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

manibusan.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 Screening and Testing Program:

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)
Steroid Synthesis

Pubertal female X X X X X

In vivo

In vitro

ER Transcriptional X

Activation

X

X

HPT

X

X

HPG

Aromatase (Recombinant) X

Uterotrophic X

Hershberger X X

Pubertal male X X X

Steroidogenesis (H295R) X X

AR Binding X X

ER Binding X X

E E- A A- T E

Amphibian Metamorphosis

Fish Reproductive Screen X X X X X X

Steroid Synthesis

Pubertal female X X X X X

In vivo

In vitro

ER Transcriptional X

Activation

X

X

HPT

X

X

HPG

Aromatase (Recombinant) X

Uterotrophic X

Hershberger X X

Pubertal male X X X

Steroidogenesis (H295R) X X

AR Binding X X

ER Binding X X

E E- A A- T E

Amphibian Metamorphosis

Fish Reproductive Screen X X X X X X

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 provides 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 

Near-Term Test+ T1S Battery

PHASE 1

Targeted

EDSP Tier 

2 Tests

WOE+

WOEin vitro HTP/ in silico in vitro/in silico to target 

EDSP T1S

Intermediate –Term Test+

PHASE 2

WOE+

WOEin vitro HTP/ in silico 

(full replacement of Tier 1 battery)

Longer-Term 

PHASE 3

WOE+

WOESlide 16 of 320
EDSP21 Implementation

Key considerations:

 Clarity 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 could 

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 21st 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 Current and Emerging technologies

• Physico-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) 

PhysicoChemical 

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) 

PhysicoChemical 

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., pKa 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 pKa, the negative log 

of the acid dissociation constant

 For acids, the estimated pKa is for the parent 

acid

 For bases, the estimated pKa 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 Ka = (H+)(A-)

(HA)

pKa = - log(Ka)

 Base is a proton acceptor: 

B + H+  BH+ (e.g. ammonia, NH3 + H+  NH4

+)

Base dissociation constant Kb = (BH+)

 (B)(H+)

Base: Ka 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 pKa <2 (acids) or 

highest pKa of conjugate acid >11.5 (bases)

• Example

– Phosphoric acid has 3 pKas, 1.80, 6.95 and 12.9. The 

lowest pKa is less than 2. Exclude

– Guanidine is a strong base. The guanidinium ion is a 

weak conjugate acid with pKa 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 pKa <5 (acids) or the 

highest pKa of the conjugate acid >9 (bases)

• Examples

– Barbituric acid has 3 pKas, 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 pKas, 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

pKa of acids or 

conjugate acids of 

bases

Chemaxon's

"Chemicalize" 

predictive 

software

pKa < 2 or pKa 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 halflife < 40 days

Approx. 100 

Excluded

Charged at 

pH 7

pKa based net 

negative or positive 

charge at pH7

Chemaxon's

"Chemicalize" 

predictive 

software

Lowest acid pKa

< 5 or highest 

conjugate acid 

pKa >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) 

PhysicoChemical 

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 (ERmediated 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 

Chemical 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

A HO B

“A_site only” Interaction 

CH3

J. Katzenellenbogen

QOxygen= -0.25

Slide 55 of 320
R 394

E 353 H 524

C

T 347

A B

“B_site only” Interaction 

H3C

NH2

J. Katzenellenbogen

QOxygen= -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 LogKow 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 LogKow 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 LogKow 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)

E2

VN

HCP

CRTL

HOB

OHP

[3H]-E

2 Binding (%)

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

E2

P

PNEP

PNMP

PNBP

PNPrP

PIPrP

 Log Concentration (M)

[3H]-E

2 Binding (%)

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 Kow = 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 E2 efficacy)

0.0001

0.001

0.01

0.1

1

10

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

IAB E2 control

CTRL

Log Concentration (M)

Vtg mRNA (Fraction of maximum E

2 efficacy)

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

160

Percent 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

160

Percent 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

160

Percent 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

160

Percent 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

rec rtERα cyto rtER

E2

Phenol

Total 

Protein

(mg/mL)

0.01 4

RBA

(%)

0.0025 0.000026

Lower total assay protein, lower applied chemical conc

Higher total assay protein, higher applied chemical conc 

Same chemical 

free fraction 

displacing 3H-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 LogKow relationship within chemical groups

Slide 66 of 320
1E-06

1E-05

0.0001

0.001

0.01

0.1

1 2 3 4 5 6 7 8

Relative 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 LogKOW <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

rec rtERα cyto rtER

E2

Phenol

Total 

Protein

(mg/mL)

0.01 4

RBA

(%)

0.0025 0.000026

Lower total assay protein, lower applied chemical conc

Higher total assay protein, higher applied chemical conc 

Same chemical 

free fraction 

displacing 3H-E2

Slide 72 of 320
0.00001

0.0001

0.001

0.01

0.1

1

1 2 3 4 5 6 7 8

RBA %

log Kow

rec rtER rec hER

cyto rtER

Log Kow 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 320
0.00001

0.0001

0.001

0.01

0.1

1

1 2 3 4 5 6 7 8

RBA (%)

log Kow

rec rtERa rec hERa

cyto rtER

4-alkylanilines

Log Kow 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 KOW <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 cyclohexanols ( 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 System
CAS 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 also 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 training set. 

LogKow = 4.06 est

CAS#

NH2

H3C

LogKow = 3.05 m

CAS# 104-13-2

RBA = 0.00040

NH2

H3C

LogKow = 1.96 m

CAS# 589-16-2

RBA = 0.000047

NH2

H3C

LogKow = 2.40 m

CAS# 2696-84-6

RBA = 0.00011

H3C

H C NH2 3 NH2

LogKow = 1.39 m

CAS# 106-49-0

RBA = 0.000007 

LogKow = 5.12 est

H3C

NH2

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

NH2

H3C

NH2

H3C

NH2

LogKow = 0.90 m

CAS# 62533

RBA<0.000001%

LogKow = 2.70 m

CAS# 769926

RBA=0.000098

CH3

H3C

CH3

NH2

Training Set for related group: 4,t-alkylanilines: 

