toxcast and tox21: high throughput screening for hazard ... · high throughput screening 101 (hts)...

ToxCast and Tox21: High Throughput Screening for Hazard & Risk of Environmental Chemicalsfor Hazard & Risk of Environmental Chemicals

David Dix

Office of Research and DevelopmentNational Center for Computational Toxicology

This work was reviewed by EPA and approved for presentation but does not necessarily reflect official Agency policy.

NLSOT, 07oct2010

Future of Toxicity Testing and Ultimately, Environmental Risk Assessments

Science, February 2008

EPA strategy, March 2009

CTRP 2nd gen plan, Sept 2009

Science, August 21, 2009, g ,

Office of Research and DevelopmentComputational Toxicology Research Program 1

Grand Challenge for Computational Toxicology:P di ti H T i itPredicting Human Toxicity

Complex Cellular and

Tissues

Biochemical HTS

Cellular and HCS HTS

ToxRefDB

ToxicityCellChanges

CellularNetworks

Cellular SystemsTissueDose

HTS

Exposure MolecularTargets Changes NetworksDose

MolecularPathways

p Targets

Cell-Based

HTSModel

Organism MTS

Office of Research and DevelopmentComputational Toxicology Research Program

Virtual Tissues2

Too Many Chemicals Too Little Data (%)609912

40

50

60

1000

10000

9912

20

30

40

100

1000

0

10

20

1

10

0

Acute Cancer GentoxDev Tox Repro Tox

IRIS TRI PesticidesInerts CCL 1 & 2 HPV


MPV

3

High Throughput Screening 101 (HTS)(HTS)

96-, 384-, 1536 Well Plates

Chemical Exposure

96 , 38 , 536 e atesRobotic Platform

Cell Population

Pathway

Cell Population

Target Biology (e.g., Estrogen Receptor)

Office of Research and DevelopmentComputational Toxicology Research Program4

HTS: High Throughput Screening4

HTS in Drug Development

Id tifMake

difi tiHTS tests

100 000C tIdentify target,

pathway, or cellular h t

modifications to most active chemicals to

make suitable f i i

Test in animals for

safety, effectiveness

Test in humans for

safety, effectiveness

>100,000 chemicals with

no known activity

Create testing system (aka,

“ ”)phenotype for in vivo testing

effectiveness effectivenessfor effect on

target“assay”)


HTS i T i lHTS in Toxicology

Obt i

Test prioritized chemicals in

animals Chemicals Id tifObtain or create testing

systems (“ ”)

HTS tests chemicals for effect

on assays

C e ca swith known

or suspected

toxicity/

Identify toxicity

pathways, cellular

h t

Computational analysis

&Synthesis

(“assays”)on assays yactivityphenotypesof HTS resultsCategorize as

inactive subject to further testing


ToxCast and Tox21 High Throughput Screening of Chemical Bioactivity

• Addresses chemical screening and prioritization• Addresses chemical screening and prioritization needs for chemicals regulated by EPA

• Comprehensive use of HTS technologies to generate biological fingerprints and predictive signatures

• Committed to stakeholder involvement and transparencyp y• Communities of Practice- Chemical Prioritization;

Exposure• Release of all data upon peer review publication


• Release of all data upon peer review publication7

G l f T C t d T 21Goals of ToxCast and Tox21• Identify toxicity pathwaysy y p y

• Obtain HTS assays for pathways

• Screen a large chemical library

• Initially link HTS results to adverse effects- Toxicity signatures

• Ultimately identify points of departure from HTS data - Toxicity pathways


Tox21 Screening Throughputg g p

8 rows x 12 columns 88 test samples

16 rows x 32 columns 352 test samples

96-well plate 32 rows x 48 columns 1,408 test samples

384-well plate4 x 96-well plates

1536-well plate16 x 96-well platesIf @ 100 microtiter plates per day:

Time to screen 1 MM samples

samples§/day(wells/day)

Plate format Time to screen 1 MM samples

samples§/day(wells/day)

Plate format


§ wells remaining after subtraction of control wells; NCGC uses left 4 columns of a 1536-well plate for control wells7 days140,800 (153,600)1,536-well

4 weeks35,200 (38,400)384-well

4 months8,800 (9,600)96-well

7 days140,800 (153,600)1,536-well

4 weeks35,200 (38,400)384-well

4 months8,800 (9,600)96-well

9

Comparison of VolumesComparison of Volumes

TotalV l

ppfor for Screening Compounds Screening Compounds in 7 Concentrationsin 7 Concentrations

Volume

96-well plate: 100 l x 7 pts = 700 l




• 1536 well HTS• 10,000 chemicals• 25 assays per year


ToxCast Phase I and II, Tox21

ToxCastPhase I

ToxCastPhase II Tox21

Number of Chemicals

Actives 272 120 700

Inerts 24 100 1000

Antimicrobials 33 100 500Antimicrobials 33 100 500

HPV 35 170 1300

MPV 7 60 1500

Green 4 60 500

PCCL 73 150 500

Pharmaceuticals 0 100 2500Consumer Products /Food additives 0 0 1500

Total 309 ~700 ~10000


ToxCast HTS AssaysCellular Assays

~500 Total Endpoints

• Cell lines– HepG2 human hepatoblastoma– A549 human lung carcinoma– HEK 293 human embryonic kidney

