofluorescence Filter

Slide 151 of 320 

# In assays with a fluorescent

- based readout, fluorescent compounds can give a false signal that is not receptor mediated.

All compounds run in red, green and blue detection assays to filter

Page 67

# Example Rule: “Flare”

Slide 152 of 320 

# • Tox21 assays run in 1536

- well plates

• Large number of potent compounds included in library

• In BG1 assay, luminescence of very potent compounds can “leak out” into neighboring wells: “Flare”

• Partial solution: use 3 replicates with compounds having different neighbors

– flare should only show up 1/3 of times

• However, in a region with many positive compounds, this does not always help

Page 68

# Flare Example

Slide 153 of 320 

# Single point above resp.cutoff appears to be caused by flare

Page 69

# Issue Potential solutions being investigated

Cytotoxic or cytostatic compounds Develop structural class filters that indicate cytotoxicity; Look for corresponding activity in other assays using the same cell and readout system but different targets

Surfactants, chelators Develop chemical class filters specifically for these classes

Flare Perform better randomization of replicates; develop better spatial
filter for detector.

Chemical contamination Rebuild sample plates and rerun assays at a later date.

Partial agonists vs. noise level Combine data across assays in a meta

- analysis to look for low but consistent efficacy.

Chemical batch discrepancies Once final analytical QC data is available, discard failing samples.

Activity of weak compounds Combine assays in a meta

- analysis to look for consistent but weak activity at higher concentrations.

Solubility Develop one or more assays that can use another solvent.

Volatility Low

- throughput methods are available to run in vitro assays for volatile compounds, need to scale up.

Metabolic capacity Add assays both with and without metabolic capacity. Larger battery is evaluating HTP ER assays using +/

- S9 fraction. 

# Technical Considerations for Assays

– Not Restricted to ER or HTP

Slide 154 of 320 

## Page 73

# Evaluation of Performance: HTP ER Binding and Transactivation Assays

 Performance of assays compared with the expected outcome for a set of 37 ER (agonist) reference chemicals

• Overall accuracy

• Intra

- laboratory reproducibility (reliability)



#  Performance parameters applicable to HTP technology

• Reproducibility of results for test chemicals

– Intra

- assay variation

– Multiple, independently procured samples of same chemical

– Replication across assays



# • Transferability of data and analysis procedure

Slide 155 of 320

### Slide 156 of 320 CASRN Name ExpectedTox21BG1 LUCTox21BLAATG ERaTRANSATG ERECISOT LUCNVS_NR_hERNVS_NR_bERNVS_NR_mERa

50

- 28

- 2 17beta

- estradiol Strong A A A A A A A A

56

- 53

- 1 Diethylstilbestrol (DES) Strong A A A a A a A a A a A a A a

57

- 63

- 6 17alpha

- ethinyl estradiol Strong A A A A A A A A

84

- 16

- 2 meso

- Hexestrol Strong

- Moderate A A A A A A A A

53

- 16

- 7 Estrone Moderate A A A A A A A A

57

- 91

- 0 17alpha

- Estradiol Moderate A A A A A A A A

68

- 23

- 5 Norethynodrel Moderate A A

68

- 22

- 4 Norethindrone Moderate A A A A A A A A

131

- 55

- 5 2,2',4,4'

- Tetrahydroxy

- benzophenone Moderate A A A A A A A A

140

- 66

- 9 4

- tert

- Octylphenol Weak A A A A A A A A

84852

- 15

- 3 Nonylphenol (branched) Weak A A A A A A A A

80

- 05

- 7 Bisphenol A Weak A A A A A A A A

1478

- 61

- 1 Bisphenol AF Weak A A A A A A A A

77

- 40

- 7 Bisphenol B Weak A I b A A I i A A A

599

- 64

- 4 4

- Cumylphenol Weak A A A A A A A A

143

- 50

- 0 Kepone Weak A A A A I i A I A

434

- 22

- 0 19

- Nortestosterone Weak A A

58

- 18

- 4 17alpha

- Methyltestosterone Weak A A A A I i A I I

446

- 72

- 0 Genistein Weak A A A A A A A

479

- 13

- 0 Coumestrol Weak A A c
520

- 18

- 3 Kaempferol Weak A A A A I I

520

- 36

- 5 Apigenin Weak A A A A A I I

486

- 66

- 8 Daidzein Weak A A A A A A A A

789

- 02

- 6 o,p'

- DDT Weak A A A A I j I I I

94

- 26

- 8 Butylparaben Weak A A A A A A A A

120

- 47

- 8 Ethylparaben Very Weak A A d A A I i A I I

85

- 68

- 7 Butylbenzyl phthalate Very weak A A A I i I I I

72

- 43

- 5 Methoxychlor Very Weak A e I b A A I i A h I I

1912

- 24

- 9 Atrazine Negative I I I I I I I I

330

- 55

- 2 Linuron Negative I I I I I I I I

50

- 06

- 6 Phenobarbital Negative I I

57

- 30

- 7 Phenobarbital Sodium Negative I I I I I I I I

52

- 01

- 7 Spironolactone Negative I I I I I I I I

50

- 22

- 6 Corticosterone Negative I I A b A I I I I

57

- 83

- 0 Progesterone Negative I I A g A g I A A I

520

- 86

- 8 Haloperidol Negative I I I A I I I I

65277

- 42

- 1 Ketoconazole Negative I I I I I I I I 

## Table 6.2.1 Page 78 

# Results for 8 ER HTP Assays When Testing Reference Chemicals

Agrees with expectation

Expected active,
measured negative

Fails auto filter,
but manual call
indicates
active

Expected inactive,
measured
active

# Tox21 BLA: Ambiguous Cases

Slide 157 of 320 

# Partial Agonists at noise threshold Same chemical, 2 samples,
different calls

Possible interference
From autofluorescence

# Non

- concordance with expected results for reference chemicals:
ATG “False Positives” Slide 158 of 320

# Progesterone: Positive in multiple assays

Slide 159 of 320 

# In Tox21 BG1 assay, 3 independently procured samples give same borderline activity

# Performance Statistics For Assay Accuracy Using Reference Chemicals

Slide 160 of 320Tox21 BG1 LUCTox21 BLAATGERaTRANSATG ERE CISOT LUCNVS_NR_hERNVS_NR_bERNVS_NR_mERa



## Reference Chemicals Tested (Actives/ Inactives ) 28/9 27/9 23/8 24/8 25/8 24/8 25/8 25/8
Concordance 1

, 4 

## 1 0.94 0.94 0.91 0.79 0.91 0.73 0.78 Sensitivity 2 

## 1 0.93 1 1 0.72 0.92 0.68 0.71 Specificity 3 

## 1 1 0.75 0.63 1 0.88 0.88 1

Pages 81

- 82, Table 6.2.3 

# • The Tox21 and ATG TA assays displayed high levels of concordance and sensitivity ( e.g. , proportion of all active chemicals correctly classified).

• Of the 3 ER binding assays, the NVS_NR_hER displayed the highest level of concordance and sensitivity.

# Performance Statistics Reproducibility Using Reference Chemicals

 Standard deviations (SD) for the assay response of technical replicates at each
concentration were calculated for each reference chemical.

 Mean SDs (across full concentration response) ranged from 1.2 to 23.7% relative to a maximal response of 100%.

 Lower SDs (Tox21BG1); Higher SDs (ATG ERa Trans)

Slide 161 of 320 

## Tox21
BG1
LUC Tox21

BLA ATG ERa
TRANS ATG

ERE
CIS OT
LUC NVS_ NR_
hER NVS_
NRbE

R NVS_

NR
mERa

17b

- estradiol 

## 8.1 4.4 7.8 6.0 9.6 1.2 2.7

-

Norethinodrone 

## 7.8 2.8 11.6 6.4 7.1 16.2 6.2 8.4

Kepone 

## 5.9 2.8 7.3 5.0 1.6 7.3 8.5 13.7

Atrazine 

## 3.3 2.3 11 1.9 1.3 4.6 5.5 8.2



## Pages 81

- 82, Table 6.2.4 Table 6.2.4: Comparison of mean SDs for assay response of technical replicates for ER agonists for the 8 ER HTP Assays

# Assay Reproducibility: Across Independently Procured Samples

Slide 162 of 320 

## Page 88

- 89, Table 6.3.3 

# Data has not yet been filtered for analytical QC failures

# Concordance Among Different Assays

Slide 163 of 320 

## Page 91

# Transferability of Data: HTP ER Assays

 Pilot study is ongoing to evaluate the transferability of data and consistency in classification of chemicals when using same or similar data analysis procedures and classification criteria

• Data from the Tox21 BG1 Luc and BLA TA assays currently being independently evaluated by Federal Agencies within Tox21 Consortium

• Results to be available mid

- 2013

Slide 164 of 320

# Summary: HTP ER Assays

 8 HTP ER assays described

• Multiple orthogonal assays

• Intended use is as a battery

• Each assay has strengths and limitations



#  Question to be addressed:

• “Does this chemical interact with the estrogen receptor in vitro?”



#  Data has been generated and analyzed on large number of chemicals

• Systematic, transparent process used to process and display data



#  Challenges

• Process for combining across battery to increase confidence in prediction

Slide 165 of 320

### Slide 166 of 320 

# Preliminary Findings of Comparative Analysis of HTP vs. ER Expert System Training Set Data

Dr. Mike Hornung Office of Research and Development
National Health and Environmental Effects Research Laboratory
Mid

- Continent Ecology Division

# EDSP Universe of Chemicals n= 10,341

Chemical
Lists FIFRA Registration Review
Schedule for Active Ingredients (Approx.=1500) SDWA and INERTS (Approx.=9000)

Physico

Chemical Properties

(Approx n=5000) 

# Excluded

Exposure
Potential

SDWA 

# Lower Priority

ER Expert System

High through put
system 

# Prioritized List of Chemicals for EDSP Tier 1 Screening yes

No * Mixtures will be lower priority

no

Yes 

# Considerations of Read

Across and Chemical Categories

Slide 167 of 320

# 1) Determine ESv1 coverage of EDSP chemicals to prioritize for T1S (Sec 3)

2) Build ESv2 and determine coverage of EDSP chemicals to prioritize for T1S (Sec3)

3) Identify remaining chemicals with Unknown Binding Potential ( UnkBP )
i.e. , those outside ESv2 model domain (Sec 3)

4) Determine where HTP data covers UnkBP chemicals (Sec 8)

5) Determine if and how HTP data could be used to expand TrSet to cover UnkBP chemicals. (Sec 4, 5, 6, 7, 8) 

# Moving Incrementally:

5 Goals

ESv1

ESv2

ESv3

Slide 168 of 320

# Outline of Section 7 Presentation

 Chemicals used in analysis

 Review of in vitro assays used as TrSet , additional information, and decision process

 Agreement between in vitro TrSet and in vitro HTP assays:

• Binding assays

• TA assays

• Binding & TA; chemical groups

 Examples of factors that can contribute to assay discordance

Slide 169 of 320

# Chemicals Included in Analysis

 296 Chemicals

 Represent broad range of chemical classes

 Cover Log K
ow 

# range within those classes.

 Covered EPA inventories: Food

- use Inerts and Antimicrobials

 Includes Active and Inactive chemicals/classes

Rainbow Trout Training Set

HOB LogKow = 7.29 CLogP
CAS# 1843

- 05

- 6

RBA = NB

O

O H O C H 3

THBP LogKow = 2.20 CLogP
CAS# 131

- 55

- 5
RBA = 0.1077 O

O H O H

O H O H

DHDPK LogKow = 3.01 msrd

CAS# 131

- 56

- 6
RBA = 0.032 O

O H O H

HBO LogKow = 3.52 msrd

CAS# 117

- 99

- 7
RBA = 0.00097 O

O H

HMBP LogKow = 3.79 CLogP
CAS# 131

- 57

- 7
RBA = 0.0010 O

O H O C H 3



### Slide 170 of 320

# Data Available at time of Analysis: 5 HTP Assays

 3 ER Binding Assays ER Source Total Protein (mg/ml)
1) 

# NVS mERα recombinant LBD 0.00028 2) NVS hER MCF7 cell lysate 0.28 3) NVS bER bovine uterine cytosol 5.6

• [3H]

- E2 displacement endpoint for all three

• Highest conc tested: 25μM prescreen; 50 μM dose

- response



#  2 TA Assays. ER

- mediated reporter gene assays:

1) Tox21_BLA_ERa_LBD Fluorescence readout 2) Tox21_BG1_ERα/ß (endogenous) Luciferase readout

• Highest conc tested: 92μM

Slide 171 of 320

# Review of in vitro TrSet Assays for Prioritization

 Rainbow trout ER competitive binding assay

• Trout liver cytosolic receptors (endogenous ERs)

• Endpoint: 3H

- E2 displacement

• Highest conc tested: chemical solubility in assay media

• Chemical interaction at ER (MIE of ER

- mediated AOP)

 Rainbow trout liver slice vitellogenin gene activation

• Endpoint: Vitellogenin mRNA

• Highest conc tested: chemical solubility in assay media, or cytotoxicity if
noted at lower conc.

• Verification of parent ER activity further along ER AOP

• Includes endogenous metabolism allowing investigation of metabolic

activation

Slide 172 of 320

### Cyto rtER binding: Reproducible Results

Type A Displacement: 80% or greater 

# Decision Path Step 1: Analyze Binding Displacement Curve to Trigger Next Step

Type B Displacement:
50 to 80% Type C Displacement:
20 to 50% Type D Displacement:
5 to 20% Type E Displacement:
Flatline / skijump

Slide 173 of 320

## yes Perform Slice Vtg Assay: chemical produces agonist or antagonist response?



## yes Chemical log Kow
within the active range of TrSet class? Known active TrSet
class?

classified

as BINDER

RBA
calculated chemical
classified as 

### Nonbinder



## no yes Good shape to cyto
rtER binding curve? 

## no

no no Does chemical belong to

a TrSet chemical class known to produce false positive results?



## no Possible
false +

*Perform Ki binding:
Is the chemical a competitive binder? 

## yes

*To date no chemical has been inactive in slice assay and a competitive binder in the Ki assay 

## yes yes

no Type A Example: >80% displacement Type B Example:

50

- 80% displacement 

## Decision Path Step 2 for Type A & Type B Displacement Curves: Type A: >80% displacement; in untested class; Type B: 50 to 80% displacement

Slide 174 of 320

### Perform Slice Vtg Assay: chemical produces agonist or antagonist response?



## yes

classified as

BINDER:

RBA
calculated chemical
classified as 

### Nonbinder 

## no yes Good shape to cyto
rtER binding curve? 

## no

no Does chemical belong to

a TrSet chemical class known to produce false positive results?