1E-06

1E-05

0.0001

0.001

0.01

0.1

1 3 5 7

RBA

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

HO

O

CH3

LogKow = 0.80 CLogP

CAS# 4065-45-6

O

HO

O

CH3

S

O

O OH

LogKow = 2.20 CLogP

CAS# 131-55-5

O

HO

OH

OH

HO

LogKow = 3.01 msrd

CAS# 131-56-6

O

HO

OH

LogKow = 7.29 CLogP

CAS# 1843-05-6

O

HO

O

CH3

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

HO

O

CH3

THBP

LogKow = 2.20 CLogP

CAS# 131-55-5

RBA = 0.1077

O

HO

OH

OH

HO

DHDPK

LogKow = 3.01 msrd

CAS# 131-56-6

RBA = 0.032

O

HO

OH

HBO

LogKow = 3.52 msrd

CAS# 117-99-7

RBA = 0.00097

O

HO

BHMB

LogKow = 0.80 CLogP

CAS# 4065-45-6

RBA = NB

O

HO

O

CH3

S

O

O OH

HMBP

LogKow = 3.79 CLogP

CAS# 131-57-7

RBA = 0.001013

O

HO

O

CH3

l) tested BHMB - negative for binding to rtER

Slide 89 of 320
Phenones

O

CH3

O

CH3

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

CH3

O

ACP

LogKow = 1.63 msrd

CAS# 98-86-2

pMBA

LogKow = 2.26 KOWWIN

CAS# 104-87-0

O

H3C

LogKow = 1.47 msrd

CAS# 100-52-7

LogKow = 5.70 CLogP

CAS# 21145-77-7

LogKow = 5.70 CLogP

CAS# 1506-02-1

H3C CH3

H3C CH3

H3C CH3

CH3

O

O

H3C CH3

H3C CH3

H3C CH3

CH3

O

H3C CH3

CH3

O

H3C CH3

O

CH3

CH3 O

CH3

CH3

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

CH3

H3C

O

H3C

CH3

O

TPH

LogKow = 4.84 KOWWIN

CAS# 2844-09-9

Slide 90 of 320
O

CH3

O

CH3

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

CH3

O

ACP

LogKow = 1.63 msrd

CAS# 98-86-2

RBA = NB

pMBA

LogKow = 2.26 KOWWIN

CAS# 104-87-0

RBA = NB

O

H3C

LogKow = 1.47 msrd

CAS# 100-52-7

LogKow = 5.70 CLogP

CAS# 21145-77-7

LogKow = 5.70 CLogP

CAS# 1506-02-1

H3C CH3

H3C CH3

H3C CH3

CH3

O

O

H3C CH3

H3C CH3

H3C CH3

CH3

O

H3C CH3

CH3

O

H3C CH3

O

CH3

CH3 O

CH3

CH3

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

CH3

H3C

O

H3C

CH3

O

TPH

LogKow = 4.84 KOWWIN

CAS# 2844-09-9

RBA = 0.0012

Slide 91 of 320

Phenones
Phenones - Branched 

H3C CH3

CH3

O

H3C CH3

O

CH3

CH3

O

CH3

H3C

O

CH3

CH3

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) 

