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Overview of the CompTox Research Effort
Russell ThomasDirectorNational Center for Computational Toxicology
ECHO SeminarApril 21, 2017
The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the U.S. EPA
National Center forComputational Toxicology
Outline
• Short overview of CompTox research effort
• Availability of research data
• Potential application to prioritizing for exposure monitoring
1
National Center forComputational Toxicology
Understanding ‘Why’ We Need to Innovate In This Space…
0
10
20
30
40
50
60
70
Per
cent
of C
hem
ical
s
Acute Cancer
Gentox Dev Tox
Repro Tox EDSP Tier 1
<1%
Modified from Judson et al., EHP 2010
$1,000
$10,000
$100,000
$1,000,000
$10,000,000
Cos
t
Number of Chemicals /Combinations
Ethics Concerns Economics
Lack of Data
National Center forComputational Toxicology
3
Risk Assessments Generally Contain a Standard Set of Components
New technologies and approaches will also have to cover these basic components
Phys Chem
Exposure
HazardDose Response, PK, and PODs
Risk SummaryUncertainty
Variability
National Center forComputational Toxicology
4
It All Starts With Chemistry…
• Chemical structure database of >700,000 unique substances with QC flags to link chemical structure with names and identifiers
• Consensus QSAR models for a range of physical chemical properties, environmental fate, and hazard characteristics
• Comprehensive physical-chemical property database (experimental and predicted)
https://comptox.epa.gov/dashboard
National Center forComputational Toxicology
5
Adding the High-Throughput Hazard Screening Component
ToxCast
Concentration
Res
pons
e
~600 Cell & biochemical
assays
~1,000 Chemicals
Tox21
~30 Cell & biochemical
assays
~8,000 Chemicals
Set Chemicals Assays Completion
ToxCast Phase I 293 ~600 2011
ToxCast Phase II 767 ~600 2013
ToxCast Phase III 1001 ~100 Ongoing
E1K (endocrine) 880 ~50 2013
National Center forComputational Toxicology
6
Broad Success Derived from High-Throughput Screening Approaches
Provide Mechanistic Support for Hazard ID
Group Chemicals by Similar Bioactivity and Predictive Modeling
Prioritization of Chemicals for Further Testing
Assays/Pathways
Che
mic
als
IARC Monographs 110, 112, 113
FIFRA SAP, Dec 2014
National Center forComputational Toxicology
7
Selected Criticisms of ToxCast
• You don’t include metabolism in your in vitro assays
• You don’t measure my favorite endpoint
• You don’t cover all of biological space
• In vitro assays are not normal biology
• Assay (x) in your battery did not get the right answer for my chemical
• My assay disagrees with your assay (x), so your approach is flawed
• You can’t test my favorite chemicals because of limitations in your methods (e.g., solvents, high LogP)
• Your assay descriptions to do not allow me to reproduce your results
• I get different answers when I analyze your dataUpdated from Bob K’s original list
National Center forComputational Toxicology
8
Beginning to Address Concerns for Increased Biological Coverage
Requirements:
• Whole genome• 384 well• Automatable
• Low cost
Thousands of chemicals Multiple Cell Types
X
National Center forComputational Toxicology
9
Comparing Sequencing Platforms and Developing Analysis Approach
TruSeqr2 0.74
TempO-Seqr2 0.75
Low Coverager2 0.83
Currently capable of assigning to >40 MOAs/MIEs based on transcriptional responses
MOA/MIE Analysis Pipeline
• Large scale screen of 1,000 chemicals (ToxCast I/II) in single cell type this summer
• Additional screens across multiple cell types/lines• Additional reference chemicals and genetic
perturbations (RNAi/CRISPR/cDNA)
National Center forComputational Toxicology
10
Beginning to Address Metabolic Competence
“Extracellular”Approach
“Intracellular”Approach
Chemicals metabolism in the media or buffer of cell-based and cell-free assays