## no Possible
false +

Perform rec rtER binding: Does chemical produce displacement? 

## yes yes

Hold parent chemical in under investigation bin Type C Example: 20 to 50% displacement 

## Decision Path Step 2 for Type C Displacement Curves: Type C: 20% to 50% displacement

Assay protein comparison:
cyto rtER = 4 mg/ml

rec rtER = 0.01 mg/ml 

## Possible
metabolism

Slide 175 of 320

# Assay Total Protein Affects Chemical Bioavailability (Free Fraction)

-11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 10 20 30 40 50 60 70 80 90 100 110



## Concentration (log M)% Specific Binding 

### E2 Phenol

cyto rtER rec rtERα

E2

Phenol

Total
Protein (mg/mL) 4 0.01

RBA (%) 0.000026 0.0025 

# Lower total assay protein, lower applied chemical conc

Higher total assay protein, higher applied chemical conc Same chemical
free fraction displacing 3 

# H

- E2

Slide 176 of 320

### no Perform Slice Vtg Assay: chemical produces agonist or antagonist response?

yes classified as

BINDER : RBA
calculated chemical
classified as Nonbinder Chemical belongs to
known inactive TrSet
chemical class? 

## no

NO* 

## no Evidence in scientific literature, or chemical structure to suggest potential for binding?



## yes

Perform rec rtER binding:
Does the chemical produce displacement? 

## yes yes

no Possible
metabolism

to active I.D.
bioactive metabolite,
classified as BINDER yes



## * To date no chemical has followed this path Hold parent chemical in under investigation bin Type E Example:
Flatline 

## Decision Path Step 2 for Type E Displacement Curves: Type E: Flatline or “ skijump ” displacement

Parent
chemical
classified as
Nonbinder

Slide 177 of 320

# ER Binding Assays

Slide 178 of 320

### A B

C D

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,2',4,4'-Tetrahydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%) 131

- 55

- 5

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,4-Hydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%) 131

- 56

- 6

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-HydroxyBenzophenone

Log Concentration (M)[3H]-E2Binding (%) 117

- 99

- 7

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-Hydroxy-4-methoxybenzophenone

Log Concentration (M)[3H]-E2Binding (%) 131

- 57

- 7 

## 50 μM 

# Effect of Concentration cut

- off in Binding Assays

 4 TrSet actives; If all factors equal, would expect only A & B likely ACTIVE in NVS ER binding assays (below cut

- off).

O O H

O

C H 3 O O H

O H O O H

O H O H O H

O O H 

### A B

C D

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,2',4,4'-Tetrahydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%) 131

- 55

- 5

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,4-Hydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%) 131

- 56

- 6

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-HydroxyBenzophenone

Log Concentration (M)[3H]-E2Binding (%) 117

- 99

- 7

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-Hydroxy-4-methoxybenzophenone

Log Concentration (M)[3H]-E2Binding (%) 131

- 57

- 7 

## 50 μM 

# rtER binding assay results

A B

C D

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,2',4,4'-Tetrahydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%) 131

- 55

- 5

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,4-Hydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%) 131

- 56

- 6

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-HydroxyBenzophenone

Log Concentration (M)[3H]-E2Binding (%) 117

- 99

- 7

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-Hydroxy-4-methoxybenzophenone

Log Concentration (M)[3H]-E2Binding (%) 131

- 57

- 7 

## 50 μM

Slide 179 of 320

# Effect of Concentration Cut

- off in Binding Assays

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,2',4,4'-Tetrahydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%)

O O H

O H O H O H 

#  A. 2,2’,4,4’

- Tetrahydroxybenzophenone was active in NVS binding assays

rtER NVS mERa

NVS hER

NVS bER 50 μM LBD total protein

= 0.00028 mg/ml

Full ER total protein = 0.28 mg/ml

Full ER total protein

= 5.6 mg/ml Full ER total protein

= 4 mg/ml

Slide 180 of 320

# Effect of Concentration Cut

- off in Binding Assays

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 2,4-Hydroxybenzophenone

E2

Log Concentration (M)[3H]-E2Binding (%)

O O H

O H 

# rtER NVS mERa

NVS hER

NVS bER (inactive) 

#  B. 2,4

- Hydroxybenzophenone was active in NVS binding assays

50 μM LBD total protein

= 0.00028 mg/ml

Full ER total protein = 0.28 mg/ml

Full ER total protein

= 5.6 mg/ml Full ER total protein

= 4 mg/ml

Slide 181 of 320

# 2

- Hydroxybenzophenone 2

- Hydroxy

- 4

- methyoxybenzophenone 

# Effect of Concentration Cut

- off in Binding Assays

Inactive in 25 μM pre

- screen O O H

O

C H 3 O O H



## Inactive in 25 μM pre

- screen 0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-HydroxyBenzophenone

Log Concentration (M)[3H]-E2Binding (%) 117

- 99

- 7

0 10 20 30 40 50 60 70 80 90 100 110

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL E2 2-Hydroxy-4-methoxybenzophenone

Log Concentration (M)[3H]-E2Binding (%) 131

- 57

- 7 

# rtER rtER

NVS mERa

, hER , and bER NVS mERa

, hER , and bER  C. & D. Lower affinity benzophenones were Inactive in NVS due to concentration cut

- off

Slide 182 of 320

# Additional Replication Would Increase Confidence

Triphenylethylene cyto rtER binding

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 E2
3PE

CTRL[3H]-E2 Binding (%)

Log Concentration (M) Triphenylethylene 

# mERa

hER

bER rtER

NVS binding: n=1 tech replicate / conc / run n=1 run per chemical 

# TrSet binding: n=2 tech replicates / conc /run n=2 runs per chemical, using different trout liver ER prep for each LBD total protein

= 0.00028 mg/ml

Full ER total protein = 0.28 mg/ml

Full ER total protein

= 5.6 mg/ml Full ER total protein

= 4 mg/ml

Slide 183 of 320

## 50 μM 

# rtER
mERa

hER

bER TrSet binding n=2 tech replicates / conc /run n=3 runs per chemical, using different trout liver ER prep for each



# NVS binding: n=1 tech replicate / conc / run n=1 run per chemical 

# Additional Replication would Increase Confidence?

LBD total protein

= 0.00028 mg/ml

Full ER total protein = 0.28 mg/ml

Full ER total protein

= 5.6 mg/ml

Slide 184 of 320

# Chemical Bioavailability? LBD vs Full Receptor?

mERa 0.00028 mg/ml



# hER 0.28 mg/ml



# bER 5.6 mg/ml 

##  however, mER
Inactive for t

- pentyl cyclohexanone  mER appears most sensitive for
chlorhexidine
diacetate

Slide 185 of 320

# Activity of TrSet Chemicals Among all Binding Assays

Comparison of INACTIVES hER Inactive bER Inactive mERa Inactive All three NVS ER binding Inactive

172 chemicals in TrSet with RBA=0 (Inactive) 158 (92%) 164 (96%) 161 (94%) 152 (88%)



#  INACTIVES in TrSet assays were generally also inactive in NVS binding assays.
≈ 90%

 This might be expected due to pre

- screen and conc cutoffs tending to yield Inactive result for lower affinity chemicals

TrSet Actives hER Active bER Active mERa Active Any HTP ER
Active

124 chemicals in TrSet with RBA > 0 (Active) 42 (34%) 31 (25%) 29 (23%) 44 (35%)



##  

# ≈ 30% of ACTIVES in TrSet assays were HTP ACTIVES

Slide 186 of 320

## ES TrSet RBA (%) Number of TrSet
Actives Percentage Matching TrSet

NVS

- hER NVS

- bER NVS

- mERa

RBA > 1 * 

## 7 86% 86% 100%

0.1 ≤ RBA < 1 7 100% 100% 86%

0.01 ≤ RBA < 0.1 18 56% 33% 39%

0.001 ≤ RBA < 0.01 33 30% 21% 18%

0.0001 ≤ RBA < 0.001 36 17% 8% 6%

0.00001 ≤ RBA < 0.0001 22 0 0 0 

# Number of Active Chemicals in Binding Assays by TrSet RBA

 ES TrSet assays optimized for lower affinity chemicals resulting in more Actives than NVS assays run with prescreen and cutoffs

 Among NVS assays, hER assay may identify more positives than bER or mERa

Slide 187 of 320

# Binding Assays Summary

 Differences in assay components and how the assays are
run can influence the results:

• Concentration cutoff: Most discordance between

NVS in vitro binding activity and in vitro TrSet assays could be explained by concentration cut

- off

• LBD or Full receptor?

• Chemical bioavailability

 Lack of replication for some chemicals can limit interpretation of activity

Slide 188 of 320

# Gene Activation Assays

ER

- mediated gene assays:

Tox21 in vitro TA Assay Endpoint Readout Metabolism Tox21_BLA_ERa LBD 5X

- UAS

ßLactamase + GAL4_hER α LBD = ß

- lactamase Fluorescence considered low for

HEK

- 293 cells

Tox21_BG1_ER α/ ß (endogenous) ERE pGudLuc7.0 (4 EREs ) = luciferase Luminescence Unknown

TrSet in vitro TA Assay Endpoint Readout Metabolism
trout liver slice ( endogenous ERs ) Vtg mRNA (endogenous) QPCR Phase I & Phase II (endogenous)

Slide 189 of 320

# Interpreting Gene Activation Assays

Factors affecting interpretation:

- Concentrations tested (cutoffs)

- Test chemical interferences with endpoint readout

– e.g. , fluorescence

- Cytotoxicity

- Chemical Solubility

- Media pH

- Parent chemical vs metabolites.

- Is metabolism the cause of activity ?

- If so, what evidence is there ?

- Is the structure of a putative metabolite a likely ER binder?

e.g. , verifying presence of active metabolite supports more accurate classification of parent structure (e.g., as Nonbinder ) and metabolite
as Binder

Slide 190 of 320

# Concentration Cut

- off & Sensitivity in TA Assays

 Concentration cut

- off may also affect the response of the TA assays

• Activity in trout liver slice Vtg assay did not occur until concentration reached

- 4logM (100 μM) and higher.

• If BLA, BG1 and trout Vtg assays all have similar sensitivity for this chemical, would expect to see some activity in BLA and BG1 (at least one pt activity?) trout liver slice Vtg mRNA Tox21_ERa_BLA Tox21_ERa_BG1

1.0 × 10 5 1.0 × 10 6 1.0 × 10 7 1.0 × 10 8

-10 -9 -8 -7 -6 -5 -4 -3 -2 AAN

E 2
CONTROL

CTRL n-Amylaniline (pentylaniline) trout liver slice Vtg mRNA

Log Concentration (M)VTG mRNA copies/400 ng total RNA 

# A B C

Slide 191 of 320

# Interpretation of Activity within Chemical Groups: Alkylbenzenethiols

rtER binding: Inactive Inactive

mER binding: Inactive Active
hER binding: Inactive Active
bER binding: Inactive Active

Tox21

- BLA: Inactive Inactive
Tox21

- BG1: Inactive Active C H 3

C H 3 C H 3 S H 

## 4

- t

- butylbenzenethiol [2396

- 68

- 1] p

- toluene thiol [106

- 45

- 6]

C H 3 S H



### Slide 192 of 320

# rtER Binding: Alkylbenzenethiol Example

C H 3

C H 3 C H 3 S H 

## 4

- t

- butylbenzenethiol [2396

- 68

- 1] p

- toluene thiol [106

- 45

- 6] C H 3 S H

trout liver cytosolic rtER binding mean & se

0 25 50 75 100 125 150 175

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 E2 4-t-butylthiophenol

CTRL ppt

Log Concentration (M)[3H]-E2Binding (%) trout liver cytosolic rtER binding mean & se

0 25 50 75 100 125 150 175

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 E2 4-methylbenzenethiol

CTRL

Log Concentration (M)[3H]-E2Binding (%)



### Slide 193 of 320

# NVS Binding: Alkylbenzenethiol Example

NVS mERa

NVS hER

NVS bER C H 3

C H 3 C H 3 S H 

## 4

- t

- butylbenzenethiol [2396

- 68

- 1] p

- toluene thiol [106

- 45

- 6] C H 3 S H



## Inactive in 25 μM prescreen

Inactive in 25 μM prescreen

Inactive in 25 μM prescreen

Slide 194 of 320

# BLA Assay: Alkylbenzenethiol Example

C H 3

C H 3 C H 3 S H 

# 4

- t

- butylbenzenethiol [2396

- 68

- 1] p

- toluene thiol [106

- 45

- 6]

C H 3 S H



### Slide 195 of 320

# BG1 assay: Alkylbenzenethiol Example

C H 3

C H 3 C H 3 S H 

# 4

- t

- butylbenzenethiol [2396

- 68

- 1] p

- toluene thiol [106

- 45

- 6]

C H 3 S H



### Slide 196 of 320

# Interpretation of Benzenethiol Results

C H 3

C H 3 C H 3 S H 

# 4

- t

- butylbenzenethiol [2396

- 68

- 1] p

- toluene thiol [106

- 45

- 6] C H 3 S H



# “Active” Inactive

Options to understand activity of this chemical class

 Test chemicals in trout liver slice Vtg assay (only rtER binding to this point).

 Expand chemicals in this class to establish greater confidence in structure

activity relationships • Inactive in all assays • Inactive in rtER Binding Assay

• Inactive in BLA Assay

• Active in NVS Binding and BG1 Assay

• Influence of flare effect on BG1 ?