CH3

O O

CH3

O

CH3

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

H3C

CH3

O

ACP

LogKow = 1.63 msrd

CAS# 98-86-2

RBA = NB

pMBA

LogKow = 2.26 KOWWIN

CAS# 104-87-0

RBA = NB

O

H3C

LogKow = 1.47 msrd

CAS# 100-52-7

LogKow = 5.70 CLogP

CAS# 21145-77-7

LogKow = 5.70 CLogP

CAS# 1506-02-1

H3C CH3

H3C CH3

H3C CH3

CH3

O

O

H3C CH3

H3C CH3

H3C CH3

CH3

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 CH3

H3C

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

HO

CH3

N CH3

H3C CH3

HO

N

N

Cl N

CH3

LogKow = 8.00 CLogP

CAS# 23328-53-2

LogKow = 8.00 CLogP

CAS# 25973-55-1

N

N

HO

CH3

CH3

N

CH3

H3C

HO

N

N

N

H3C

CH3

CH3

H3C

LogKow = 5.81 CLogP

CAS# 84268-33-7

CH3

H3C CH3

HO

N

N

N

O

O

CH3

N

N

HO

CH3

H3C

CH3

H3C

H3C

N

BMBP

LogKow = 7.63 CLogP

CAS# 3147-75-9

RBA = NB

N

N

HO

CH3

N

HMP

LogKow = 4.31 CLogP

CAS# 2440-22-4

RBA = NB

N

N

HO

CH3

H3C

CH3

H3C

H3C

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

CH3

Br

OH

CH3

H3C

H3C

Br

HO

H3C CH3

O

S

O

O

Br

Br OH

S

O

O

O

Br

HO

Br

BPB

LogKow = 4.88 msrd

CAS# 115-39-9

RBA = NB

PR

LogKow = 3.02 msrd

CAS# 143-74-8

RBA = 0.000101

OH

S

O

O

O

HO

Br

Br OH

S

O

O

O

Br

HO

Br

BPB

LogKow = 4.88 msrd

CAS# 115-39-9

RBA = NB

PR

LogKow = 3.02 msrd

CAS# 143-74-8

RBA = 0.000101

OH

S

O

O

O

HO

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

NH2

NH2

OH

O

OH

HO

HO

OH

O

HO

HO

HO

HO

HO

OH

OH

HO

HO

O

O

O

HN

" R1 OH H

N CH3

O

Acetanilides

Anhydrides

H3C O CH3

O O

Slide 96 of 320
Amino Anthracenedione

O

O

NH

CH3

NH

H3C

Rainbow Trout Training Set

Non-Food Use Inerts (2009) Inventory

QGS

LogKow = 8.00 KowWin

CAS# 128-80-3

RBA = NB

O

O

H2N

NH2

DAAQ

LogKow = 3.00 msrd

CAS# 128-95-0

RBA = NB

SBII

LogKow = 7.20 KowWin

CAS# 17354-14-2

RBA = NB

O

O

NH

H3C

NH

CH3

O

O

NH

O

O

HN

LogKow = 7.73 KowWin

CAS# 81-77-6

LogKow = 1.94 msrd

CAS# 2475-46-9

O

O

HN

CH3

NH

HO

LogKow = 4.98 KowWin

CAS# 27354-18-3

O

O

H2N

NH2

DAAQ

LogKow = 3.00 msrd

CAS# 128-95-0

RBA = NB

O

O

HN

H3C

CH3

LogKow = 5.38 KowWin

CAS# 4395-65-7

O

O NH2

HN

LogKow = 6.07 KowWin

CAS# 14233-37-5

O

O HN CH3

CH3

HN CH3

CH3

SBII

LogKow = 7.20 KowWin

CAS# 17354-14-2

RBA = NB

O

O

NH

H3C

NH

CH3

O

O

NH

CH3

NH

H3C

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

HN

H3C

NH

H3C

O

O

HN

H3C

CH3

CH3

NH

H3C

CH3

H3C

O

O

HN

H3C

CH3

NH

CH3

H3C

O

O

NH2

NH2

Slide 97 of 320
Phosphoric Acid Ester 

O

O P O

O

P O

O

O

O

H3C

H3C

Rainbow Trout Training Set

Non-Food Use Inerts (2009) Inventory

O

O P O

O

P O

O

O

O

H3C

H3C

O P

O

OH

O

CH3

O P

O

O

O

CH3

CH3

O P

O

O

O

CH3

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

OH

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

CH3

H3C CH3

P O

O

O

H3C

CH3

H3C

O

CH3

H3C

H3C

Slide 98 of 320
99

Contains 

a Cycle

Yes

Log KOW <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 cyclohexanols ( 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 Log 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 320
ACS

LogKow = -1.00 KOWWIN

CAS# 50-81-7

RBA = NB

O

OH

OH OH

HO O

H

LogKow = -1.00 KOWWIN

CAS# 89-65-6

O

OH

OH OH

HO O

H

LogKow = -1.00 KOWWIN

CAS# 134-03-2

O

OH

O OH -

HO O

H

Na+

LogKow = -1.00 KOWWIN

CAS# 6381-77-7

O

OH

O OH -

HO O H

Na+

LogKow = -0.91 KOWWIN

CAS# 27277-00-5

O

H3C

N

N

NH

N

H

N

CH3

CAF

LogKow = -0.07 msrd

CAS# 58-08-2

RBA = NB

O

N

CH3

O

N

H3C

N

N

CH3 URA

LogKow = -1.00 KOWWIN

CAS# 69-93-2

RBA = NB

O

N

H

O

N

H

N

H

O

HN

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

NH

N

N

HN

N

LogKow = -1.23 msrd

CAS# 58-61-7

H2N

N

HO

OH

HO

O

N

N N

(A) Ascorbic Acid Analogs; Caffeine Analogs

Vitamin C – ascorbic acid

Caffeine

Slide 100 of 320
O

H3C

H3C

IPN CH3

LogKow = 1.70 msrd

CAS# 78-59-1

RBA = NB

HMPY

LogKow = 0.02 msrd

CAS# 118-71-8

RBA = NB

O

OH

CH3

O

DHAA

LogKow = 0.78 KOWWIN

CAS# 520-45-6

RBA = NB

O

CH3

O

OH

H3C

O

DMXC

LogKow = 1.67 KOWWIN

CAS# 487-06-9

RBA = NB

O

CH3

O

H3C

O O

LogKow = 0.57 KOWWIN

CAS# 4437-85-8

O

O

H3C

O

LogKow = -0.41 msrd

CAS# 108-32-7

O O H3C

O

LogKow = 2.52 msrd

CAS# 6485-40-1

O

CH3

H2C

H3C

(B) Aldehyde Analogs; Ketone Analogs

HCIN

LogKow = 4.82 KOWWIN

CAS# 101-86-0

RBA = 0.001755

O

CH3

LogKow = 4.33 KOWWIN

CAS# 122-40-7

O

CH3

DAM

LogKow = 4.21 KOWWIN

CAS# 23696-85-7

RBA = 0.001138

CH3

CH3

O

CH3

CH3

MION

LogKow = 4.84KOWWIN

CAS# 1335-46-2

RBA = 0.0008063

CH3

CH3

CH3

O

CH3 H3C

H3C

O

CH3

CH3

H3C CH3

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 H3C

O

LogKow = 2.18 msrd 

CAS# 122-57-6

LogKow = 4.36 KOWWIN

CAS# 80-54-6

H3C

CH3

CH3

H3C

O

Aldehyde – Ketone ****

Slide 101 of 320
LogKow = 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

O CH3

O

O

O

O

CH3

CH3

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

CH3

O

NGDE

LogKow = 0.23 KOWWIN

CAS# 17557-23-2

RBA = NB

CH3

O CH3

O

O

O

(C) Di-ketone Analogs; Di-carboxy Ester Analogs; Epoxides

Di-ketone & Di-carboxy ester:

Epoxides:

Slide 102 of 320
LogKow = 2.31 KOWWIN

CAS# 98-94-2

N

H3C

CH3

LogKow = 3.98 CLogP

CAS# 4107-98-6

N

H3C

CH3

CH3

CH3

LogKow = 8.00 KOWWIN

CAS# 67-97-0

H2C

H3C

H3C

H3C CH3

OH

H

H

LogKow = 8.00 KOWWIN

CAS# 1406-16-2

H2C H3C

CH3

H3C CH3

OH

H

H

O Cl

Cl N

DOS O

LogKow = 1.94 KOWWIN

CAS# 71526-07-3

RBA = NB

LogKow = 2.25 KOWWIN

CAS# 52836-31-4

O

Cl

Cl

N

CH3

H3C

O

H3C

LogKow = 2.12 msrd

CAS# 121776-33-8

N

O

Cl

Cl

CH3

O CH3

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

H3C

H3C

LogKow = 2.89 KOWWIN

CAS# 614-45-9

O

O

O

CH3

CH3

CH3

Reactive Peroxides

LogKow = 3.46 msrd 

CAS# 94-36-0

O

O

O

O

LogKow = 8.00 KOWWIN

CAS# 58-95-7

CH3

O

CH3

O

H3C

CH3

CH3

CH3

CH3

H3C

CH3

O

Vitamin E acetate Vitamin E

Di-Chloroacetyl Oxazolidine

Tert-amine

Slide 103 of 320
BZC

LogKow = 1.86 msrd

CAS# 94-09-7

RBA = ??