Capable of metabolizing chemicals inside the cell in cell-based assays
More closely models effects of hepatic metabolism and generation of circulating
metabolites
More closely models effects of target tissue metabolism
Integrated approach to model in vivometabolic bioactivation and detoxification
-9 -8 -7 -6 -5 -40
1
2
3
4
5
L o g M e th o x y c h lo r (M )
Fo
ld I
nd
uc
tio
n
A c tive In a c tiv e E m p ty
C Y P 3 A 4 m R N A (n g )
RL
U
0 5 0 1 0 0 1 5 00
5 0 0 0 0
1 0 0 0 0 0
1 5 0 0 0 01 2 H o u rs
1 8 H o u rs
2 4 H o u rs
3 6 H o u rs
4 8 H o u rs
Collaboration with Unilever
National Center forComputational Toxicology
11
Framework for Integrating Hazard Components…
Tier 2Select In Vitro
Assays
Tier 1High-Throughput Transcriptomic
Assay
No Defined Biological Target or Pathway
Defined Biological Target or Pathway
Tier 3
Organotypic Assays and Microphysiological
Systems
Estimate Point-of-Departure Based on Likely Tissue- or Organ-level Effect without
AOP
Estimate Point-of-Departure Based on Pathway
Transcriptional Perturbation
Orthogonal confirmation
Identify Likely Tissue-, Organ-, or Organism
Effect and Susceptible Populations
In VitroAssays for other KEs
and Systems Modeling
Existing AOP No AOP
Estimate Point-of-Departure Based on AOP
Multiple Cell Types+/- Metabolic Competence
MOA/MIE Identification
-4
-3
-2
-1
0
1
2
3
-4 -3 -2 -1 0 1 2 3
Min
imum
In V
ivo
ToxR
efLo
w E
ffect
Lev
el
for R
at O
nly
(mg/
kg/d
)
Minimum In Vitro Rat Oral Equivalent Dose (mg/kg/d)
National Center forComputational Toxicology
Adding the High-Throughput Toxicokinetic Component
Rotroff et al., Tox Sci., 2010Wetmore et al., Tox Sci., 2012
Reverse Dosimetry
Oral Exposure
Plasma Concentration
In Vitro Potency Value
Oral Dose Required to Achieve Steady
State Plasma Concentrations
Equivalent to In VitroBioactivity
Human Liver Metabolism
Human Plasma Protein Binding
Population-Based IVIVE Model
Upper 95th Percentile CssAmong 100 Healthy
Individuals of Both Sexes from 20 to 50 Yrs Old
EPA ToxCast Phase I and II Chemicals • Currently evaluated ~700 ToxCast Phase I and II
chemicals• Models available through ‘“httk” R package
(https://cran.r-project.org/web/packages/httk/)
National Center forComputational Toxicology
Comparing Dosimetry Adjusted Bioactivity with Exposure
Wetmore et al., Tox Sci., 2012
Fent
in H
ydro
xide
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prop
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noxy
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sulfa
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0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000
100000
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
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l Pht
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etry
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yclo
ate
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hoxy
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hion
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xsul
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eA
traz
ine
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olan
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linPr
ochl
oraz
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ural
inN
orflu
razo
n
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000
100000
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
Tebu
pirim
fos
Trifl
umiz
ole
Tric
losa
nFo
sthi
azat
ePy
rimet
hani
lA
mitr
azH
PTE
MG
KD
iuro
nM
etho
xych
lor
Tria
sulfu
ron
Qui
ntoz
ene
Fora
msu
lfuro
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uazi
nam
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sulfu
ron
Dife
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alat
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ethy