However, only EDSP Inventory chemical is benzene thiol and salt form. inactive

C H 3 S H C H 3

C H 3 C H 3 S H S H

C H 3



### n
- butylbenzenethiol active

pentylbenzenethiol S H

C H 3



### 4

- t

- butylbenzenethiol p
- toluene thiol test ? test ?

benzenethiol

S H



### Slide 197 of 320

# Interpretation of Activity within Chemical Groups:
Benzotriazole Phenols

rtER binding: Inactive Inactive

mER binding: Active Inactive
hER binding: Inactive Inactive
bER binding: Inactive Inactive
Tox21

- BLA: Inactive Inactive
Tox21

- BG1: Active Inactive

Slide 198 of 320

# rtER Binding: Benzotriazole Phenols Example

trout liver cytosolic rtER binding mean & se

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 E2
BMBP

CTRL

Log Concentration (M)[3H]-E2Binding (%) trout liver cytosolic rtER binding mean & se

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 E2
HMP

CTRL

Log Concentration (M)[3H]-E2Binding (%)



### Slide 199 of 320

# NVS Binding: Benzotriazole Phenols Example

NVS mERa

NVS hER

NVS bER Inactive in 25 μM prescreen Inactive in 25 μM prescreen N

N

N O H

C H 3 C H 3 C H 3

C H 3 C H 3 N N N O H

C H 3 

## 2

- (2

- hydroxy

- 5

- methylphenyl)

- benzotriazole 2

- (2

- hydroxy

- 5

- t

- octylphenyl)

- benzotriazole

Slide 200 of 320

# BLA Assay: Benzotriazole Phenols Example

All 3 source replicates Inactive All 3 source replicates Inactive N

N

N O H

C H 3 C H 3 C H 3

C H 3 C H 3 N N N O H

C H 3 

## 2

- (2

- hydroxy

- 5

- methylphenyl)

- benzotriazole 2

- (2

- hydroxy

- 5

- t

- octylphenyl)

- benzotriazole

Slide 201 of 320

# BG1 Assay: Benzotriazole Phenols Example

all 3 chemical source replicates Inactive All 3 chemical source replicates Active N

N

N O H

C H 3 C H 3 C H 3

C H 3 C H 3 N N N O H

C H 3 

## 2

- (2

- hydroxy

- 5

- methylphenyl)

- benzotriazole 2

- (2

- hydroxy

- 5

- t

- octylphenyl)

- benzotriazole

setaside (flare)



### Slide 202 of 320

# Interpretation of Benzotriazole Phenols Results

N

N

N O H

C H 3 C H 3 C H 3

C H 3 C H 3 N N N O H

C H 3 

## 2

- (2

- hydroxy

- 5

- methylphenyl)

- benzotriazole 2

- (2

- hydroxy

- 5

- t

- octylphenyl)

- benzotriazole



# • equivocal responses among assays

• may call parent chemical Inactive based upon all binding assays

• flare effect present at high

concentration in BG1

• can hypothesize metabolic
activation but need verification • Inactive in all assays

Slide 203 of 320

# Potential Signal Artifacts ?

Charged Species

 Charged species _FP (2009 SAP)

• Octylbenzene sulfonic acid, false positive binding, Ki determinations

 Dodecylbenzene sulfonic acid (DBS) produced similar false positive binding

0 10 20 30 40 50 60 70 80 90 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 CTRL Dodecylbenzenesulfonic acid rtER Binding

E2

Log Concentration (M)[3H]-E2Binding (%) 

# NVS mERa NVS hER NVS bER ERES rtER S O

O O H

C H 3



### Slide 204 of 320Dodecylbenzenesulfonic acid trout Vtg Gene Expression PCR_8.28.6

1.0×10 3 1.0×10 4 1.0×10 5 1.0×10 6 1.0×10 7

-10 -9 -8 -7 -6 -5 -4 -3 -2 DBS

E 2
CTRL

CTRL

Log Concentration (M)VTG mRNA copies/400 ng total RNA Dodecylbenzensulfonic Acid rtER Gene Expression:Antagonist Mode

1.0×10 4 1.0×10 5 1.0×10 6

-10 -9 -8 -7 -6 -5 -4 -3 -2 DBS + E2 at -8 log M

E2

Control

CTRL LDH

Log Concentration (M)VTG mRNA copies/400 ng total RNA LDH Leakage LDH 8.28.6

0 25 50 75 100 125 150 175 200

-10 -9 -8 -7 -6 -5 -4 -3 -2 DBS 48h

E 2 48h

Ctrl 48h

CTRL

Log Concentration (M)Leakage % of Total LDH



#  DBS produced no Vtg induction = Inactive

 Drop in E2 response in antagonism mode was coincident with cytotoxity = Inactive

 Results supports conclusion that DBS is Nonbinder

 pKa =

- 1.84. Would be flagged by pKa filter trout Vtg slice: agonism assay trout Vtg slice: antagonism assay trout Vtg slice: Cytotoxicity Assay

S O

O O C H 3



### Slide 205 of 320 

# Potential Signal Artifacts ?

Charged Species

# 8

- Hydroxyquinoline Sulfate

 Showed apparent binding in NVS hER and TrSet assays.

 In TrSet assay the apparent binding was coincident with reduced pH.

 False binding may be produced by changes in assay pH 0 20 40 60 80 100

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 CTRL 8-Hydroxyquinoline Sulfate rtER Binding

E2 8HQ

Log Concentration (M)[3H]-E2Binding (%) pH Data 8HQ in cytosol

-11 4 5 6 7 8 9

-4 -3 -2 -1 Time: 0h
Time: 20h

Log Concentration (M)pH 

# trout liver cytosol rtER binding NVS hER N O H S

O O

O H



### Slide 206 of 320 

# Potential Signal Artifacts ?

pH8-Hydroxyquinoline Sulfate liver slice Vtg mRNA_agonist PCR 8HQ

1.0×10 3 1.0×10 4 1.0×10 5 1.0×10 6 1.0×10 7 1.0×10 8

-10 -9 -8 -7 -6 -5 -4 -3 -2 CTRL 8HQ

E2

control

Log Concentration (M)VTG mRNA copies/400 ng total RNA 8-Hydroxyquinoline Sulfate Vtg mRNA _ antagonist PCR 8HQ

1.0×10 3 1.0×10 4 1.0×10 5 1.0×10 6 1.0×10 7

-10 -9 -8 -7 -6 -5 -4 -3 -2 CTRL 8HQ+E2-9
8HQ+E2-6

E 2 control

Log Concentration (M)VTG mRNA copies/400 ng total RNA pH of Slice Media 8-Hydroxyquinoline Sulphate

6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2

-5 -4 -3 -2 Expt. 0524 Expt. 0907 Expt. 0927

CTRL Concentration (log M)pH of Slice Media 

#  Test Chemical effect on assay pH can also affect gene induction

trout Vtg slice: agonism assay trout Vtg slice: antagonism assay trout Vtg slice: Assay Media pH

 8HQ produced no Vtg induction

 Drop in E2 response in antagonism mode was independent of E2 concentration, and was coincident with pH decrease

 pKa filter would flag this chemical. pKa =

- 3.96. Only ionized forms at assay pH.
Slide 207 of 320 

# Potential Signal Artifacts ?

pH

# Activity Due to Metabolism ?

NO binding but GA

– possible bioactivated Metabolite

Slide 208 of 320

# Metabolic Activation?

Methyltestosterone

NVS mERa NVS hER NVS bER

TrSet rtER

Binding curves show no or only partial displacement

Slide 209 of 320

# Activity Due to Metabolism:

Methyltestosterone

Tox21_BG1 Tox21_BLA

 Low/no activity in binding but strong activity in cell

- based assays suggests metabolism

 Verified the 17methyltestosterone to 17methylestradiol conversion in fish

 17methylestradiol has high affinity (RBA=68%) for the fish ER

 Call: 17methyltestosterone = NONBINDER and 17methylestradiol = BINDER

 Apparent discordance is actually agreement if metabolic conversion to bioactive
metabolite is verified in BG1 and BLA

Slide 210 of 320

#  Discordant calls were mostly ES TrSet chemicals with low affinity

 Discordant calls were in multiple chemical classes

Chemical Class No. of chemicals RBA (%) Range Log K ow 

### range

Acyclic_Perfluoro 1 0.00052 6.3

Special Rule Class

DDT

- like Exact Match 3 0.016

– 0.023 5.87

– 6.79 Phosphoric Acid Esters 2 0.0012

– 0.0019 4.70

– 6.30 Thiophosphate Esters 1 0.00067 3.44 Alkylchlorobenzenes 2 0.00016

– 0.00018 4.66

– 5.15

A

- type Alkylphenols 11 0.000026

– 0.0035 1.51

– 5.33 Alkoxyphenols 2 0.000025

– 0.00079 1.59

– 3.50 Parabens (non

- benzoate) 1 0.00015 2 Salicylates (non

- Benzoate) 4 0.000062

– 0.0017 2.60

– 6.16

2

- Hydroxy Benzophenones 1 0.00097 3.44
Mixed Phenol

- Exact Match 2 0.00019

– 0.00079 1.91

– 2.94

B

- type

4

- Alkylaniline 3 0.00007

– 0.0015 1.62

– 4.08

4

- Alkoxyaniline 1 0.000064 2.63 Phthalates 1.6<LogK ow 

### <6.6 4 0.000066

– 0.00046 2.65

– 6.57 Phenones (Branched) 2 0.00007

– 0.00009 2.58

– 3.04 Alkylcyclohexanols 2 0.00024

– 0.00030 3.53

– 4.32

2

- ;4

- ; or 2,4,6

- Benzoates 2 0.00005

– 0.0001 2.87
Phenones cyclo

- substituted 1 0.00013 2.96 Cyclohexanones 1 0.00011 2.53 Mixed Organics

- Exact Match 11 0.000029

– 0.0026 2.05

– 5.02 Slide 211 of 320 

# Chemicals Inactive in 5 HTP Assays But Active in ES TrSet Assays

# Chemicals Inactive in 5 HTP Assays But Active in ES TrSet Assays

 Discordant calls were mostly ES TrSet chemicals with low affinity

 Discordant calls were in multiple chemical classes

Chemical Class No. of chemicals RBA (%) Range Log K ow 

### range Acyclic_Perfluoro 1 0.00052 6.3

Special Rule Class

DDT

- like Exact Match 3 0.016

– 0.023 5.87

– 6.79 Phosphoric Acid Esters 2 0.0012

– 0.0019 4.70

– 6.30 Thiophosphate Esters 1 0.00067 3.44 Alkylchlorobenzenes 2 0.00016

– 0.00018 4.66

– 5.15

A

- type Alkylphenols 11 0.000026

– 0.0035 1.51

– 5.33 Alkoxyphenols 2 0.000025

– 0.00079 1.59

– 3.50 Parabens (non

- benzoate) 1 0.00015 2 Salicylates (non

- Benzoate) 4 0.000062

– 0.0017 2.60

– 6.16

2

- Hydroxy Benzophenones 1 0.00097 3.44
Mixed Phenol

- Exact Match 2 0.00019

– 0.00079 1.91

– 2.94

B

- type

4

- Alkylaniline 3 0.00007

– 0.0015 1.62

– 4.08

4

- Alkoxyaniline 1 0.000064 2.63 Phthalates 1.6<LogK ow 

### <6.6 4 0.000066

– 0.00046 2.65

– 6.57 Phenones (Branched) 2 0.00007

– 0.00009 2.58

– 3.04 Alkylcyclohexanols 2 0.00024

– 0.00030 3.53

– 4.32

2

- ;4

- ; or 2,4,6

- Benzoates 2 0.00005

– 0.0001 2.87
Phenones cyclo

- substituted 1 0.00013 2.96 Cyclohexanones 1 0.00011 2.53 Mixed Organics

- Exact Match 11 0.000029

– 0.0026 2.05

– 5.02 O H

C H 3

LogKow = 3.20 msrd

CAS# 645

- 56

- 7 RBA = 0.00088 C H 3

C H 3

C H 3 O H LogKow = 3.30 msrd

CAS# 585

- 34

- 2 RBA = 0.00091 C H 3 O H

LogKow = 2.47 msrd

CAS# 123

- 07

- 9 RBA = 0.00036



## HTP Inactive HTP Inactive HTP Inactive O H C H 3

C H 3

C H 3

LogKow = 3.31 msrd

CAS# 98

- 54

- 4 RBA = 0.0014 C H 3

C H 3

C H 3 O H LogKow = 3.31 msrd

CAS# 88

- 18

- 6 RBA = 0.0018

O H C H 3

C H 3

LogKow = 3.32 msrd

CAS# 99

- 71

- 8 RBA = 0.0018 C H 3

C H 3 O H

LogKow = 3.27 msrd

CAS# 89

- 72

- 5 RBA = 0.0010 O H

C H 3

LogKow = 3.65 msrd

CAS# 1638

- 22

- 8 RBA = 0.0035 

## BLA Active BLA Active

HTP Inactive HTP Inactive HTP Inactive 

# Alkylphenols : TrSet Actives

Slide 212 of 320

# Chemicals Inactive in 5 HTP Assays But Active in ES TrSet Assays

 Discordant calls were mostly ES TrSet chemicals with low affinity

 Discordant calls were in multiple chemical classes

Chemical Class No. of chemicals RBA (%) Range Log K ow 

### range Acyclic_Perfluoro 1 0.00052 6.3

Special Rule Class

DDT

- like Exact Match 3 0.016

– 0.023 5.87

– 6.79 Phosphoric Acid Esters 2 0.0012

– 0.0019 4.70

– 6.30 Thiophosphate Esters 1 0.00067 3.44 Alkylchlorobenzenes 2 0.00016

– 0.00018 4.66

– 5.15

A

- type Alkylphenols 11 0.000026

– 0.0035 1.51

– 5.33 Alkoxyphenols 2 0.000025

– 0.00079 1.59

– 3.50 Parabens (non

- benzoate) 1 0.00015 2 Salicylates (non

- Benzoate) 4 0.000062

– 0.0017 2.60

– 6.16

2

- Hydroxy Benzophenones 1 0.00097 3.44
Mixed Phenol

- Exact Match 2 0.00019

– 0.00079 1.91

– 2.94

B

- type

4

- Alkylaniline 3 0.00007

– 0.0015 1.62

– 4.08

4

- Alkoxyaniline 1 0.000064 2.63 Phthalates 1.6<LogK ow 

### <6.6 4 0.000066

– 0.00046 2.65

– 6.57 Phenones (Branched) 2 0.00007

– 0.00009 2.58

– 3.04 Alkylcyclohexanols 2 0.00024

– 0.00030 3.53

– 4.32

2

- ;4

- ; or 2,4,6

- Benzoates 2 0.00005

– 0.0001 2.87
Phenones cyclo

- substituted 1 0.00013 2.96 Cyclohexanones 1 0.00011 2.53 Mixed Organics

- Exact Match 11 0.000029

– 0.0026 2.05

– 5.02 O H C H 3 C H 3

C H 3 C H 3

C H 3
4DP LogKow = 7.27 CLogP
CAS# 27193

- 86

- 8 RBA = 0.012



## NVS hER
BLA Active
BG1 Active O H C H 3

PNP

- 5

LogKow = 5.99
CAS# 104

- 40

- 5 RBA = 0.016



## BG1 Active O H C H 3

PNP LogKow = 5.92 msrd

CAS# 84852

- 15

- 3 RBA = 0.046 

### ( branched )



## All 3 NVS ER
BLA Active
BG1 Active O H C H 3

C H 3

C H 3

PTAP LogKow = 3.83 msrd

CAS# 80

- 46

- 6 RBA = 0.0040 O H

C H 3 PNHpP

LogKow = 5.15 CLogP
CAS# 1987

- 50

- 4 RBA = 0.021



## BLA Active
BG1 Active BG1 Active O H

C H 3 C H 3 C H 3

C

H 3 C H 3

PTOP LogKow = 5.16 CLogP
CAS# 140

- 66

- 9 RBA = 0.0094 OPDTBP LogKow = 5.19 msrd

CAS# 96

- 76

- 4 RBA = 0.0027 C H 3 C H 3

C H 3

O H C H 3

C H 3 C H 3 O H

C H 3

PNOP LogKow = 5.68 CLogP
CAS# 1806

- 26

- 4 RBA = 0.0091



## All 3 NVS ER
BLA Active
BG1 Active BG1 Active HTP Inactive 

# Alkylphenols : TrSet Actives

Slide 213 of 320

# Assays At 2 Levels Along the AOP: Binding and TA

Looked at assays at two AOP levels as with TrSet assays (binding and TA):

- chemical was Inactive in all 5 HTP assays (3 Binding and 2 TA),

- chemical was Active in both a Binding and a TA HTP assay

- chemical was Active in either Binding or TA HTP assay, but not both.