O

H2N

O

CH3

EAB

LogKow = 2.57 msrd

CAS# 87-25-2

RBA = 0.00005877

O

NH2

O

CH3

O

O Si O

Si

Si O

H3C CH3

CH3

CH3

CH3 H3C

H3C

OCS

LogKow = 5.10 msrd

CAS# 556-67-2

RBA = NB

LogKow = 5.71 KOWWIN

CAS# 541-02-6

H3C

Si

CH3

O

Si

CH3

CH3

O

Si

CH3

H3C

O

Si

H3C

H3C

O

H C Si 3

H3C 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

H3C

(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

H3C CH3

CH3

O

Si

H3C

H3C

CH3

O

Si

CH3

CH3

H3C

LogKow = 4.03 KOWWIN

CAS# 14576-08-0

H3C

CH3

H3C

O CH3

CH3

CH3

H3C OH

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

H3C

O

HO

H3C

O

OH

VN

LogKow = 1.21 msrd

CAS# 121-33-5

RBA = NB

OH

O

CH3

O

LogKow = 1.61 msrd

CAS# 121-32-4

OH

O

CH3

O

HQ

LogKow = 0.59 msrd

CAS# 123-31-9

RBA = NB

LogKow = 0.80 msrd

CAS# 108-46-3

OH

HO

OH

OH

PO

LogKow = -0.72 msrd

CAS# 65-23-6

RBA = NB

CH3

OH

HO

HO

N

CH3

OH

HO

HO

N+

H ClLogKow = -0.72 msrd

CAS# 58-56-0

Slide 105 of 320
106

Contains 

a Cycle

Yes

Log KOW <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 cyclohexanols ( 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 Log 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 320
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

ESv2 Predictions

Slide 111 of 320

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

- Similar coverage whether INERTS, or SDWA Only
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

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 Predictions
ER 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 320
A). 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 320
Excluded 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 320
INERTS 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 nonSDWA= 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 ESv2 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 320
ER 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) 

PhysicoChemical 

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?”

• Use 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

Chemicals

Assays

1800 8200

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-ligandmediated

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 μM, follow-up with concentration response

– Single replicate, 8 points (0.02-50 μM)

– Most reference chemicals (positive and negative) run in 

triplicate

Appendix F Slide Slide 135 135 of 320 of 320 135
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 μM – 6 nM

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

Appendix F Slide 136 of 320
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 μM – 6 nM

 Lower-throughput version of BG1 Luc ER TA assay recently validated by OECD 

and ECCVAM

Appendix F Slide 137 of 320
NCGC Assay Plate Layout

Slide 138 of 320
NCGC Plate Layout

– Concentration-response series

Slide 139 of 320

15-point

concentrationresponse series
OT Luciferase Transactivation

Agonist Assay

 Conducted by Odyssey Thera (OT)

 Stable 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 μM

Appendix F Slide 140 of 320
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 μM (Highest concentration for any HTP assay)

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

Appendix F Slide 141 of 320
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 (AC50) is derived from the fitted model. 

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

• it achieves an AC50

• the R2 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 

Page 50 Slide 146 of 320
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/(AC50 **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. 

Filter out AC50 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 AC50 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

Page 73 Slide 154 of 320
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 Expected

Tox21 

BG1 LUC

Tox21 

BLA

ATG ERa 

TRANS

ATG ERE 

CIS

OT LUC

NVS_NR_

hER

NVS_NR_

bER

NVS_NR_

mERa

50-28-2 17beta-estradiol Strong A A A A A A A A

56-53-1 Diethylstilbestrol (DES) Strong A A Aa Aa Aa Aa Aa Aa

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 Ii 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 Ac

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 Ad 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 Ae I

b A A Ii Ah 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 Ab A I I I I

57-83-0 Progesterone Negative I I Ag Ag 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 320

Tox21 BG1 LUC

Tox21 BLA

ATG ERa TRANS

ATG ERE CIS

OT LUC

NVS_NR_hERNVS_NR_bER

NVS_NR_mERa

Reference Chemicals Tested 

(Actives/Inactives) 28/9 27/9 23/8 24/8 25/8 24/8 25/8 25/8

Concordance1,4 1 0.94 0.94 0.91 0.79 0.91 0.73 0.78

Sensitivity2 

 1 0.93 1 1 0.72 0.92 0.68 0.71

Specificity3 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

Page 88 Slide 162 of 320 -89, Table 6.3.3

Data has not yet been filtered for analytical QC failures
Concordance Among Different Assays

Page 91 Slide 163 of 320
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) 

PhysicoChemical 

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 Kow 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

HO

O

CH3

THBP

LogKow = 2.20 CLogP

CAS# 131-55-5

RBA = 0.1077

O

HO

OH

OH

HO

DHDPK

LogKow = 3.01 msrd

CAS# 131-56-6

RBA = 0.032

O

HO

OH

HBO

LogKow = 3.52 msrd

CAS# 117-99-7

RBA = 0.00097

O

HO

HMBP

LogKow = 3.79 CLogP

CAS# 131-57-7

RBA = 0.0010

O

HO

O

CH3

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 

yes competitive binder?

*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: Decision Path Step 2 for Type A & Type B Displacement Curves: 50 - 80% displacement

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

rec rtERα cyto rtER

E2

Phenol

Total 

Protein

(mg/mL)

0.01 4

RBA

(%)

0.0025 0.000026

Lower total assay protein, lower applied chemical conc

Higher total assay protein, higher applied chemical conc 

Same chemical 

free fraction 

displacing 3H-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:

Decision Path Step 2 for Type E Displacement Curves: Flatline

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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 OH

O

CH3

O OH

OH

O OH

HO OH OH

O OH

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

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]-E2 Binding (%)

O OH

HO OH OH

 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]-E2 Binding (%)

O OH

OH

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 OH

O

CH3

O OH

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]-E2 Binding (%)

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]-E2 Binding (%)

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-UASßLactamase + 

GAL4_hERα LBD = 

ß-lactamase

Fluorescence considered low for 

HEK-293 cells 

Tox21_BG1_ERα/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

1.0×105

1.0×106

1.0×107

1.0×108

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

AAN

E2

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

CH3

CH3

HS CH3

4-t-butylbenzenethiol

[2396-68-1] p-toluene thiol

[106-45-6]