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Dic
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ate
Ben
sulid
eD
imet
hom
orph
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ropy
latr
azin
ete
trac
yclin
e di
hydr
ate
Thia
met
hoxa
mIm
azet
hapy
rC
loth
iani
din
Dip
heny
lam
ine
Feno
xapr
op-e
thyl
Azo
xyst
robi
nO
ryza
linC
lom
azon
eSe
thox
ydim
Met
ribuz
inD
ieth
yl to
luam
ide
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000
100000
Chl
oron
ebPa
clob
utra
zol
Pyrip
roxy
fen
Mes
otrio
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ate
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ethy
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ynil
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ethe
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lor
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chlo
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lleth
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met
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neFo
rmet
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e H
Cl
Flua
zifo
p-P-
buty
lD
ibut
yl p
htha
late
imet
hyl p
htha
late
Dia
zoxo
n
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000
100000
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
Assay Bioactivity
Exposure Range
National Center forComputational Toxicology
But, Exposure Information is Lacking on Most Chemicals
Dinoseb
2-[2-(
2-Ethoxy
ethoxy
)ethoxy
]et
1,2,4,
5-Tetr
achloro
benze
ne
Perfluoro
octanes
ulfonam
ide
3-Phen
oxyben
zoic
acid
Endrin
Heptac
hlor epoxid
e, iso
mer B
Potassiu
m perfluoro
hexan
esulfo
2-Meth
yl-4,6
-dinitrophen
ol
Pentad
ecafl
uoroocta
noic ac
id a
Sulfasa
lazine
1,4-D
ichloro
benze
ne
Isopro
palin
Potassiu
m nonafluoro
-1-butan
es
Warfari
n
Perfluoro
undecan
oic ac
id
Hexam
ethyl-
p-rosa
niline c
hlori
Di-n-octy
l phthala
te
Perfluoro
heptan
oic ac
id
Perfluoro
nonanoic
acid
Benzy
l hyd
rogen
phthalate
Perfluoro
decan
oic ac
id
Fomesafe
n
Heptad
ecafl
uoroocta
nesulfo
nic
Surinab
ant
Dibutyl se
bacate
Coumarin
Tamoxif
en
Etofenpro
x
Didecyl
dimeth
yl am
monium chlo
Di(ethyle
ne glyc
ol) diben
zoate
1,2-B
enzis
othiazolin
-3-one
Benz[a
]anthrac
ene
Tris(1,
3-dich
loro-2-
propyl)
ph
Safrole
2,4-D
initrophen
ol
p,p'-DDT
Perfluoro
hexan
oic ac
id
7,12-D
imeth
ylben
z(a)an
thracen
e
Pirinixi
c acid
Naphthale
ne
Methyl
laurat
eMire
x
1,2,3-
Trichloro
benze
ne
5,5-D
iphenylh
ydan
toin
N,N-D
iethyl
anilin
e
Butaned
ioic ac
id
9-Phen
anthro
l
Benzo
[b]fluoran
thene
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000Gen. USMHE
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
O-Ethyl
O-(p-nitr
ophenyl)
phen
o,p'-DDT
1,3-D
iisopro
pylben
zene
Triphen
yl phosp
hate
Biphenyl
6-Pro
pyl-2-t
hiouracil
Diphenyle
nemeth
ane
Isoeu
genol
Dibenzo
furan
3-Buten
-2-one,
3-meth
yl-4-(
2,6
Acenap
hthylene
Acenap
hthene
4-(2-m
ethylb
utan-2-
yl)phen
ol
Diethyls
tilbes
trol (D
ES)
Octrizo
le
4-Octy
lphenol
4-(1,1
,3,3-T
etram
ethylb
utyl)ph
Carbosu
lfan
Dieldrin
Kepone (
Chlordec
one)
Tebuco
nazole
Benodan
il
4-Aminoaz
obenze
ne
Propan
ol, 1 (o
r 2)-(
2-meth
oxym
4,4'-m
ethyle
nebis(
N,N-dim
ethyl
2,4,6-
Trimeth
ylphen
ol
N-Ethyl-
3-meth
ylanilin
e
2-Hyd
roxy
-4-(octy
loxy)ben
zophe
Chlorpyri
fos
Zamife
nacin
2,6-D
imeth
ylanilin
e
2,4-D
initrotoluen
e
Ethoxyquin
2,4,5-
Trichloro
phenol
Diisobutyl
adipate
2,4,6-
Trichloro
phenol
Carbofuran
Benzo
phenone
p,p'-DDD
Fluoranthen
e
4,4'-O
xydian
iline
Proges
terone
Diphenhyd
ramine h
ydro
chlorid
e
methyl
1H-ben
zimidaz
ol-2-yl
car
2,6-D
i-tert-
butylphen
ol
Fluconaz
ole
2-(2-B
utoxyeth
oxy)et
hanol
2-meth
oxy-5-
nitroan
iline
2-Chloro
-2'-deo
xyad
enosin
e
1,5-D
iaminonap
hthalene
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000 Gen. USMHE
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
N-[(3R
)-1-az
abicy
clo[2.