HTP in vitro HTP in vitro HTP in vitro

INACTIVE: ACTIVE: ACTIVE:
TrSet assays all 5 assays 1+ Bind, AND, 1+ TA 1+ Bind, OR, 1+ TA

INACTIVE : 172 chemicals 134 9 29

ACTIVE : 124 chemicals 57 34 33

HTP Totals 191 43 62



# INACTIVES: 70% of the HTP INACTIVE calls are TrSet INACTIVES (134/191)
30% of the HTP INACTIVE calls are TrSET ACTIVES (57/191)

ACTIVES: 43 chemicals were ACTIVE in at least one binding AND one TA HTP assay. 80% of these HTP ACTIVES agree with TrSet assay ACTIVES (34/43);
9 HTP Bind + TA ACTIVES were TrSet INACTIVE 62 chemicals were ACTIVE in a binding OR a TA assay, but not both. 53% of these HTP ACTIVES agree with TrSet ACTIVES (33/62)

29 HTP ACTIVES were TrSet INACTIVE

Slide 214 of 320

# Preliminary Assessment

 The 5 HTP Assays

• Detect moderate to high affinity chemicals well

• Inconsistent detection of low affinity chemicals

 Discrepancies in activity; Factors to consider in interpretation

• Chemical concentration cut

- offs

- Can affect the ability of assays to detect low potency chemicals

• pH

• Metabolism

• Charge

• Replication

 Further analysis of chemicals with discordant responses will help to verify activity of chemicals and improve interpretation of HTP in vitro and TrSet
in vitro assay results

Slide 215 of 320

# 1) Determine ESv1 coverage of EDSP chemicals to prioritize for T1S (Sec 3)

2) Build ESv2 and determine coverage of EDSP chemicals to prioritize for T1S (Sec3)

3) Identify remaining chemicals with Unknown Binding Potential ( UnkBP ) i.e., those outside ESv2 model domain (Sec 3)

4) Determine where HTP data covers UnkBP chemicals (Sec 8)

5) Determine if and how HTP data could be used to expand TrSet to cover UnkBP chemicals. (Sec 4, 5, 6, 7, 8)



# Moving Incrementally:

5 Goals

ESv1

ESv2

ESv3

Slide 216 of 320

### Slide 217 of 320 

# Category

- based Approach to Strategic Testing to Cover Chemicals of Unknown Binding Potential

Dr. Pat Schmieder and Rick Kolanczyk Office of Research and Development National Health and Environmental Effects Research Laboratory
Mid

- Continent Ecology Division

# EDSP Universe of Chemicals n= 10,341

Chemical
Lists FIFRA Registration Review
Schedule for Active Ingredients (Approx.=1500) SDWA and INERTS (Approx.=9000)

Physico

Chemical Properties

(Approx n=5000) 

# Excluded

Exposure
Potential

SDWA 

# Lower Priority

ER Expert System

High through put
system 

# Prioritized List of Chemicals for EDSP Tier 1 Screening yes

No * Mixtures will be lower priority

no

Yes 

# Considerations of Read

Across and Chemical Categories

Slide 218 of 320

# 5 Goals

1) Determine ESv1 coverage of EDSP chemicals to prioritize for T1S (Sec 3)

2) Build ESv2 and determine coverage of EDSP chemicals to prioritize for T1S (Sec3)

3) Identify remaining chemicals with Unknown Binding Potential ( UnkBP ) i.e., those outside ESv2 model domain (Sec 3)

4) Determine where HTP data covers UnkBP chemicals (Sec 8)

5) Determine if and how HTP data could be used to expand TrSet to

cover UnkBP chemicals. (Sec 4, 5, 6, 7, 8 ) ESv1

ESv2

ESv3 

# Building from Initial Steps to Address New Challenges Moving Incrementally

Slide 219 of 320

# a) Assess Distribution of UnkBP Chemicals by ESv2 Decision Tree Categories

- Determine number of UnkBP chemicals within a chemical group

- Determine number of chemicals with HTP data

- Type of HTP data available

- ToxCast

– 8 assays (3 Binding; 5 TA) represent 2 levels of AOP

- Tox21

– 2 assays (2 TA) represent 1 level of AOP 

# Determining Where HTP Data Covers UnkBP Chemicals

b) Assess where HTP is across untested LogKow ranges within Chemical Categories & Chemical Groups

- Select chemicals for testing to cover the LogKow range

Part 1: Within defined ESv2 Groups

Part 2: Within the mixed functional group classes Mixed Phenols and Mixed Organics

Slide 220 of 320

# a) Assess Distribution of UnkBP Chemicals by ESv2 Decision Tree Categories 

# Determining Where HTP Data Covers UnkBP Chemicals

Slide 221 of 320

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories

Slide 222 of 320 ESv 2 Chemical Category # grp chems 

### % of 1704

I

. Acyclic_Perfluoro
Acyclic Perfluoro (Unknown Binding Potential) 16 0.9



### III

. Belongs to a known Inactive class

**III. Known Inactives Subtotal=** 66 3.9



### V

. Special Rule applies
**V. Special Rules Subtotal=** 88 5.2



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2



### Unk **Binding Potential Total=** 1704

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories Largest Number in ‘VII. Site B

- type Potential Binders’

Of the 1704 UnkBP chemicals, there are 1400 (82%) that are potential Site B

- type binders;

Slide 223 of 320 ESv 2 Chemical Category # grp chems 

### % of 1704

I

. Acyclic_Perfluoro
Acyclic Perfluoro (Unknown Binding Potential) 16 0.9



### III

. Belongs to a known Inactive class

**III. Known Inactives Subtotal=** 66 3.9



### V

. Special Rule applies
**V. Special Rules Subtotal=** 88 5.2



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2



### Unk **Binding Potential Total=** 1704

# HTP Data Available For 1400 Site B

- type Binders

HTP data is available for 611 (44%) of the Site B

- type Binders across all groups

Slide 224 of 320 All HTP All HTP TC&T21 8 assays T21 only 2 assays no HTP no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp
chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# HTP data is available for 611 (44%) of the Site B

- type Binders across all groups

- 182 (30%) have ToxCast + Tox21 data (8 assays: 3 Binding & 5 TA)

Slide 225 of 320 

# HTP Data Available For 1400 Site B

- type Binders

All HTP All HTP TC&T21 8 assays T21 only 2 assays no HTP no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp
chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# HTP data is available for 611 (44%) of the Site B

- type Binders across all groups

- 182 (30%) have ToxCast + Tox21 data (8 assays: 3 Binding & 5 TA)

- 429 (70%) have Tox21 (NCGC assay data; 2 TA assays (BLA and BG1))

Slide 226 of 320 

# HTP Data Available For 1400 Site B

- type Binders

All HTP All HTP TC&T21 8 assays T21 only 2 assays no HTP no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp
chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# HTP data is available for 611 (44%) of the Site B

- type Binders across all groups

- 182 (30%) have ToxCast + Tox21 data (8 assays: 3 Binding & 5 TA)

- 429 (70%) have Tox21 (NCGC assay data; 2 TA assays (BLA and BG1))

- 789 Site B chemicals (56%) have no HTP data available

Slide 227 of 320



# HTP Data Available For 1400 Site B

- type Binders

All HTP All HTP TC&T21 8 assays T21 only 2 assays no HTP no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp
chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# Mixed Organics are Majority (98%) of Site B UnkBP

1368 chemicals and 80% of 1704 UnkBP

Slide 228 of 320 ESv 2 Chemical Category and Groups # grp chems 

### % of
1704

VII

. Site "B" : Contains "Specified" fragment

Mixed Organics

- UnkBP 1368 80.3

2

- Alkylanilines 7 0.4

Mixed Acetanilides (LogKow> 1

. 3 ) 

### 7 0.4

Phenones cyclo

- substituted

- UnkBP 6 0.4

Multi subst

. Alkylanilines 5 0.3 Alkylcyclohexanols [LogKow> 4

. 4

, or > 2

. 6 & < 3

. 5 ] 

### 4 0.2

3

- Alkylanilines 2 0.1

2

- ; 4

- ; or 2

, 4

, 6

- Benzoates UnkBP 1 0.1

**VII. Site "B" Subtotal=** 1400 82.2

# HTP Data For Mixed Organics With UnkBP

1368 Mixed Organics 589 (43%) have HTP data

Slide 229 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category and Groups # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

Mixed Organics

- UnkBP 1368 80.3 43 

### 589 175 414 57 

### 779

2

- Alkylanilines 7 0.4 86 

### 6 4 2 14 

### 1

Mixed Acetanilides (LogKow> 1

. 3 ) 7 0.4 29 

### 2 0 2 71 

### 5

Phenones cyclo

- substituted

- UnkBP 6 0.4 67 

### 4 0 4 33 

### 2

Multi subst

. Alkylanilines 5 0.3 100 

### 5 1 4 0 

### 0
Alkylcyclohexanols [LogKow> 4

. 4

, or > 2

. 6 & < 3

. 5 ] 4 0.2 50 

### 2 1 1 50 

### 2

3

- Alkylanilines 2 0.1 100 

### 2 1 1 0 

### 0

2

- ; 4

- ; or 2

, 4

, 6

- Benzoates UnkBP 1 0.1 100 

### 1 0 1 0 

### 0

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# 1368 Mixed Organics 589 (43%) have HTP data

- 175 chemicals (30%) have ToxCast and Tox21 data (8 assays: 3 Bind & 5TA)

Slide 230 of 320 

# HTP Data For Mixed Organics With UnkBP

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category and Groups # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

Mixed Organics

- UnkBP 1368 80.3 43 

### 589 175 414 57 

### 779

2

- Alkylanilines 7 0.4 86 

### 6 4 2 14 

### 1

Mixed Acetanilides (LogKow> 1

. 3 ) 7 0.4 29 

### 2 0 2 71 

### 5

Phenones cyclo

- substituted

- UnkBP 6 0.4 67 

### 4 0 4 33 

### 2

Multi subst

. Alkylanilines 5 0.3 100 

### 5 1 4 0 

### 0
Alkylcyclohexanols [LogKow> 4

. 4

, or > 2

. 6 & < 3

. 5 ] 4 0.2 50 

### 2 1 1 50 

### 2

3

- Alkylanilines 2 0.1 100 

### 2 1 1 0 

### 0

2

- ; 4

- ; or 2

, 4

, 6

- Benzoates UnkBP 1 0.1 100 

### 1 0 1 0 

### 0

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# 1368 Mixed Organics 589 (43%) have HTP data

- 175 chemicals (30%) have ToxCast and Tox21 data (8 assays: 3 Bind & 5TA)

- 414 chemicals (70%) have Tox21 data, 2 TA assays (BLA and BG1)

Slide 231 of 320 

# HTP Data For Mixed Organics With UnkBP

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category and Groups # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

Mixed Organics

- UnkBP 1368 80.3 43 

### 589 175 414 57 

### 779

2

- Alkylanilines 7 0.4 86 

### 6 4 2 14 

### 1

Mixed Acetanilides (LogKow> 1

. 3 ) 7 0.4 29 

### 2 0 2 71 

### 5

Phenones cyclo

- substituted

- UnkBP 6 0.4 67 

### 4 0 4 33 

### 2

Multi subst

. Alkylanilines 5 0.3 100 

### 5 1 4 0 

### 0
Alkylcyclohexanols [LogKow> 4

. 4

, or > 2

. 6 & < 3

. 5 ] 4 0.2 50 

### 2 1 1 50 

### 2

3

- Alkylanilines 2 0.1 100 

### 2 1 1 0 

### 0

2

- ; 4

- ; or 2

, 4

, 6

- Benzoates UnkBP 1 0.1 100 

### 1 0 1 0 

### 0

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# 1368 Mixed Organics 589 (43%) have HTP data

- 175 chemicals (30%) have ToxCast and Tox21 data (8 assays: 3 Bind & 5TA)

- 414 chemicals (70%) have Tox21 data, 2 TA assays (BLA and BG1) 779 (57%) have no HTP data available

Slide 232 of 320 

# HTP Data For Mixed Organics With UnkBP

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category and Groups # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VII

. Site "B" : Contains "Specified" fragment

Mixed Organics

- UnkBP 1368 80.3 43 

### 589 175 414 57 

### 779

2

- Alkylanilines 7 0.4 86 

### 6 4 2 14 

### 1

Mixed Acetanilides (LogKow> 1

. 3 ) 7 0.4 29 

### 2 0 2 71 

### 5

Phenones cyclo

- substituted

- UnkBP 6 0.4 67 

### 4 0 4 33 

### 2

Multi subst

. Alkylanilines 5 0.3 100 

### 5 1 4 0 

### 0
Alkylcyclohexanols [LogKow> 4

. 4

, or > 2

. 6 & < 3

. 5 ] 4 0.2 50 

### 2 1 1 50 

### 2

3

- Alkylanilines 2 0.1 100 

### 2 1 1 0 

### 0

2

- ; 4

- ; or 2

, 4

, 6

- Benzoates UnkBP 1 0.1 100 

### 1 0 1 0 

### 0

**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789

# Distribution Of UnkBP Chemicals By ESv2 Decision Tree Categories

2 nd 

# Largest Number are ‘VI. Site A

- type Potential Binders’

Slide 233 of 320 ESv 2 Chemical Category # grp chems 

### % of 1704

I

. Acyclic_Perfluoro
Acyclic Perfluoro (Unknown Binding Potential) 16 0.9



### III

. Belongs to a known Inactive class

**III. Known Inactives Subtotal=** 66 3.9



### V

. Special Rule applies
**V. Special Rules Subtotal=** 88 5.2



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2



### Unk **Binding Potential Total=** 1704

# 134 (8%) that are potential ‘Site A

- type’ binders 

# 2 nd 

# Largest Number are ‘VI. Site A

- type Potential Binders’