HS CH3

Slide 192 of 320
rtER Binding: Alkylbenzenethiol Example

CH3

CH3

HS CH3

4-t-butylbenzenethiol

[2396-68-1]

p-toluene thiol

[106-45-6] HS CH3

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]-E2 Binding (%)

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]-E2 Binding (%)

Slide 193 of 320
NVS Binding: Alkylbenzenethiol Example

NVS mERa

NVS hER

NVS bER

CH3

CH3

HS CH3

4-t-butylbenzenethiol

[2396-68-1] p-toluene thiol

[106-45-6] HS CH3

Inactive in 

25 μM prescreen

Inactive in 

25 μM prescreen

Inactive in 

25 μM prescreen

Slide 194 of 320
BLA Assay: Alkylbenzenethiol Example

CH3

CH3

HS CH3

4-t-butylbenzenethiol

[2396-68-1] p-toluene thiol

[106-45-6]

HS CH3

Slide 195 of 320
BG1 assay: Alkylbenzenethiol Example

CH3

CH3

HS CH3

4-t-butylbenzenethiol

[2396-68-1]

p-toluene thiol

[106-45-6]

HS CH3

Slide 196 of 320
Interpretation of Benzenethiol Results

CH3

CH3

HS CH3

4-t-butylbenzenethiol

[2396-68-1]

p-toluene thiol

[106-45-6] HS CH3

Inactive “Active”

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 structureactivity 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

HS CH3

CH3

CH3

HS CH3

HS

CH3

n-butylbenzenethiol

active

pentylbenzenethiol

HS

CH3

p-toluene thiol 4-t-butylbenzenethiol

test ? test ?

benzenethiol

HS

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]-E2 Binding (%)

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]-E2 Binding (%)

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

HO

CH3

H3C

CH3

CH3

CH3

N

N

N

HO

CH3

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

HO

CH3

H3C

CH3

CH3

CH3

N

N

N

HO

CH3

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 Active all 3 chemical source replicates Inactive

N

N

N

HO

CH3

H3C

CH3

CH3

CH3

N

N

N

HO

CH3

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

HO

CH3

H3C

CH3

CH3

N CH3

N

N

HO

CH3

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]-E2 Binding (%)

NVS mERa NVS hER NVS bER ERES rtER

S

O

O

HO

CH3

Slide 204 of 320
Dodecylbenzenesulfonic acid

trout Vtg Gene Expression

PCR_8.28.6

1.0×103

1.0×104

1.0×105

1.0×106

1.0×107

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

DBS

E2

CTRL

CTRL

Log Concentration (M)

VTG mRNA copies/400 ng total RNA

Dodecylbenzensulfonic Acid

rtER Gene Expression:Antagonist Mode

1.0×104

1.0×105

1.0×106

-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

E2 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

OCH3

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]-E2 Binding (%)

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

S OH

O

O

HO

Slide 206 of 320

Potential Signal Artifacts ?

pH
8-Hydroxyquinoline Sulfate

liver slice Vtg mRNA_agonist

PCR 8HQ

1.0×103

1.0×104

1.0×105

1.0×106

1.0×107

1.0×108

-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

1.0×103

1.0×104

1.0×105

1.0×106

1.0×107

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

8HQ+E2-9

8HQ+E2-6

E2

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 Kow 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<LogKow<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 Kow 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<LogKow<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

OH

H3C

LogKow = 3.20 msrd

CAS# 645-56-7

RBA = 0.00088

CH3

H3C

CH3

OH

LogKow = 3.30 msrd

CAS# 585-34-2

RBA = 0.00091

H3C

OH

LogKow = 2.47 msrd

CAS# 123-07-9

RBA = 0.00036

HTP Inactive HTP Inactive HTP Inactive

OH

CH3

H3C

CH3

LogKow = 3.31 msrd

CAS# 98-54-4

RBA = 0.0014

CH3

H3C

CH3

HO

LogKow = 3.31 msrd

CAS# 88-18-6

RBA = 0.0018

OH

H3C

CH3

LogKow = 3.32 msrd

CAS# 99-71-8

RBA = 0.0018

H3C

H3C

HO

LogKow = 3.27 msrd

CAS# 89-72-5

RBA = 0.0010

OH

H3C

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 Kow 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<LogKow<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

OH H3C

CH3

H3C

CH3

H3C

4DP

LogKow = 7.27 CLogP

CAS# 27193-86-8

RBA = 0.012

NVS hER

BLA Active

BG1 Active

OH

H3C

PNP-5

LogKow = 5.99

CAS# 104-40-5

RBA = 0.016

BG1 Active

OH

H3C

PNP

LogKow = 5.92 msrd

CAS# 84852-15-3

RBA = 0.046

( branched )

All 3 NVS ER

BLA Active

BG1 Active

OH

CH3

H3C

CH3

PTAP

LogKow = 3.83 msrd

CAS# 80-46-6

RBA = 0.0040

OH

H3C

PNHpP

LogKow = 5.15 CLogP

CAS# 1987-50-4

RBA = 0.021

BLA Active

BG1 Active

BG1 Active

OH

CH3

CH3

H3C

H3C

CH3

PTOP

LogKow = 5.16 CLogP

CAS# 140-66-9

RBA = 0.0094

OPDTBP

LogKow = 5.19 msrd

CAS# 96-76-4

RBA = 0.0027

H3C

CH3

CH3

OH

CH3

CH3

H3C OH

H3C

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) 

PhysicoChemical 

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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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-; or2,4,6-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 

ESv2 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-; or2,4,6-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 

ESv2 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-; or2,4,6-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 

ESv2 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-; or2,4,6-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 

ESv2 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-; or2,4,6-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

2nd Largest Number are ‘VI. Site A-type Potential Binders’

Slide 233 of 320

ESv2 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

2nd Largest Number are ‘VI. Site A-type Potential Binders’

Slide 234 of 320

Distribution Of UnkBP Chemicals By ESv2 Decision Tree Categories

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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 

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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

ESv2 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 LogKow 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 320
1E-06