2.2]oct
(2S,3S
)-N-[2
-meth
oxy-5-
(triflu
o-Tolidine
1,2-D
initroben
zene
Nitroben
zene
Predniso
ne
4-(Butan
-2-yl)
phenol
4-Meth
ylphen
ol
Phosmet
Quinoline
Volinan
serin
Cyclopam
ine
Methyl
octanoate
Butylpara
ben
4-tert
-Butyl
phenol
2,6-D
initrotoluen
e
N-Nitr
osodi-N
-butylam
ine
1,5,9-
Cyclododec
atrien
e
3,3,4,
4,5,5,
6,6,7,
7,8,8,
8-Trid
Methyle
ugenol
Methylp
araben
N-Phen
yl-1,4
-benze
nediam
ine
3,3'-D
imeth
oxyben
zidine)
2,6-D
imeth
ylphen
ol
(-)-C
otinine
4-Nitr
otoluene
Oxytet
racyc
line h
ydro
chlorid
e
Eugenol
2,4-D
i-tert-
butylphen
ol
N,N'-M
ethyle
nebis(
acryl
amide)
Candoxa
tril
p-Cres
idine
Propylp
araben
Dibutyl hex
aned
ioate
Ethylpara
ben
Tannic
acid
Resorci
nol
Dimeth
yl glutar
ate
N,N-D
imeth
ylocty
lamine
Erythro
mycin
Triethyle
ne Glyc
ol Diac
etate
Triethyl
citrat
e
Diallyl
phthalate
Dimeth
yl su
ccinate
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000Gen. USMHE
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
1-Hyd
roxy
pyrene
Azelai
c acid
di(2-et
hylhex
yl)
Tridem
orph
Anthracen
e
Triamcin
olone
Acetam
inophen
Octhilin
one
2-Ben
zylid
eneo
ctanal
Tri(eth
ylene g
lycol) b
is(2-e
th
N-Nitr
osodiphen
ylamine
Aldrin
Phorate
2,6-D
iethyla
niline
Vernolat
e
Genist
ein
5-Hep
tyldihyd
ro-2(
3H)-f
uranone
Terbuthyla
zin
Mepan
ipyrim
2-Anisi
dine
Tributyl
phosphate
Pyrene
3-Hyd
roxy
fluoren
e
Pyrimeth
amine
2-Nap
hthylamine
Bisphen
ol B
Rifampici
n
Di(2-et
hylhex
yl)ad
ipate
Simva
statin
2-tert
-Butyl
-4-meth
oxy-phen
ol
Monuron
N,N,4-
Trimeth
ylanilin
e
1,3-D
iphenylg
uanidine
Flutamide
Heptac
hlor
Benzid
ine
Caffein
e
Haloperi
dol
Lovasta
tin
Carbam
azep
ine
PK 1119
5
Chlorthal-
dimeth
yl
Butam
8-Hyd
roxy
quinoline
3-Nitr
otoluene
2-Meth
ylphen
ol
4,4'-M
ethyle
ne bis(
2-meth
ylani
Androste
nedione
Diisopro
pyl meth
ylphosp
honate
Phenolphthale
in0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
10000Gen. USMHE
Ora
l Equ
ival
ent D
ose
or E
stim
ated
Exp
osur
e(m
g/kg
/day
)
Bioactivity from Wetmore et al., Tox Sci., 2015
National Center forComputational Toxicology
15
Adding the High-Throughput Exposure Component
(Bio) Monitoring
Dataset 1
Dataset 2…
e.g., CDC NHANES study
Wambaugh et al., 2014
Predicted Exposures
…
Use
Production Volume
Inferred Exposures
Pharmacokinetic Models
Estimate Uncertainty
Calibrate models
Infe
rred
Exp
osur
e
Predicted Exposure
• Exposures estimated for >8,000 chemicals
• 4 product use categories plus production volume explain ~50% of the variance in the NHANES data
• The same five variables work for all NHANES demographic groups analyzed – stratified by age, sex, and body-mass index
• Uncertainty captured in exposure estimates
National Center forComputational Toxicology
16
Comparing Bioactivity with Exposure Predictions for Risk Context
Wetmore et al., Tox Sci., 2015
Chemicals
In Vitro Bioactivity
Exposure Predictions
With Uncertainty
National Center forComputational Toxicology
17
Adding in Uncertainty and Variability for PD and PK
Propagation of Experimental Uncertainty in High-Throughput Toxicokinetic Estimates