Slide 234 of 320 

# Distribution Of UnkBP Chemicals By ESv2 Decision Tree Categories

ESv 2 Chemical Category # grp chems 

### % of 1704

I

. Acyclic_Perfluoro
Acyclic Perfluoro (Unknown Binding Potential) 16 0.9



### III

. Belongs to a known Inactive class

**III. Known Inactives Subtotal=** 66 3.9



### V

. Special Rule applies
**V. Special Rules Subtotal=** 88 5.2



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9



### VII

. Site "B" : Contains "Specified" fragment

**VII. Site "B" Subtotal=** 1400 82.2



### Unk **Binding Potential Total=** 1704

# HTP Data Available For ‘Site A

- type’ Potential Binders

- 56 chemicals (42%) of 134 ‘Site A

- type’ UnkBP have HTP data

Slide 235 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# - 56 chemicals (42%) of 134 ‘Site A

- type’ UnkBP have HTP

- 20 (36%) have ToxCast + Tox21 data (8 assays: 3 Binding & 5 TA)

Slide 236 of 320 

# HTP Data Available For ‘Site A

- type’ Potential Binders

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# - 56 chemicals (42%) of 134 ‘Site A

- type’ UnkBP have HTP

- 20 (36%) have ToxCast + Tox21 data (8 assays: 3 Binding & 5 TA)

- 36 (64%) have Tox21 (NCGC assay data; 2 TA assays (BLA and BG1))

Slide 237 of 320 

# HTP Data Available For ‘Site A

- type’ Potential Binders

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# - 56 chemicals (42%) of 134 ‘Site A

- type’ UnkBP have HTP

- 20 (36%) have ToxCast + Tox21 data (8 assays: 3 Binding & 5 TA)

- 36 (64%) have Tox21 (NCGC assay data; 2 TA assays (BLA and BG1))

- 78 chemicals (58%) have no HTP

Slide 238 of 320 

# HTP Data Available For ‘Site A

- type’ Potential Binders

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# 133 Mixed Phenols 

# Mixed Phenols Are Majority of Site A UnkBP

Slide 239 of 320 ESv 2 Chemical Category # grp chems % of
1704



### VI

. Site "A" : Contains a Phenol fragment

Mixed Phenol

- UnkBP 133 7.8


### Alkoxyphenols [LogKow > 4

. 1 ] 1 0.1



### VI. Site "A" Subtotal= 134 7.9

# 133 Mixed Phenols 55 (41%) Mixed Phenols have HTP data 

# HTP Data For Mixed Phenols

Slide 240 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

Mixed Phenol

- UnkBP 133 7.8 41 

### 55 19 36 59 

### 78

Alkoxyphenols [LogKow > 4

. 1 ] 1 0.1 100 

### 1 1 0 0 

### 0

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# 133 Mixed Phenols 55 (41%) Mixed Phenols have HTP data

- 19 chemicals (35%) have ToxCast and Tox21 data (8 assays: 3 Bind & 5TA)

Slide 241 of 320 

# HTP Data For Mixed Phenols

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

Mixed Phenol

- UnkBP 133 7.8 41 

### 55 19 36 59 

### 78

Alkoxyphenols [LogKow > 4

. 1 ] 1 0.1 100 

### 1 1 0 0 

### 0

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# 133 Mixed Phenols 55 (41%) Mixed Phenols have HTP data

- 19 chemicals (35%) have ToxCast and Tox21 data (8 assays: 3 Bind & 5TA)

- 36 chemicals (65%) have Tox21 data, 2 TA assays (BLA and BG1)

Slide 242 of 320 

# HTP Data For Mixed Phenols

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

Mixed Phenol

- UnkBP 133 7.8 41 

### 55 19 36 59 

### 78

Alkoxyphenols [LogKow > 4

. 1 ] 1 0.1 100 

### 1 1 0 0 

### 0

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# 133 Mixed Phenols 55 (41%) Mixed Phenols have HTP data

- 19 chemicals (35%) have ToxCast and Tox21 data (8 assays: 3 Bind & 5TA)

- 36 chemicals (65%) have Tox21 data, 2 TA assays (BLA and BG1) 78 (59%) have no HTP data available

Slide 243 of 320 

# HTP Data For Mixed Phenols

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems



### VI

. Site "A" : Contains a Phenol fragment

Mixed Phenol

- UnkBP 133 7.8 41 

### 55 19 36 59 

### 78

Alkoxyphenols [LogKow > 4

. 1 ] 1 0.1 100 

### 1 1 0 0 

### 0

**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

# - 88 chemicals in the Category 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories
3rd Largest Number in ‘V. Special Rules apply’

Slide 244 of 320 ESv 2 Chemical Category # grp chems % of 1704


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9



### III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9


### V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2


### VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9



### VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 

### Unk **Binding Potential Total=** 1704

# - 88 chemicals in the Category

- Higher % with HTP data (66% and 58 chemicals) 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories
3rd Largest Number in ‘V. Special Rules apply’

Slide 245 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960

# - 88 chemicals in the Category

- Higher % with HTP data (66% and 58 chemicals)

- 24 chemicals (41%) 8 assays 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories
3rd Largest Number in ‘V. Special Rules apply’

Slide 246 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960

# - 88 chemicals in the Category

- Higher % with HTP data (66% and 58 chemicals)

- 24 chemicals (41%) 8 assays

- 34 chemicals (59%) 2 assays 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories
3rd Largest Number in ‘V. Special Rules apply’

Slide 247 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960

# - 88 chemicals in the Category

- Higher % with HTP data (66% and 58 chemicals)

- 24 chemicals (41%) 8 assays

- 34 chemicals (59%) 2 assays

- 30 chemicals (34%) no HTP 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories
3rd Largest Number in ‘V. Special Rules apply’

Slide 248 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78

VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960

### HTP TC&T21
8 assays T21 only 2 assays no HTP no HTP



## Expert System Chemical Group #group chems % of
1704 % of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


## V

. Special Rule applies

Multi

- Cyclic Hydrocarbons UnkBP 

## 67 3.9 69 

## 21 25 31 

## 21

Thiophosphate Esters UnkBP 

## 14 0.8 71 

## 3 7 29 

## 4

Alkylbromobenzene 

## 7 0.4 29 

## 0 2 71 

## 5
**V. Special Rules Subtotal=** 88 5.2 66 

## 24 34 34 

## 30 

# Multi

- Cyclic Hydrocarbons Are Majority of Category ‘V’ UnkBP

Well covered with HTP data (69%)

Slide 249 of 320

# Well covered with HTP data (69%)



# ...also Thiophosphate Esters in Category ‘V’ with UnkBP

10 of the 14 have HTP data

HTP TC&T21
8 assays T21 only 2 assays no HTP no HTP



## Expert System Chemical Group #group chems % of
1704 % of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


## V

. Special Rule applies

Multi

- Cyclic Hydrocarbons UnkBP 

## 67 3.9 69 

## 21 25 31 

## 21

Thiophosphate Esters UnkBP 

## 14 0.8 71 

## 3 7 29 

## 4

Alkylbromobenzene 

## 7 0.4 29 

## 0 2 71 

## 5
**V. Special Rules Subtotal=** 88 5.2 66 

## 24 34 34 

## 30

Slide 250 of 320 

# Multi

- Cyclic Hydrocarbons Are Majority of Category ‘V’ UnkBP

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories

Remaining Categories contain 4% and 1% of the remaining UnkBP chemicals....

Slide 251 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives**  **Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48

# ....and the UnkBP chemicals are spread across well studied groups, but UnkBPs are outside of the LogKow range of in vitro TrSet data

Slide 252 of 320 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category and Groups # grp chems % of 1704 % of grp chems # of grp
chems # of grp chems # of grp chems % of grp chems # of grp chems



### III

. Belongs to a known Inactive class

Alcohols [LogKow> 3

. 4 ] 27 1.6 11 

### 3 2 1 89 

### 24

Mono

- cyclic Hydrocarbons [ LogKow < 2

. 5

, > 6

. 4 ] 13 0.8 31 

### 4 2 2 69 

### 9

Triazines [ LogKow > 4

. 1 ] 9 0.5 22 

### 2 1 1 78 

### 7

Benzoates (non

- ring Subst ) [ LogKow < 3

. 0 ,> 4

. 3 ] 6 0.4 67 

### 4 1 3 33 

### 2

Sorbitans [LogKow< 3

. 1 ,> 5

. 9 ] 4 0.2 25 

### 1 0 1 75 

### 3

Imidazolidines [LogKow> 0 ] 3 0.2 67 

### 2 2 0 33 

### 1

Benzamides [LogKow< 2

. 1 ,> 2

. 8 ] 1 0.1 0 

### 0 0 0 100 

### 1

Bis

- Anilines [LogKow< 2

. 1 ,> 6

. 4 ] 1 0.1 0 

### 0 0 0 100 

### 1

Phenones (n

- alkyl) [LogKow> 4

. 2 ] 1 0.1 100 

### 1 0 1 0 

### 0
Pyrrolidiones [LogKow> 3

. 4 ] 1 0.1 100 

### 1 1 0 0 

### 0

**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48

# ....finally, several Acyclic perfluoro UnkBP chemicals that are not covered by TrSet in vitro
also have little HTP in vitro data

Slide 253 of 320 

# Distribution of UnkBP Chemicals By ESv2 Decision Tree Categories

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

# In summary, 44% HTP coverage overall, varying between 66% and 1% depending on category, but larger groups have 44%, 42%, and 66% HTP

Slide 254 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78
VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960

### Slide 255 of 320 

# - 509 chems , or ~70% of the HTP data is for 2 TA assays

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78
VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960 

# In summary, 44% HTP coverage overall, varying between 66% and 1% depending on category, but larger groups have 44%, 42%, and 66% HTP

### Slide 256 of 320 

# - 509 chems , or ~70% of the HTP data is for 2 TA assays

- 235 chems (30%) of UnkBP chemicals have HTP from 8 assays

All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives**  **Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78
VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960 

# In summary, 44% HTP coverage overall, varying between 66% and 1% depending on category, but larger groups have 44%, 42%, and 66% HTP

# - 509 chems , or ~70% of the HTP data is for 2 TA assays

- 235 chems (30%) of UnkBP chemicals have HTP from 8 assays 

# Leaving 960 chemicals (56%) UnkBP chemicals not covered by in vitro TrSet or HTP

Slide 257 of 320 All HTP TC&T21 8 assays T21 only 2 assays no HTP

ESv 2 Chemical Category # grp chems % of
1704 % of grp chems # of grp chems # of grp chems # of grp chems % of grp chems # of grp chems


### I

. Acyclic_Perfluoro Acyclic Perfluoro (Unknown Binding Potential) 16 0.9 6 

### 1 0 1 94 

### 15

III

. Belongs to a known Inactive class
**III. Known Inactives Subtotal=** 66 3.9 27 

### 18 9 9 73 

### 48
V

. Special Rule applies **V. Special Rules Subtotal=** 88 5.2 66 

### 58 24 34 34 

### 30
VI

. Site "A" : Contains a Phenol fragment
**VI. Site "A" Subtotal=** 134 7.9 42 

### 56 20 36 58 

### 78
VII

. Site "B" : Contains "Specified" fragment
**VII. Site "B" Subtotal=** 1400 82.2 44 

### 611 182 429 56 

### 789
**Unk Binding Potential Total=**  1704 44 

### 744 235 509 56 

### 960 

# In summary, 44% HTP coverage overall, varying between 66% and 1% depending on category, but larger groups have 44%, 42%, and 66% HTP

# a) Assess Distribution of UnkBP Chemicals by ESv2 Decision Tree Categories

- Determine number of UnkBP chemicals within a chemical group

- Determine number of chemicals with HTP data

- Type of HTP data available

- ToxCast

– 8 assays (3 Binding; 5 TA) represent 2 levels of AOP

- Tox21

– 2 assays (2 TA) represent 1 level of AOP 

# Determining Where HTP Data Covers UnkBP Chemicals

b) Assess where HTP is across untested LogKow ranges within Chemical Categories & Chemical Groups

- Select chemicals for testing to cover the LogKow range

Part 1: Within defined ESv2 Groups

Part 2: Within the mixed functional group classes Mixed Phenols and Mixed Organics

Slide 258 of 320

# Part 1: Unk BP Chemicals In Defined ESv2 Groups
Outside Tested LogK
ow 

# Range

Benzoates (non

- ring Subst )[ LogKow <3.0,>4.3] Log Kow Methyl_benzoate 1.83 benzoic_acid,_ethyl_ester 2.32 Propan

- 2

- yl_benzoate 2.74 Cinnamyl_benzoate 4.30 Linalyl_benzoate 5.84 Geranyl_benzoate 5.93

Slide 259 of 320 LogKow Range LogKow Range 

### III. Belongs to a known Inactive class # chem % of 1704 Low High



### Alcohols [LogKow> 3

. 4 ] 27 1.6 27

Mono

- cyclic Hydrocarbons [ LogKow <2.5,>6.4] 13 0.8 3 10
Triazines [ LogKow >4.1] 9 0.5 9
Benzoates (non

- ring Subst)[LogKow<3.0,>4.3] 6 0.4 3 3
Sorbitans [LogKow<3.1,>5.9] 4 0.2 4

Imidazolidines [LogKow>0] 3 0.2 1 > cutoff
Benzamides [LogKow<2.1,>2.8] 1 0.1 1

Bis

- Anilines [LogKow<2.1,>6.4] 1 0.1 1
Phenones (n

- alkyl)[LogKow>4.2] 1 0.1 1
Pyrrolidiones [LogKow>3.4] 1 0.1 1

## ESv2 Group Chemical Name LogKow


## VII. Site "B":Contains "Specified" fragment

2

- Alkylanilines

2

- Methylaniline 1.62

2

- Ethylaniline 2.11 2,6

- Dimethylaniline 2.17

2

- isopropylaniline 2.53

2

- Ethyl

- 6

- methylaniline 2.66 2,6

- Diethylaniline 3.15 2,6

- Diisopropylaniline 3.99 

# Part 1: UnkBP Chemicals In Defined ESv2 Groups

....or potential new group

Slide 260 of 3201E

- 06 1E

- 05 0.0001

0.001

0.01

0.1

1 2 3 4 5 6 7 8RBA

Log Kow 

# Training Set for: Aniline (RBA<0.00001%), and 4,n

- alkylanilines

1.3< LogKow <5.1

LogKow = 3.05 m N H 2 C H 3

LogKow = 1.96 m N H 2 C H 3

LogKow = 2.40 m C H 3 N H 2 C H 3 N H 2

LogKow = 1.39 m

LogKow = 5.12 est C H 3 N H 2

LogKow =3.39 m Log Kow = 4.06 est N H 2

C H 3 N H 2

C H 3 N H 2

LogKow = 0.90 m

LogKow = 2.70 m C H 3

C H 3

C H 3 N H 2 

# Training Set for related group: 4,t

- alkylanilines:

Slide 261 of 320

# Do ortho substituted alkylanilines behave like para subst ?

Do 2,6

- substituted alkylanilines behave like 2

- alkyl subst ?