1E-05

0.0001

0.001

0.01

0.1

1 2 3 4 5 6 7 8

RBA

Log Kow

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

1.3<LogKow<5.1

LogKow = 3.05 m

NH2

H3C

LogKow = 1.96 m

NH2

H3C

LogKow = 2.40 m

H3C

H C NH2 3 NH2

LogKow = 1.39 m

LogKow = 5.12 est

H3C

NH2

LogKow=3.39 m Log Kow = 4.06 est

NH2

H3C

NH2

H3C

NH2

LogKow = 0.90 m

LogKow = 2.70 m

CH3

H3C

CH3

NH2

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 groups 
ESv2 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 groups 
HTP 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

ESv2 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

T21

covered -- --

Redefining a Large Chemical Group 

Example: Multi-Cyclic Hydrocarbons 

- 67 chemicals in the groups with UnkBP

Slide 267 of 320
CH2

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)

H3C

H3C

H3C

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

CH3

H3C CH3

CH3 CH3

H3C

H3C

H3C

LogKow = 3.30 msrd

CAS# 91-20-3

LogKow = 3.30 msrd

CAS# 91-20-3

LogKow = 7.68 CLogP

CAS# 1625-91-8

H3C

CH3

CH3

CH3

H3C

H3C

CH3

CH3

CH2

CH2

CH3 H3C

LogKow = 4.31 msrd

CAS# 28804-88-8

H3C

CH3

LogKow = 6.88 CLogP

CAS# 69009-90-1

H3C

CH3

CH3

H3C

Slide 268 of 320
CH2

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)

H3C

H3C

H3C

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

CH3

H3C CH3

CH3 CH3

H3C

H3C

H3C

LogKow = 3.30 msrd

CAS# 91-20-3

LogKow = 3.30 msrd

CAS# 91-20-3

LogKow = 7.68 CLogP

CAS# 1625-91-8

H3C

CH3

CH3

CH3

H3C

H3C

CH3

CH3

CH2

CH2

CH3 H3C

LogKow = 4.31 msrd

CAS# 28804-88-8

H3C

CH3

LogKow = 6.88 CLogP

CAS# 69009-90-1

H3C

CH3

CH3

H3C

Slide 269 of 320

Multicyclic Hydrocarbons
CH2

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)

H3C

H3C

H3C

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

CH3

H3C CH3

CH3 CH3

H3C

H3C

H3C

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

H3C

CH3

CH3

CH3

H3C

H3C

CH3

CH3

CH2

CH2

CH3 H3C

LogKow = 4.31 msrd

CAS# 28804-88-8

H3C

CH3

LogKow = 6.88 CLogP

CAS# 69009-90-1

H3C

CH3

CH3

H3C

Slide 270 of 320

Multicyclic Hydrocarbons
CH2

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)

H3C

H3C

H3C

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

CH3

H3C CH3

CH3 CH3

H3C

H3C

H3C

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

H3C

CH3

CH3

CH3

H3C

H3C

CH3

CH3

CH2

CH2

CH3 H3C

LogKow = 4.31 msrd

CAS# 28804-88-8

H3C

CH3

LogKow = 6.88 CLogP

CAS# 69009-90-1

H3C

CH3

CH3

H3C

Slide 271 of 320

Multicyclic Hydrocarbons
CAS# 581-42-0 CAS# 208-96-8

H3C

CH3

CAS# 83-32-9

CAS# 53-70-3

CAS# 120-12-7 CAS# 218-01-9 CAS# 56-55-3

FE

LogKow = 4.18 msrd

CAS# 86-73-7

RBA = NB

CAS# 85-01-8 CAS# 57-97-6 CAS# 206-44-0

CH3

CH3

CAS# 129-00-0

CAS# 198-55-0

CAS# 103-29-7 CAS# 61788-32-7 CAS# 92-94-4 CAS# 92-06-8 CAS# 84-15-1

CAS# 56-49-5

H3C

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# 496-11-7 CAS# 119-64-2 CAS# 91-17-8 CAS# 3048-65-5

CAS# 92-52-4 CAS# 101-81-5
CAS# 496-11-7 CAS# 119-64-2 CAS# 91-17-8 CAS# 3048-65-5 CAS# 581-42-0 CAS# 208-96-8

H3C

CH3

CAS# 83-32-9

CAS# 53-70-3

CAS# 120-12-7 CAS# 218-01-9 CAS# 56-55-3

FE

LogKow = 4.18 msrd

CAS# 86-73-7

RBA = NB

CAS# 85-01-8 CAS# 57-97-6 CAS# 206-44-0

CH3

CH3

CAS# 129-00-0

CAS# 198-55-0

CAS# 103-29-7 CAS# 61788-32-7 CAS# 92-94-4 CAS# 92-06-8 CAS# 84-15-1

CAS# 56-49-5

H3C

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# 101-81-5
CAS# 581-42-0 CAS# 208-96-8

H3C

CH3

CAS# 83-32-9

CAS# 53-70-3

CAS# 120-12-7 CAS# 218-01-9 CAS# 56-55-3

FE

LogKow = 4.18 msrd

CAS# 86-73-7

RBA = NB

CAS# 85-01-8 CAS# 57-97-6 CAS# 206-44-0

CH3

CH3

CAS# 129-00-0

CAS# 198-55-0

CAS# 103-29-7 CAS# 61788-32-7 CAS# 92-94-4 CAS# 92-06-8 CAS# 84-15-1

CAS# 56-49-5

H3C

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# 496-11-7 CAS# 119-64-2 CAS# 91-17-8 CAS# 3048-65-5

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

H3C

H3C

H3C

NAFT

LogKow = 3.30 msrd

CAS# 91-20-3

RBA = NB

CAS# 581-42-0 CAS# 208-96-8

H3C

CH3

CAS# 83-32-9

CAS# 53-70-3

CAS# 120-12-7 CAS# 218-01-9 CAS# 56-55-3

FE

LogKow = 4.18 msrd

CAS# 86-73-7

RBA = NB

CAS# 85-01-8 CAS# 57-97-6 CAS# 206-44-0

CH3

CH3

CAS# 129-00-0

CAS# 56-49-5 CAS# 198-55-0

H3C

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# 496-11-7 CAS# 119-64-2 CAS# 91-17-8 CAS# 3048-65-5
CH2

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

H3C

CH3

CH3

CH3

H3C

H3C

CAS# 103-29-7 CAS# 61788-32-7 CAS# 92-94-4 CAS# 92-06-8 CAS# 84-15-1

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 LogKow ranges for UnkBP chemicals 