Propagation of Experimental Uncertainty in Models of ER Potency
Chemical Rank
ER
Mod
el S
core
Rat
io o
f Css
95th
Per
cent
ile to
Med
ian
Est
imat
e
Chemical Rank
Variability Predominates
Uncertainty Predominates
National Center forComputational Toxicology
18
Covering All the Components of a 21st Century Risk Assessment
Phys Chem
Exposure
HazardDose Response, PK, and PODs
Risk SummaryUncertainty
Variability
National Center forComputational Toxicology
Outline
• Short overview of CompTox research effort
• Availability of research data
• Potential application to prioritizing for exposure monitoring
19
National Center forComputational Toxicology
20
Regulatory Applications Require More Focus on Quality and Transparency
• Public release of Tox21 and ToxCast data on PubChem and EPA web site (raw and processed data)
• Publicly available ToxCast data analysis pipeline• Data quality flags to indicate concerns with chemical
purity and identity, noisy data, and systematic assay errors
• Tox21 and ToxCast chemical libraries have undergone analytical QC and results publicly available
• Public posting of ToxCast procedures• Chemical Procurement and QC• Data Analysis • Assay Characteristics and Performance
• External audit on ToxCast data and data analysis pipeline
• Migrating ToxCast assay annotations to OECD 211 compliant format
FLAGS:Only one conc above baseline, activeBorderline active
National Center forComputational Toxicology
21
Effort to Provide Data Through Display and Decision Support Dashboards
Enhanced Chemistry Dashboard(https://comptox.epa.gov/dashboard)
ToxCast Dashboard(https://actor.epa.gov/dashboard)
EDSP21 Dashboard(https://actor.epa.gov/edsp1)
National Center forComputational Toxicology
Dashboard Allows Chemical Specific Queries or List Retrieval
Data Currently Organized and Presented as Simple Tabs
National Center forComputational Toxicology
23
Chemical Properties Tab Builds on Chemistry Dashboard Foundation
National Center forComputational Toxicology
Data “Layers” Allow User Interaction with Underlying Models and Data
National Center forComputational Toxicology
Data “Layers” Allow User Interaction with Underlying Models and Data
National Center forComputational Toxicology
Quantitative In Vivo Toxicity Values Assembled From Multiple Sources
Sources include EPA and public sources
National Center forComputational Toxicology
Outline
• Short overview of CompTox research effort
• Availability of research data
• Potential application to prioritizing for exposure monitoring
35
National Center forComputational Toxicology
36
Integrating Different Components for Prioritization
Hazard
Dev Tox Repro Tox Cancer
Endocrine
In VivoX In VivoX In VivoX
Human Health
Estrogen AgonistX In Vitro
QSARX
Androgen AgonistX In Vitro
QSARX
Androgen AntagonistX In Vitro
QSARX
ExposureCPCat
X Present in Children’s ProductsPresent in Consumer ProductsX
Physical Chemical PropertiesX Appropriate mass range
X Exclude polymers
X Pesticide Home Use
LiteratureX Male reproduction
X Female reproduction
X Embryo or embryonic development
Prioritize