Slide 262 of 320



# 2

- Alkylanilines Compared to 4

- Alklyanilines

Combine 2

- alkyl subst with 4

- alkyl subst

....or new group

## ESv2 Group Chemical Name LogKow


## VII. Site "B":Contains "Specified" fragment

2

- Alkylanilines

2

- Methylaniline 1.62

2

- Ethylaniline 2.11 2,6

- Dimethylaniline 2.17

2

- isopropylaniline 2.53

2

- Ethyl

- 6

- methylaniline 2.66 2,6

- Diethylaniline 3.15 2,6

- Diisopropylaniline 3.99

Slide 263 of 320 

# Part 1: In Defined ESv2 Groups ....or potential new groups

## ESv2 Group Chemical Name LogKow


## VII. Site "B":Contains "Specified" fragment

2

- Alkylanilines

2

- Methylaniline 1.62

2

- Ethylaniline 2.11 2,6

- Dimethylaniline 2.17

2

- isopropylaniline 2.53

2

- Ethyl

- 6

- methylaniline 2.66 2,6

- Diethylaniline 3.15 2,6

- Diisopropylaniline 3.99

Slide 264 of 320 

# Part 1: In Defined ESv2 Groups ....or potential new groups

## ESv2 Group Chemical Name LogKow


## VII. Site "B":Contains "Specified" fragment

2

- Alkylanilines

2

- Methylaniline 1.62

2

- Ethylaniline 2.11 2,6

- Dimethylaniline 2.17

2

- isopropylaniline 2.53

2

- Ethyl

- 6

- methylaniline 2.66 2,6

- Diethylaniline 3.15 2,6

- Diisopropylaniline 3.99

2

- Methylaniline 1.62

2

- Ethylaniline 2.11

2

- isopropylaniline 2.53

2,6

- Dimethylaniline 2.17

2

- Ethyl

- 6

- methylaniline 2.66 2,6

- Diethylaniline 3.15 2,6

- Diisopropylaniline 3.99

Slide 265 of 320 

# Part 1: In Defined ESv2 Groups ....or potential new groupsESv2 Group Chemical Name LogKow TC &T21 T21 

## VII. Site "B":Contains "Specified" fragment

2

- Alkylanilines

2

- Methylaniline 1.62 1 1

2

- Ethylaniline 2.11 0 1

2,6

- Dimethylaniline 2.17 1 1

2

- isopropylaniline 2.53 0 0

2

- Ethyl

- 6

- methylaniline 2.66 1 1

2,6

- Diethylaniline 3.15 1 1

2,6

- Diisopropylaniline 3.99 0 1

2

- Methylaniline 1.62 1 1

2

- Ethylaniline 2.11 0 1

2

- isopropylaniline 2.53 0 0

2,6

- Dimethylaniline 2.17 1 1

2

- Ethyl

- 6

- methylaniline 2.66 1 1

2,6

- Diethylaniline 3.15 1 1

2,6

- Diisopropylaniline 3.99 0 1

Slide 266 of 320 

# HTP in vitro Coverage

.... potential new groupsHTP All HTP **Testing needed**  **or** recomme nd

Total Class Total Class 8 assays LogP
range 8 assays

or 2 assays LogP range HTP
coverag

e LogP
range #chems

ESv 2 Chemical Class # chem LogP
range #chems covered #chems covered Adequat e? to test to test

V

. Special Rule applies

Multi Cyclic Hydrocarbons UnkBP 67 3.16

- 17.62 21 3.16

- 6.70 25 3.16

- 17.62 T 21 covered

-- -- 

# Redefining a Large Chemical Group

Example: Multi

- Cyclic Hydrocarbons

- 67 chemicals in the groups with UnkBP

Slide 267 of 320C H 2 

# Multicyclic Hydrocarbons

Rainbow Trout Training Set

LogKow = 4.30 CLogP
CAS# 530

- 48

- 3 LogKow = 4.81 msrd

CAS# 645

- 49

- 8

LogKow = 5.65 CLogP
CAS# 519

- 73

- 3 LogKow = 5.87 CLogP
CAS# 58

- 72

- 0 LogKow = 4.18 msrd

CAS# 86

- 73

- 7 LogKow = 4.25 msrd

CAS# 613

- 31

- 0 LogKow = 4.81 msrd

CAS# 103

- 30

- 0 LogKow = 4.83 msrd

CAS# 80

- 56

- 8

LogKow = 7.31 CLogP
CAS# 632

- 51

- 9



# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009)

C H 3 C H 3

C

H 3

LogKow = 4.83 msrd

CAS# 80

- 56

- 8 LogKow = 2.32 msrd

CAS# 79

- 92

- 5 LogKow = 4.70 CLogP
CAS# 18172

- 67

- 3 LogKow = 3.30 msrd

CAS# 124

- 76

- 5 LogKow = 3.87 msrd

CAS# 1321

- 94

- 4 C H 3 C H 3 C H 3

C H 3 C H 3 C H 3 C H 3

C

H 3

LogKow = 3.30 msrd

CAS# 91

- 20

- 3

LogKow = 3.30 msrd

CAS# 91

- 20

- 3 LogKow = 7.68 CLogP
CAS# 1625

- 91

- 8 C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 2

C H 2 C H 3 C H 3

LogKow = 4.31 msrd

CAS# 28804

- 88

- 8

C H 3

C H 3

LogKow = 6.88 CLogP
CAS# 69009

- 90

- 1 C H 3 C H 3 C H 3

C H 3



### Slide 268 of 320C H 2



# Rainbow Trout Training Set

LogKow = 4.30 CLogP
CAS# 530

- 48

- 3 LogKow = 4.81 msrd

CAS# 645

- 49

- 8

LogKow = 5.65 CLogP
CAS# 519

- 73

- 3 LogKow = 5.87 CLogP
CAS# 58

- 72

- 0 LogKow = 4.18 msrd

CAS# 86

- 73

- 7 LogKow = 4.25 msrd

CAS# 613

- 31

- 0 LogKow = 4.81 msrd

CAS# 103

- 30

- 0 LogKow = 4.83 msrd

CAS# 80

- 56

- 8

LogKow = 7.31 CLogP
CAS# 632

- 51

- 9



# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009)

C H 3 C H 3

C

H 3

LogKow = 4.83 msrd

CAS# 80

- 56

- 8 LogKow = 2.32 msrd

CAS# 79

- 92

- 5 LogKow = 4.70 CLogP
CAS# 18172

- 67

- 3 LogKow = 3.30 msrd

CAS# 124

- 76

- 5 LogKow = 3.87 msrd

CAS# 1321

- 94

- 4 C H 3 C H 3 C H 3

C H 3 C H 3 C H 3 C H 3

C

H 3

LogKow = 3.30 msrd

CAS# 91

- 20

- 3

LogKow = 3.30 msrd

CAS# 91

- 20

- 3 LogKow = 7.68 CLogP
CAS# 1625

- 91

- 8 C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 2

C H 2 C H 3 C H 3

LogKow = 4.31 msrd

CAS# 28804

- 88

- 8

C H 3

C H 3

LogKow = 6.88 CLogP
CAS# 69009

- 90

- 1 C H 3 C H 3 C H 3

C H 3



### Slide 269 of 320 

# Multicyclic HydrocarbonsC H 2



# Rainbow Trout Training Set

DPE LogKow = 4.30 CLogP
CAS# 530

- 48

- 3 CSB LogKow = 4.81 msrd

CAS# 645

- 49

- 8 TPM LogKow = 5.65 CLogP
CAS# 519

- 73

- 3 3PE LogKow = 5.87 CLogP
CAS# 58

- 72

- 0

FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7 DAC LogKow = 4.25 msrd

CAS# 613

- 31

- 0 TSB LogKow = 4.81 msrd

CAS# 103

- 30

- 0

AP LogKow = 4.83 msrd

CAS# 80

- 56

- 8 4PE LogKow = 7.31 CLogP
CAS# 632

- 51

- 9



# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009)

C H 3 C H 3

C

H 3

AP LogKow = 4.83 msrd

CAS# 80

- 56

- 8 LogKow = 2.32 msrd

CAS# 79

- 92

- 5 LogKow = 4.70 CLogP
CAS# 18172

- 67

- 3 LogKow = 3.30 msrd

CAS# 124

- 76

- 5

LogKow = 3.87 msrd

CAS# 1321

- 94

- 4 C H 3 C H 3 C H 3

C H 3 C H 3 C H 3 C H 3

C

H 3

NAFT LogKow = 3.30 msrd

CAS# 91

- 20

- 3

NAFT LogKow = 3.30 msrd

CAS# 91

- 20

- 3 DtBB LogKow = 7.68 CLogP
CAS# 1625

- 91

- 8 C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 2

C H 2 C H 3 C H 3

LogKow = 4.31 msrd

CAS# 28804

- 88

- 8 C H 3

C H 3

LogKow = 6.88 CLogP
CAS# 69009

- 90

- 1 C H 3 C H 3 C H 3

C H 3



### Slide 270 of 320 

# Multicyclic HydrocarbonsC H 2



# Rainbow Trout Training Set

DPE LogKow = 4.30 CLogP
CAS# 530

- 48

- 3
RBA = 0.0045 CSB LogKow = 4.81 msrd

CAS# 645

- 49

- 8
RBA = 0.0052 TPM LogKow = 5.65 CLogP
CAS# 519

- 73

- 3
RBA = 0.0043 3PE LogKow = 5.87 CLogP
CAS# 58

- 72

- 0
RBA = 3.0

FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7

RBA = NB DAC LogKow = 4.25 msrd

CAS# 613

- 31

- 0

RBA = NB TSB LogKow = 4.81 msrd

CAS# 103

- 30

- 0

RBA = NB

AP LogKow = 4.83 msrd

CAS# 80

- 56

- 8

RBA = NB 4PE LogKow = 7.31 CLogP
CAS# 632

- 51

- 9

RBA = NB



# Inventory

– Antimicrobials; Food Use Inerts; Non

- Food Use Inerts (2009)

C H 3 C H 3

C

H 3 AP LogKow = 4.83 msrd

CAS# 80

- 56

- 8

RBA = NB LogKow = 2.32 msrd

CAS# 79

- 92

- 5 LogKow = 4.70 CLogP
CAS# 18172

- 67

- 3 LogKow = 3.30 msrd

CAS# 124

- 76

- 5

LogKow = 3.87 msrd

CAS# 1321

- 94

- 4 C H 3 C H 3 C H 3

C H 3 C H 3 C H 3 C H 3

C

H 3

NAFT LogKow = 3.30 msrd

CAS# 91

- 20

- 3

RBA = NB

NAFT LogKow = 3.30 msrd

CAS# 91

- 20

- 3

RBA = NB DtBB LogKow = 7.68 CLogP
CAS# 1625

- 91

- 8

RBA = NB C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

C H 2

C H 2 C H 3 C H 3

LogKow = 4.31 msrd

CAS# 28804

- 88

- 8 C H 3

C H 3

LogKow = 6.88 CLogP
CAS# 69009

- 90

- 1 C H 3 C H 3 C H 3

C H 3



### Slide 271 of 320 

# Multicyclic HydrocarbonsCAS # 208

- 96

- 8 CAS # 581

- 42

- 0 C H 3

C H 3

CAS # 83

- 32

- 9

CAS # 53

- 70

- 3 CAS # 120

- 12

- 7 CAS # 56

- 55

- 3 CAS # 218

- 01

- 9 FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7

RBA = NB

CAS # 206

- 44

- 0 CAS # 85

- 01

- 8 CAS # 57

- 97

- 6 C H 3

C H 3

CAS # 129

- 00

- 0

CAS # 198

- 55

- 0

CAS # 92

- 06

- 8 CAS # 92

- 94

- 4 CAS # 103

- 29

- 7 CAS # 84

- 15

- 1 CAS # 61788

- 32

- 7 CAS # 56

- 49

- 5

C H 3

CAS # 207

- 08

- 9 CAS # 205

- 99

- 2 CAS # 193

- 39

- 5 CAS # 191

- 24

- 2 

# Inventory

– EDSP (2012)

“Fused Rings”

“Bridged Rings” ??????

Slide 272 of 320 

# Multicyclic Hydrocarbons

CAS # 119

- 64

- 2 CAS # 496

- 11

- 7 CAS # 3048

- 65

- 5 CAS # 91

- 17

- 8

CAS # 92

- 52

- 4 CAS # 101

- 81

- 5CAS # 119

- 64

- 2

CAS # 496

- 11

- 7 CAS # 3048

- 65

- 5 CAS # 91

- 17

- 8 CAS # 208

- 96

- 8 CAS # 581

- 42

- 0 C H 3

C H 3

CAS # 83

- 32

- 9

CAS # 53

- 70

- 3 CAS # 120

- 12

- 7 CAS # 56

- 55

- 3 CAS # 218

- 01

- 9 FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7

RBA = NB

CAS # 206

- 44

- 0 CAS # 85

- 01

- 8 CAS # 57

- 97

- 6 C H 3

C H 3

CAS # 129

- 00

- 0

CAS # 198

- 55

- 0

CAS # 92

- 06

- 8 CAS # 92

- 94

- 4 CAS # 103

- 29

- 7 CAS # 84

- 15

- 1 CAS # 61788

- 32

- 7 CAS # 56

- 49

- 5

C H 3

CAS # 207

- 08

- 9 CAS # 205

- 99

- 2 CAS # 193

- 39

- 5 CAS # 191

- 24

- 2 

# Inventory

– EDSP (2012)

“Fused Rings”

“Bridged Rings” ??????