- Select chemicals for testing to cover the LogKow 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 LogKow 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 LogKow ranges for UnkBP chemicals 

- Select chemicals for testing to cover the LogKow 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

NH2

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 H3C 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 320
RBA<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 inventory
RBA<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

CH3

CH3

CH3

CH3 O

CH3

O

CH3

O

H3C

O

CH3 O

CH3

CH3

CH3 O

CH3

O

O

CH3

CH3 O

O CH3

O

CH3

CH3 O

CH3

O CH3

O

CH3

CH3

CH3

O

CH3

O CH3

O

CH3

CH3

CH3

CH3

O

O CH3

CH3

O

CH3

CH3

CH3

O

O

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

O

H3C CH3

O

CH3

CH3

CH3

O

CH3

O

CH3

H3C

Aromatic Ring

Ortho- subst. Meta - subst.

Para - subst.

Multi - subst.

Slide 282 of 320
O

CH3

CH3

CH3 O

CH3

CH3

O

CH3

O

CH3

H3C

CH3

CH3 CH3

O

CH3

CH3

O

CH3

CH2

CH3 O

CH3

CH3

CH3

O

CH3

CH3

CH3

O

O

CH3

CH3

O

CH2 O

CH2

O

CH3

H3C

H3C CH3

O

CH3

H3C

CH3

CH3

O

CH3

O

CH3

H3C

CH3

O CH3

CH3

CH3

CH3

O

CH3

CH3

O

CH3

H3C

H3C CH3

O

CH3

CH3

O

CH3

CH3

O

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

O

CH3

CH3

O CH2

CH3

O

multicyclic

cyclohexene

Slide 283 of 320

EDSP Inventory – Aldehyde Structures – Expansion to ESv3
RBA<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

CH3

O

CH3

O CH3

O

CH3

O

CH3

CH3

H3C

CH3

CH3

H3C

CH3

O

CH3

O

CH3

O

CH3

CH3

O

CH3

CH3

H3C O

CH3

H3C

CH3

CH3

CH3

CH3

H3C

CH3 CH3

CH3

O

CH3

CH3

CH3

H3C

CH3

CH3

H3C

CH3

O

CH3

CH3

O

CH3

O

CH3 CH3

CH2

CH3

CH3

H3C

CH3

CH3

O

CH3

CH3

CH3 CH3

O

CH3

CH3

CH3

O

CH3

CH3

H3C CH3

CH3

CH3

O

CH3

CH3 O

CH3

H3C

CH3

CH3

CH3

O

CH3

H3C

CH3

CH3

CH3

CH3

CH3

CH3

O CH3

Slide 285 of 320
CH3

CH3

O

CH3

H3C

H3C

CH3

CH3

CH3

O

CH2

CH3

CH3

CH3

O

CH3

CH3

CH3 O

CH2 CH3

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

O

CH3

CH3

CH3

CH3

CH3

O

CH2

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

CH3

O

CH3

CH3

CH3

O

CH3

H3C

CH3

O

CH3 H3C

CH3

O

CH3

H3C

CH3

CH3

CH3

CH3

O

CH3

CH2

CH3

O

CH3

H3C

CH3

CH3

CH3

O

CH3

CH3

O

CH3 CH3

CH2

CH3 O

H3C

CH2

CH3

CH3

O

CH3

CH3

CH3 O

H3C

CH3

CH3

CH3

O

CH3 CH3

CH3

CH3

CH3

O

CH3

CH3

Slide 286 of 320

EDSP Inventory – Ketone Structures – Expansion to ESv3
RBA<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

CH3

CH3

CH3

O

O

CH3

H3C

CH3

H H

O

CH3

O

CH3

H3C

CH3

O

CH3

CH3

H3C

H

H

CH3

O CH3

H3C

CH2

CH3

CH3

CH3

O

O

CH2

O

CH3

CH3

CH3 O

CH3

CH3

O

CH3

CH3

CH3

O

CH3

CH3

CH3

H3C

CH3

CH2

O

CH3

CH3

H3C

CH3

CH2

O

H

H

O

CH3

CH2

O

CH2

H3C

CH3

CH3

O

CH2

O

CH3

CH3

CH3

H

H

Slide 288 of 320
RBA<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

CH3

N

CH3

N

CH3

CH3

CH N 2

N

N CH2

CH3

CH3

N

CH3

CH3

N

CH3

CH3

N

N CH3

CH3

N

CH3

N

N

CH3

H3C

N

N

N

N N

CH3

CH3

N

CH3

CH3

N

CH3

N

CH3

CH3

N

H3C CH3

N

CH3

CH3

CH3

N

N

N+ N+

N N+ CH3 H + 3C

CH3

CH3

N

CH3

CH3

CH3

N

CH2

CH3

H3C

N

CH3 CH3

N

CH CH3 3

N

CH3

CH3

N

H3C CH3

CH3

N

CH3

CH3

CH3

N

pyridines

quinolines

paraquat - diaquat

bipyridines

Slide 290 of 320
RBA<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

HO

OH

O

O

H2N

Br

Br

O

O

HO

N

O

O

HO

N O

O

O

O

HO

OH

HO

OH

O

O

HO

OH

O

O

NH

O

O

O NH

O

O

O

O

O

H2N

CH3

O

O

N O

O

O

O

NH

CH3

O

O

Cl

O

O

H2N

O

O

H3C

O

O

HO

HO O

O

HO

OH

O

O

NH2

O O

N

S

S

N

O

O

HO

O

O

Cl NH

O

O

Cl NH

O

O

Cl

O

O

HO

NH2

H2N

OH

O

O

O

O

O

NH2

H2N

O

O

O OH

O

CH3

NH2

NH2

OH

O O

HO N

O

O

HO

NH

OH

O O

H2N

O

OH

O

O

NH

H3C

CH3

O

O NH2

Br

OH

OH

NH2

O

O

H3C

CH3

CH3

Slide 292 of 320
RBA<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

CH3

H3C

H3C CH3

S N

S

NH

H3C

CH3

CH3

S N

S

NH

S

N

S S

N

S

S

N

S

N

S

Slide 294 of 320
RBA<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
Cl

Cl

Cl

Cl

EDSP Inventory – Chlorinated Cyclichydrocarbon Structures 

Expansion to ESv3

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

H

H H

Cl

Cl

Cl

Cl

Cl

Cl

H

H

H

H

H

H

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Br

Br Br

Br

Br Cl

Cl

Cl

Cl

Cl

Cl

Cl

CH2

H

H

H

H

Cl

Cl

Cl

Cl

Cl

Cl

H

H

H

H

H

H

Cl

Cl

Cl

Cl

Cl

Cl

H

H

H

H

H

H

Cl

Cl

Cl

Cl

Cl

Cl

H

H

H

H

H

H

Cl Cl Cl

Cl

Cl

Cl

CH2

H

H

H

H

Cl

Cl

Cl

Cl

C Cl l

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

H

H

H

H

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

H

H H

CH2

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl Cl

Cl

Cl

Cl Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Slide 296 of 320
RBA<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