Slide 273 of 320 

# Multicyclic Hydrocarbons

CAS # 92

- 52

- 4 CAS # 101

- 81

- 5CAS # 208

- 96

- 8 CAS # 581

- 42

- 0 C H 3

C H 3

CAS # 83

- 32

- 9

CAS # 53

- 70

- 3 CAS # 120

- 12

- 7 CAS # 56

- 55

- 3 CAS # 218

- 01

- 9 FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7

RBA = NB

CAS # 206

- 44

- 0 CAS # 85

- 01

- 8 CAS # 57

- 97

- 6 C H 3

C H 3

CAS # 129

- 00

- 0

CAS # 198

- 55

- 0

CAS # 92

- 06

- 8 CAS # 92

- 94

- 4 CAS # 103

- 29

- 7 CAS # 84

- 15

- 1 CAS # 61788

- 32

- 7 CAS # 56

- 49

- 5

C H 3

CAS # 207

- 08

- 9 CAS # 205

- 99

- 2 CAS # 193

- 39

- 5 CAS # 191

- 24

- 2 

# Inventory

– EDSP (2012)

“Fused Rings”

“Bridged Rings” ??????

Slide 274 of 320 

# Multicyclic Hydrocarbons

CAS # 119

- 64

- 2 CAS # 496

- 11

- 7 CAS # 3048

- 65

- 5 CAS # 91

- 17

- 8

CAS # 92

- 52

- 4 CAS # 101

- 81

- 5

# Rainbow Trout Training Set

FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7

RBA = NB DAC LogKow = 4.25 msrd

CAS# 613

- 31

- 0

RBA = NB AP LogKow = 4.83 msrd

CAS# 80

- 56

- 8

RBA = NB C H 3 C H 3

C

H 3

NAFT LogKow = 3.30 msrd

CAS# 91

- 20

- 3

RBA = NB

CAS # 208

- 96

- 8 CAS # 581

- 42

- 0 C H 3

C H 3

CAS # 83

- 32

- 9

CAS # 53

- 70

- 3 CAS # 120

- 12

- 7 CAS # 56

- 55

- 3 CAS # 218

- 01

- 9 FE LogKow = 4.18 msrd

CAS# 86

- 73

- 7

RBA = NB

CAS # 206

- 44

- 0 CAS # 85

- 01

- 8 CAS # 57

- 97

- 6 C H 3

C H 3

CAS # 129

- 00

- 0

CAS # 198

- 55

- 0 CAS # 56

- 49

- 5

C H 3

CAS # 207

- 08

- 9 CAS # 205

- 99

- 2 CAS # 193

- 39

- 5 CAS # 191

- 24

- 2 

# Inventory

– EDSP (2012) CAS # 85

- 01

- 8 CAS # 206

- 44

- 0 CAS # 129

- 00

- 0 CAS # 198

- 55

- 0 

### Slide 275 of 320 

# Multicyclic Hydrocarbons

– Fused Rings

CAS # 119

- 64

- 2 CAS # 496

- 11

- 7 CAS # 3048

- 65

- 5 CAS # 91

- 17

- 8C H 2



# Rainbow Trout Training Set

DPE LogKow = 4.30 CLogP
CAS# 530

- 48

- 3
RBA = 0.0045 CSB LogKow = 4.81 msrd

CAS# 645

- 49

- 8
RBA = 0.0052

TPM LogKow = 5.65 CLogP
CAS# 519

- 73

- 3
RBA = 0.0043 3PE LogKow = 5.87 CLogP
CAS# 58

- 72

- 0
RBA = 3.0 TSB LogKow = 4.81 msrd

CAS# 103

- 30

- 0

RBA = NB 4PE LogKow = 7.31 CLogP
CAS# 632

- 51

- 9

RBA = NB

DtBB LogKow = 7.68 CLogP
CAS# 1625

- 91

- 8

RBA = NB C H 3 C H 3

C H 3 C H 3

C H 3 C H 3

CAS # 92

- 06

- 8 CAS # 92

- 94

- 4 CAS # 103

- 29

- 7 CAS # 84

- 15

- 1 CAS # 61788

- 32

- 7 

# Inventory

– EDSP (2012) CAS # 92

- 94

- 4 CAS # 84

- 15

- 1



### Slide 276 of 320 

# Multicyclic Hydrocarbons

– Bridged Rings

CAS # 92

- 52

- 4 CAS # 101

- 81

- 5

# a) Assess Distribution of UnkBP Chemicals by ESv2 Decision Tree Categories

- Determine number of UnkBP chemicals within a chemical group

- Determine number of chemicals with HTP data

- Type of HTP data available

- ToxCast

– 8 assays (3 Binding; 5 TA) represent 2 levels of AOP

- Tox21

– 2 assays (2 TA) represent 1 level of AOP 

# Determining Where HTP Data Covers UnkBP Chemicals

b) Assess where HTP is across untested LogK
ow 

# ranges for UnkBP chemicals

- Select chemicals for testing to cover the LogK
ow 

# range

Part 1: Within Defined Groups

Summary:
203 UnkBP chemicals in defined groups;

77 chemicals have HTP (8 assay or 2 assay);

Test 10

- 20% more chemicals to cover remaining LogK
ow 

# ranges

Slide 277 of 320

# a) Assess Distribution of UnkBP Chemicals by ESv2 Decision Tree Categories

- Determine number of UnkBP chemicals within a chemical group

- Determine number of chemicals with HTP data

- Type of HTP data available

- ToxCast

– 8 assays (3 Binding; 5 TA) represent 2 levels of AOP

- Tox21

– 2 assays (2 TA) represent 1 level of AOP

b) Assess where HTP is across untested LogK
ow 

# ranges for UnkBP chemicals

- Select chemicals for testing to cover the LogK
ow 

# range

Part 1: Within ES Groups

Part 2: Within the mixed functional group classes Mixed Phenols and Mixed Organics

Slide 278 of 320 

# Determining Where HTP Data Covers UnkBP Chemicals

# Proposed Expansion of ESv2 to ESv3

Carboxy Esters Benzothiazoles Anthraquinones Aldehydes

non
- cyclic

Nitro Phenols Siloxanes Sulfonamides R1 O R2 O O

O 

# R1 O

R1 O

R2 Ketones

non
- cyclic

N

S SH

S O

O NH 2

Si O Si

O R1

R1

R1 R1 R1 Si

O R1 R1

R1 N 

## Pyridines & Quinolines

N O

O

OH N O

O 

## Nitro Aromatics 

## H 3 

## C N O Isocyanates

Cl

Cl 

## Chlorinated Cyclic Hydrocarbons (non

- aromatic) Cl

OH Br

OH F

OH I

OH 

## Halo Phenols

Cl

Cl Br

Br F

F Br

F Br

Cl F

Cl 

## Halo Benzenes (multiple halogens) OH O 

## Cyclohexanols Cyclohexanones

Slide 279 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 280 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventoryRBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 281 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Aldehyde Structures

– Expansion to ESv3

C H 3
C H 3
C H 3 C H 3 O

C H 3

O C H 3

O H 3 C O

C H 3 O C H 3

C H 3
C H 3 O C H 3
O

O C H 3

C H 3 O

O C H 3 O

C H 3

O C H 3 C H 3 O C H 3

O

C H 3 C H 3

C H 3

O C H 3

C H 3 O O

C H 3

C H 3 C H 3

C H 3 O O C H 3

C H 3

O

C H 3 C H 3 C H 3 O O

C H 3
C H 3 C H 3

O

C H 3

C H 3

C H 3

C H 3

O C H 3

C H 3

C H 3

O H 3 C C H 3
O

C H 3

C H 3

C H 3 O

C H 3

O

C H 3 H 3 C 

# Aromatic Ring

Ortho

- subst. Meta

- subst. Para

- subst.

Multi

- subst.

Slide 282 of 320O

C H 3

C H 3

O C H 3 C H 3

C H 3

O C H 3

O

C H 3 H 3 C C H 3

C H 3 C H 3 O

C H 3

C H 3 O C H 3 C H 2

C H 3 O

C H 3

C H 3

C H 3

O C H 3 C H 3
C H 3 O O

C H 3 C H 3

O C H 2 O

C H 2 O

C H 3 H 3 C H 3 C C H 3

O

C H 3 H 3 C C H 3
C H 3

O C H 3
O

C H 3 H 3 C

C H 3 C H 3 O C H 3

C H 3

C H 3

O C H 3 C H 3
O

C H 3 H 3 C

C H 3 H 3 C O

C H 3

C H 3 O

C H 3

C H 3 O

C H 3

O C H 3 C H 3 C H 3 C H 3

O C H 3 C H 3

O C H 3 C H 3

O C H 2
C H 3 O 

# multicyclic cyclohexene

Slide 283 of 320 

# EDSP Inventory

– Aldehyde Structures

– Expansion to ESv3RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 284 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Ketone Structures

– Expansion to ESv3

C H 3

O C H 3

O C H 3

O



### C H 3



### O C H 3 C H 3 H 3 C C H 3 C H 3

H 3 C

C H 3 O C H 3

O

C H 3

O C H 3
C H 3

O

C H 3

C H 3

O H 3 C C H 3 H 3 C C H 3

C H 3

C H 3
C H 3 H 3 C C H 3 C H 3

C H 3 O

C H 3 C H 3 C H 3 H 3 C C H 3 C H 3

H 3 C

C H 3 O

C H 3

C H 3 O

C H 3

O

C H 3 C H 3 C H 2

C H 3
C H 3

H 3 C

C H 3
C H 3 O C H 3 C H 3

C H 3 C H 3

O

C H 3 C H 3

C H 3 O C H 3
C H 3 H 3 C C H 3

C H 3

C H 3 O

C H 3

C H 3 O C H 3 H 3 C C H 3 C H 3

C H 3 O C H 3 H 3 C C H 3 C H 3 C H 3 C H 3

C H 3
C H 3 O C H 3



### Slide 285 of 320C H 3

C H 3 O C H 3 H 3 C H 3 C

C H 3

C H 3

C H 3

O C H 2 C H 3

C H 3

C H 3

O C H 3

C H 3 C H 3 O

C H 2 C H 3 C H 3

C H 3 C H 3

C H 3 O C H 3

C H 3

C H 3

O

C H 3 C H 3 C H 3

C H 3

O

C H 3 C H 3

C H 3

C H 3

C H 3

O C H 3 C H 3
C H 3

C H 3

O C H 3

C H 3

O

C H 3 C H 3

C H 3

C H 3

C H 3

O C H 2 C H 3

C H 3

C H 3

O C H 3 C H 3

C H 3

C H 3

O C H 3

C H 3

C H 3

O

C H 3 C H 3 C H 3

C H 3

O

C H 3 C H 3

C H 3

C H 3

O

C H 3 C H 3

C H 3

C H 3

O

C H 3 C H 3 C H 3

O

C H 3 H 3 C C H 3

O

C H 3 H 3 C C H 3

O

C H 3 H 3 C C H 3

C H 3

C H 3

C H 3

O

C H 3 C H 2 C H 3

O

C H 3 H 3 C C H 3 C H 3

C H 3

O

C H 3 C H 3 O C H 3 C H 3

C H 2 O C H 3 H 3 C

C H 2 C H 3

C H 3

O

C H 3 C H 3

C H 3 O H 3 C C H 3

C H 3

C H 3

O

C H 3 C H 3 C H 3 C H 3

C H 3

O

C H 3 C H 3



### Slide 286 of 320 

# EDSP Inventory

– Ketone Structures

– Expansion to ESv3RBA<0.00001% RBA>0.00001% UNK BP

#chems # chems # chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 287 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Cyclohexanone Structures

– Expansion to ESv3

O

C H 3


### C H 3 

### C H 3



### O

O

C H 3 

### H 3 

### C C H 3



### H H 

### O

C H 3



### O

C H 3 

### H 3 

### C C H 3 

### O C H 3



### C H 3 

### H 3 

### C

H H



### C H 3



### O C H 3 

### H 3 

### C C H 2 

### C H 3


### C H 3


### C H 3 

### O



## O C H 2 

### O

C H 3


### C H 3 

### C H 3 

### O

C H 3



### C H 3



### O

C H 3


### C H 3 

### C H 3



### O C H 3 

### C H 3 

### C H 3 

### H 3 

### C C H 3



### C H 2 

### O

C H 3 C H 3 H 3 C C H 3

C H 2 O

H

H



### O

C H 3 

### C H 2



## O C H 2 H 3 C C H 3

C H 3 O C H 2 

### O
C H 3



### C H 3 

### C H 3



### H H

Slide 288 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 289 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Pyridine & Quinoline Structures

– Expansion to ESv3

N N

C H 3 N

C H 3 N

C H 3

C H 3 N C H 2

N

C H 2 N

C H 3
C H 3 N

C H 3

C H 3 N C H 3 C H 3

N C H 3 N

C H 3

N

C H 3 N N

C H 3 H 3 C N

N N

N N C H 3

C H 3 N

C H 3

C H 3 N C H 3

N

C H 3

C H 3 N H 3 C C H 3

N

C H 3

C H 3 C H 3

N

N N + N + 

### N + 

### C H 3 

### N + 

### H 3 

### C C H 3

C H 3 N

C H 3 C H 3 C H 3

N

C H 2

C H 3 H 3 C N C H 3 C H 3 N

C H 3 C H 3 N C H 3

C H 3 N

H 3 C C H 3

C H 3 N C H 3

C H 3 C H 3
N 

# pyridines

quinolines

paraquat

- diaquat

bipyridines

Slide 290 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 291 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Anthraquinone Structures

– Expansion to ESv3

O O

H O O H

O O H 2 N B r

B r O O H O

N O

O

H O

N O

O O O

H O O H

H O

O H O O

H O

O H

O

O N H O

O

N H O O O

O O O H 2 N C H 3

O O N O O

O O N H C H 3

O O C l

O O H 2 N

O O H 3 C

O O

H O

H O O O

H O

O H O O N H 2

O O N

S

S

N O O

H O

O

O C l N H O

O

C l N H O O C l

O O H O

N H 2

H 2 N

O H O O

O

O

O N H 2 H 2 N O O O O H O C H 3

N H 2 N H 2

O H O O H O N O

O

H O N H O H

O O H 2 N O

O H O O N H H 3 C C H 3

O O N H 2

B r

O H O H

N H 2 O O H 3 C C H 3 C H 3



### Slide 292 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 293 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Benzothiazole Structures

– Expansion to ESv3

N S

N

C H 3 

### H 3 

### C H 3 

### C C H 3



### S 

### N S N H H 3 

### C C H 3



### C H 3



### S N S N H

S N S S N S

S 

### N S N

S

Slide 294 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 295 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