Cl

Cl Cl

Br

Br Br

Br

Br Br

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Cl

Br Br

Cl

Cl

Cl

Cl

CH3 Cl

Cl

Cl Cl

Cl

Cl Cl

Cl

Cl

Cl

F

F

F

Cl

Cl Br

F F

F

F F

F Br

Cl

Cl

Cl

Cl Cl

Cl

Cl

Cl

Cl

Cl

Cl Cl

Cl

Cl

Cl

Cl

Cl

Cl Cl

Cl

Cl Cl

Cl

Cl Cl

Cl

Cl

Cl

Cl

Cl

Slide 298 of 320
RBA<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

Cl

Cl Cl

HO

Cl

Cl

Cl OH

Cl

Cl OH

Cl

Br

OH

Cl

OH

Cl

Cl

HO

Cl

Cl

Cl

OH

HO Br

HO Cl Cl

OH

Br

Br OH

Br

OH

Cl

Cl

F

OH

HO F

I

OH

HO I

Cl

OH Cl

Cl

OH

Cl Cl

Cl

OH

Br

Br Br

Br

Br OH

Cl

Cl Cl

OH

I

I OH

I

OH

Br

Br

I

OH

Cl

OH

Slide 300 of 320
RBA<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

N CH3

C

O

O

CH3

N

C

O

O

CH3

N

C

O

CH3

N

C

O

CH3

N

C

O

Cl

Cl

N

C

O

N

C

O

N Cl

C

O

N

C

O

N

C

O

F

F

F

N

C

O

CH3

N C O

N

C

O

N

C

O

CH3

CH3

CH3

CH2

H3C

N

C O

CH3

CH3

CH CH3

3

N

C

O

N

C

O

C

O

N

N

O

N

O

CH3

CH3

CH3 N C O

O C N

C

O

N

N

C

O

CH3

N C O

N

C

O

CH3

CH3

N C O

CH3

H3C

Slide 302 of 320
RBA<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

CH3

CH3

CH3

N O

O

CH3

N

O

O

CH3 N

O

O

CH3

N O

O

CH3

N

O

O

N

O

O

CH3

CH3

N O

O

H3C

N

O

O

N

O

O

N

O

O

CH3

N

O

O

N

O

O

O N

O

CH3

CH3

N

O

O

N

O

O

N

O

O

N

O

O

H3C

N

O

O

N

O

O

N

O

O

CH3

CH3

H3C

CH3

N

O

O

H3C

N

O

O

N

O

O

N CH3

O

O

O N

O

CH3

N O

O

N

O

O

CH3

CH3

CH3

N O

O

CH3

H3C

CH3 N

O

O

N

O

O

N O

O

N

O

O

N O

O

CH3

N

O

O

N CH3

O

O

N

O

O

N O

O

H3C

N

O O

CH3

N O

O

N

O

O

Slide 304 of 320
RBA<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

OH

N O

O

OH

N

O

O

N OH

O

O

OH

N O

O

N

O

O

N

O

O

OH

CH3 CH3

O N

O

N

O

O

N OH

O

O

O N

O

OH

N O

O

H3C

N

O

O

OH

N

O

O

N

O

O

OH CH3

O N

O

N

O

O

N OH

O

O

N

O

O

N OH

O

O

CH3

CH3

CH3

CH3

OH

CH3 CH3

H3C

O N

O

N

O

O

OH N

O

O

H3C

CH3

Slide 306 of 320
RBA<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

NH

CH3

H3C S

O

O

NH

CH3

CH3

H3C

H3C

S

NH2

O

O

S

O

O

NH

CH3

H3C

S

O

O

N

C

O

H3C

NH

O N

O

S

O

O

NH

O

CH3

S

O

O

NH

O

CH3

N

N

CH3

O

O

O NH

CH3

Cl O

CH3

O

N

S

NH2

O

O

O

H N 3C

H3C

O

O

O

CH3

NH

S O

O O

NH

Slide 308 of 320
Total 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 one 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

O S

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

S F

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

OH F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

F

O

OH

F

F F

F

F

F

F

F

F

F

F

F

F

F

F

F

F S

O

O

OH

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

OCH3

K+

F F

F

F

F

F

F

O

F

F

F F

F

F

F

F

F

F

F

F

F CH2

F

F F

F F

F

F

F F

F

F

F

F

S

O

O

N OH

S O

O

OH

H3C N

CH3

Na F

F

F

F

F

F

F

F

F

F

F

F

F

S

O

O

N

OH

S

O

O

ON+

CH3 OH

OH

F

F

F

F

F

F

F

F

F

F

F

F

F

S

O

O

N

OH

S

O

O

ON

CH3

CH3

Na+

Na F

F

F

F

F

F

F

F

F

F

F

F

F

S

O

O

N

OH

S

O

O

ON+

CH3 OH

OH

PFOA

PFOS

Slide 311 of 320
166 Ungrouped MO & MP with Both TC&T21

Mixed Organics - Unknown Binding Potential 117

Mixed Phenol - Unknown Binding Potential 8

TC&T21 Total= 125

353 Ungrouped MO & MP, or ERESv2 Grouped UnkBP Chems with ‘T21

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 ERESv2 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 Data Availability 

Slide 312 of 320
Summary

 Assess degree to which an existing ES system covers a 

new chemical list

• Chemical categories, groups, LogKow 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 LogKow 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