## C l

C l C l C l 

# EDSP Inventory

– Chlorinated Cyclichydrocarbon Structures Expansion to ESv3

C l C l C l

C l

C l C l C l C l

H H H 

### C l

C l C l C l C l C l

H

H H H H H

C l C l C l

C l

C l C l C l 

### B r

B r B r B r B r C l

C l C l C l

C l

C l C l

C H 2

H H H

H 

### C l

C l C l C l C l C l

H

H H H H H 

### C l

C l C l C l C l C l

H

H H H H H C l

C l C l C l C l C l

H

H H H H H

C l C l C l

C l

C l C l C H 2

H H H

H 

## C l



## C l C l C l

C l C l C l C l C l

C l C l

C l C l

C l
C l C l

C l

C l C l C l C l C l

C l

C l C l C l C l

H H H

H C l C l C l

C l

C l C l C l C l

H H H 

### C H 2



### C l

C l C l C l C l C l

C l

C l C l

C l C l

C l C l C l C l

C l

C l C l C l C l 

## C l

C l

C l C l C l C l

Slide 296 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 297 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Halobenzene Structures

– Expansion to ESv3

C l

C l C l



### B r

B r B r B r B r B r 

### C l

C l C l

C l C l C l



### C l
C l

B r B r C l

C l C l



### C l

C H 3 

### C l C l

C l C l C l C l C l C l

C l C l



### F

F

F

C l C l B r

F F F F F 

### B r F C l

C l

C l

C l C l C l C l



### C l

C l C l

C l C l C l



### C l
C l
C l C l C l C l



### C l

C l C l C l C l C l

C l
C l 

### C l

C l

C l

Slide 298 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 299 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Halophenol Structures

– Expansion to ESv3

C l

C l C l H O C l 

### C l

O H C l

C l

O H C l C l



### B r

O H C l

O H 

### C l

C l H O

C l

C l C l O H



### B r H O C l H O 

### C l

O H

B r

O H B r B r 

### O H

C l C l



### F

O H F H O



### I

O H I H O 

### C l

C l O H

C l

O H C l C l

C l O H

B r

B r B r B r B r O H 

### C l

C l C l O H

I

O H I I 

### O H

B r B r

I

O H 

### C l

O H



### Slide 300 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 301 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Isocyanate Structures

– Expansion to ESv3

N C O

C H 3 

### N

C

O

O C H 3

N C O

O

C H 3 N

C

O C H 3

N C O

C H 3 N

C

O C l

C l N

C
O 

### N C O C l N

C

O 

### N C O

N

C
O



### F

F

F

N

C
O

C H 3



### N C O N

C
O N C O

C H 3

C H 3

C H 3

C H 2 H 3 C N
C O 

### C H 3 

### C H 3



### C H 3 

### C H 3 

### N C O N C O



### C O

N N O
N

O C H 3

C H 3

C H 3 N C O N C O C O

N

N

C
O 

### C H 3



### N C O N

C
O C H 3



### C H 3



### N C O

C H 3 

### H 3 

### C



### Slide 302 of 320RBA<0.00001% RBA>0.00001% UNK BP

# chems # chems # chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 303 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Nitro Aromatic Structures

– Expansion to ESv3

C H 3

C H 3

C H 3
N O
O C H 3 N
O O C H 3 N O
O 

### C H 3



### N O
O C H 3



### N O

O N O

O

C H 3



### C H 3



### N O

O H 3 

### C



### N
O O N O

O N O

O

C H 3 N O

O

N
O O N O O

C H 3

C H 3 N
O O



### N O

O

N
O O N O

O H 3 C



### N O

O N
O O

N O

O

C H 3
C H 3 H 3 C C H 3

N O O

H 3 C

N
O O N O

O

C H 3 N
O O N O O

C H 3

N O
O N
O O

C H 3

C H 3

C H 3
N O
O C H 3 H 3 C C H 3 N O
O N O

O

N O
O

N O

O

N O
O C H 3 N O

O

C H 3 N
O O N O

O

N O

O H 3 C N O O C H 3

N O
O N
O O



### Slide 304 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 305 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Nitro Phenol Structures

– Expansion to ESv3

O H

N O
O 

## O H

N
O O O H N
O O



## O H

N O
O N
O O

N O

O

O H

C H 3 

### C H 3 

### N O O



## N O

O

O H N
O O N O O O H

N O

O H 3 

### C



## N O

O

O H N
O O

N O

O

O H C H 3



## N O O 

## N O

O

O H N
O O



## N O

O

O H N
O O C H 3 

## C H 3


## C H 3



## C H 3 

## O H C H 3 

## C H 3 

## H 3 

## C N O O



## N O

O

O H N
O O H 3 

## C C H 3



### Slide 306 of 320RBA<0.00001% RBA>0.00001% UNK BP

#chems #chems #chems Aldehydes 2 1 55 Carboxy Esters 12 0 151 Ketones 1 4 49 Cyclohexanols 2 0 32 Cyclohexanones 4 2 19 Pyridines & Quinolines 14 0 35 Anthraquinones 1 0 29
Benzothiazoles 5 0 5 Chlorinated Cyclic Hydrocarbons 0 0 18 Halo Benzenes 0 0 21 Halo Phenols 0 0 25 Isocyanates 3 0 18 Nitro Aromatics 1 0 24 Nitro Phenols 0 0 13 Siloxanes 1 0 7 Sulfonamides 19 1 9



### Slide 307 of 320 

# Number of Chemicals in 16 New Groups Proposed to Expand to ESv3

5975 EDSP inventory

# EDSP Inventory

– Sulfonamide Structures

– Expansion to ESv3

S O

O

N H

C H 3 

### H 3 

### C S O
O

N H

C H 3 

### C H 3



### H 3 

### C H 3 

### C

S N H 2



### O
O S O
O

N H

C H 3 

### H 3 

### C



### S O
O

N C O H 3 

### C

N H N

O O

S O
O

N H O C H 3

S O
O

N H

O

C H 3 N

N

C H 3 O O N H O

C H 3 C l O C H 3 O

N

S N H 2

O O O N H 3 C H 3 C

O



### O O

C H 3 

### N H

S O

O O N H



### Slide 308 of 320Total Class Total Class HTP LogP
range All
HTP LogP
range Testing needed

or LogP range #chems Proposed New Chem Group Use/Occurrence Class #chem LogP range TC+T21
8assays covered 8 or 2
assays covered HTP found to test to test
Aldehydes Fragr 55 1.34

- 5.27 3 1.34

- 4.36 17 1.34

- 4.36 need testing 4.36

- 5.27 1 to 3

Carboxy Esters Fragr

, some SDWA 151 1.58

- 15.51 11 1.51

- 8.63 57 1.51

- 15.51 TC&T21
covered

Ketones Fragr

, few SDWA or NF 49 1.96

- 6.35 4 2.04

- 6.35 15 1.96

- 6.35 T21 covered

Cyclohexanols Fragr

, some SDWA or NF 28 2.85

- 10.44 4 2.85

- 10.44 11 2.85

- 10.44 TC&T21
covered

Cyclohexanones Fragr

, some SDWA 20 1.54

- 5.48 1 2.94 9 2.25

- 3.81 need testing 1.54

- 2.25;3.81

- 5.48 1 to 3

Pyridines & Quinolines SDWA,
many Fragr 35

- 0.67

- 5.95 5 1.35

- 4.04 14 1.35

- 4.04 need testing 4.09

- 5.95 1 to 3

Anthraquinones all SDWA,
with o ne NF 29 3.16

- 9.02 1 2.43 11 2.43

- 9.02 T21 covered

Benzothiazoles all SDWA 5 2.56

- 5.95 0 4 2.56

- 5.95 T21 covered

Chlorinated Cyclic Hydrocarbons all SDWA 18 3.36

- 11.27 6 4.26

- 7.35 9 4.26

- 7.35 need testing 3.36

- 3.81;11.27 1 to 3

Halo Benzenes all SDWA 21 3.08

- 7.46 8 3.08

- 4.57 17 3.08

- 7.33 need testing 7.33

- 7.46 1

Halo Phenols all SDWA 25 1.71

- 5.96 7 2.16

- 4.18 15 1.71

- 5.96 T21 covered

Isocyanates all SDWA 18 2.59

- 6.11 2 3.7

- 4.75 12 3.06

- 6.11 need testing 2.59

- 3.7 1

Nitro Aromatics all SDWA 24 1.45

- 5.39 10 1.63

- 2.91 19 1.63

- 5.39 need testing 1.45

- 1.63 1

Nitro Phenols all SDWA 12 1.54

- 4.88 4 1.73

- 3.67 8 1.73

- 4.88 need testing 1.54

- 1.73 1

Siloxanes SDWA,

some NF 7 5.71

- 14.82 2 5.71

- 6.51 2 5.71

- 6.51 need testing 6.51

- 14.82 1 to 3

Sulfonamides SDWA,

some NF& F 9 1.87

- 4.33 1 2.86 3 1.87

- 2.86 need testing 2.86

- 4.33 1 to 3

Total= 506 69 223 **Recommended #**  **chems to** 
**test=** 10 to 22 

# Proposed New Groups to Cover 30% of UnkBP
Mixed Organics and Mixed Phenols

Slide 309 of 320

# A Closer Look at Acyclics

 As suggested by the Panel we looked at PFOA and PFOS

– both were positive in the binding and activation assays

PFOA PFOS

 Other structures open for investigation with respect to the EDSP inventory Acyclics

– i.e., looking beyond the pesticide inerts

Multiple halogenated alkanes (fluorine, chlorine, bromine)

– SDWA Aldehydes and Ketones

- Fragrances F

F F

F F

F F

F F

F F

F F

F F O

OH F F

S O

O OH

F F

F F

F F

F

F F

F F

F F

F F 

# • Consideration of Acyclics as negatives for the Food Use Inerts and Antimicrobial was determined to be appropriate based upon the training set.

• For expansion to the greater chemical universe further testing should be done.

• Caution in making the rule that all acyclics are negative.

• Example cited by the panel were PFOS and PFOA which were claimed to be positive in the literature.

Slide 310 of 320

# EDSP Inventory

– Perfluoro Structures

– Expansion to ESv3

F

F F

F F

F F

F

F F F

F F

F F

F F

F F

F F

F F

F F S

O O

F

F

F F

F F

F F

F F

N

F F

F F

F F

F F

F F F F

F F F F

F F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

F F

O O H F

F F

F F

F F

F F

F F

F F

F

F

F F

F F

F F

O O H F

F F F

F F

F F

F F

F F

F F

F F

F S O

O O H

F F

F F

F F

F O F F F O F O

F

F F F

F F

F F

F F F

F F

F F

F F

F F

F F

F F

F S O

O N O O C H 3 K +

F F

F

F F

F F O

F F F F F

F F

F F

F F

F F C H 2

F

F F F F

F F

F F F

F F

F S

O O

N O H S O O

O H

N C H 3 C H 3 Na F F

F F

F F

F F

F F

F F

F S O

O N O H

S O

O O N +

C H 3 O H O H F F

F F

F F

F F

F F

F F

F S O

O N O H

S O

O O N C H 3

C H 3 Na + Na F F

F F

F F

F F

F F

F F

F S O

O N O H

S O

O O N +

C H 3 O H O H 

# PFOA

PFOS

Slide 311 of 320

## 166 Ungrouped MO & MP with Both TC&T 21

Mixed Organics

- Unknown Binding Potential 117

Mixed Phenol

- Unknown Binding Potential 8

TC&T21 Total= 125

353 Ungrouped MO & MP, or ERESv 2 Grouped UnkBP Chems with ‘T 21 only’ by mixed class

Mixed Organics

- Unknown Binding Potential 276
Mixed Phenol

- Unknown Binding Potential 18

T21 only Total = 294

679 Ungrouped MO & MP or ERESv 2 Grouped UnkBP with no HTP

Mixed Organics

- Unknown Binding Potential 518
Mixed Phenol

- Unknown Binding Potential 58

No HTP Total= 576 

# Remaining Ungrouped MO and MPs UnkBP Chemicals and HTP D ata Availability

Slide 312 of 320

# Summary

 Assess degree to which an existing ES system covers a new chemical list

• Chemical categories, groups, LogK
ow 

# ranges



#  Systematically select chemicals for in vitro testing (either lower throughput or HTP) to expand TrSet to cover the entire list, i.e., EDSP Universe

• Part 1: test to cover broader LogK
ow 

# ranges in previously defined chemicals groups, or potentially new related groups; expect to test <10 %

• Part 2: test to cover large mixed functional group classes, Mixed Phenols and Mixed Organics; expect to test between 10 and 25% 

# Same Approach used to build initial Expert System is
used for additional inventories :

Slide 313 of 320

#  Iterative Approach

• Assess what cannot be adequately predicted

• Develop groups

• Test within groups

• Re

- evaluate activity within tested ranges with chemical groups

• Select chemicals to test to bound ranges of
unknowns

• etc...... ESV3

Slide 314 of 320 

# Summary

### Slide 315 of 320 

# Summary and Synthesis of the overall
Prioritization Scheme

Dr. Vicki Dellarco Office of Pesticide Programs Office of Chemical Safety and Pollution Prevention

# Legislative Framework

Scientific Framework Risk Management Challenges

Slide 316 of 320

# Programmatic Perspective On Scientific Framework/Methods

 Begin with End in Mind

• Clarity around the questions that need to be addressed & how certain does the answer need to be

– EDSP priority setting for pesticide SDWA chemicals, inerts , fragrances



#  Understand Type & Degree of Uncertainty Tolerated for Decision Context

• Scientific confidence in identification of low potency chemicals and that a negative in vitro means chemical unlikely to trigger the ER Pathway

• Scientific confidence that physicochemical filters indicate that chemical is unlikely to exhibit systemic effects relevant to endocrine disruption



#  Ensure Transparency

• Basis of science methods needs to be understood and transparent in a manner that maintains public confidence

Slide 317 of 320

#  Leverage an Established Foundation of Internationally Accepted Methods Prioritization scheme is a real world application of concepts/frameworks discussed at May 2011 SAP



# • Apply OECD (Q)SAR Validation Principles

– Domain of applicability

- Ensure predictive models applicable to chemical space

▫ Types of chemicals & range of properties found in regulatory inventories

▫ Selection of training set data



# – Defined endpoint/Mechanistic interpretation

– understanding of empirical data

▫ Use of HTP data to support expansion of ERES

Slide 318 of 320 

# Programmatic Perspective On Scientific Framework/Methods

#  Cont.

• Employ Integrated Approaches to Testing and Assessment (IATA)

– Use existing knowledge, hypothesis

- based

– Focus & test strategically

▫ Category

- based/read across to expand the ERES model domain



# • Use AOP concept to Strengthen IATA Strategy

– Conceptual basis for integrating knowledge from various technologies across different biological scales

– ERES: Relationships between chemical structure and activity

▫ Potential to initiate an ER Pathway

Slide 319 of 320 

# Programmatic Perspective On Scientific Framework/Methods

# • Other Endocrine AOPs; Androgen, Thyroid,
etc.

• Metabolism Issue 

# Looking Toward the Future

Slide 320 of 320 

# Programmatic Perspective On Scientific Framework/Methods