• Protein familiesGPCR

Biochemical Assays

y y

• Primary cells– Human endothelial cells– Human monocytes

H k ti t

– GPCR– NR– Kinase– Phosphatase

– Human keratinocytes– Human fibroblasts– Human proximal tubule kidney cells– Human small airway epithelial cells– Rat hepatocytes

– Protease– Other enzyme– Ion channel– Transporter p y

– Mouse embryonic stem cells (Sid Hunter)

• Biotransformation competent cells– Primary rat hepatocytes

• Assay formats– Radioligand binding

Enzyme activity – Primary human hepatocytes

• Assay formats– Cytotoxicity

Reporter gene

– Enzyme activity– Co-activator recruitment

Primarily Human / RatE ti Z b fi h d l t (St h i P dill )


13

– Reporter gene – Gene expression– Biomarker production– High-content imaging for cellular phenotype

Exception: Zebrafish development (Stephanie Padilla)

The ToxCast In Vitro Data SetAssays

Many hits – median value=50Chemicals

Many hits – median value=50

Fewer in cell-free HTS (Novascreen, red)

Many hits are at or near top of tested concentration range

A few are in nanomolar rangeA few are in nanomolar range


ToxCast Data Analysis

Assays

ls

AC50

Emax

Che

mic

al

AC50828 Assay-Chemical Pairshad AC50s of less than 1µM

: Assay-Chemical Hit

500 Assays X 320 Chemicals X {5-18} Concentrations X{1-3} Replicates X {1-3} Time Points ≈3.2 Million Data Points

3 2 1 04…

Concentration

Office of Research and DevelopmentComputational Toxicology Research Program 15Emax: Maximal efficacy/response/activity

AC50: Concentration whereby 50% of maximal response was achievedConc (uM): Micromolar concentrations of chemical

Digitizing Legacy in Vivo Data in ToxRefDB

Chronic/CancerMultigenationMultigenationDevelopmental

mic

als

Che

m

Martin et al 2009a,bKnudsen et al 2009


SOT 2010

30 years and more than $2B worth of data 16

Predicting Toxicity and Disease from HTS Data

ToxRefDB ToxCast Human Disease

from HTS Data


ToxCast: Multiple Assays and Technologies per Target


ToxCast: Multiple Targets per Pathway

Biologically Multiplexed Activity Profiling (BioMAP)

Multiplex Transcription Reporter Assay

Cell-free HTS Assays

Cell-based HTS Assays

High Content Cell Imaging Assays


19

Building Toxicity Signatures forR t Li Hi t th lRat Liver Histopathologyfrom Chronic Bioassays

37

21

No PathologyProliferative LesionsPre-neoplastic Lesions

68

Neoplastic Lesions

N = 248 Chemicals in ToxRefDB


ToxCast Identied Genes Associated with Progression of Rat Liver Disease

132 60 21

Any Lesion Pre-Neoplastic Neoplastic

Office of Research and DevelopmentComputational Toxicology Research Program 21Liver Disease Progression

Judson et al, EHP (2010)

Toxicity Pathways

Receptors / Enzymes / etc.Chemical

p yDirect Molecular Interaction

Pathway Regulation / Genomics

Cellular Processes

Tissue / Organ / Organism Tox EndpointTissue / Organ / Organism Tox Endpoint


Predictive Signatures from ToxCast for Chronic, Developmental and Reproductive Toxicityp p y

• Chronic/Cancer endpoints from rat, mouse and dog

• Developmental endpoints from rat and rabbit

• Reproductive endpoints from rat


ToxPi: Prioritizing Chemicals for P t ti l E d i A ti itPotential Endocrine Activity

Prioritization Index = ToxPi = f(HTS assays + Chemical properties + Pathways)( y p p y )

Bisphenol A TebuthiuronER

TROther XME/ADME

AROther NR

Ingenuity pathways

KEGG

LogP_TPSA

Predicted CaCO-2

Disease classes

KEGG pathways


Reif et al, EHP, 2010

ToxPi Ranking of ChemicalsHPTE

Linuron

ToxP

i sco

re

Pyrimethanil

als

sorte

d by

Tebuthiuron309

Che

mic

a

ERTROther

XME/ADME3

hi h

Ingenuity path

AR

KEGG path

LogP_TPSA

CaCO-2

Disease classes

Other NR


ToxScore

ToxPi

highestlowest

Reif et al, 2010

Expanding the ToxPi Approach for Prioritization of Toxicity Testing Based on ToxCast Chemical ProfilingTesting Based on ToxCast Chemical Profiling

CANCERDEVELP th

Identify in vitro assays, targets, genes and In vitro assays

Pathwaysassociated with CANCER in vivo endpoints g , g

pathways associated with multiple sectors of in vivo toxicity

In vitro assaysassociated with CANCER in vivo endpoints

of in vivo toxicity.

REPRO SYSTEMICOffice of Research and DevelopmentComputational Toxicology Research Program 26

REPRO SYSTEMIC

ToxPi Scores for Antimicrobial Pesticide Actives

One of the methods be developed to use ToxCast data for classifying and prioritizing antimicrobials and inerts.


27

Future ToxPi (Toxicological Prioritization Index)

ToxPi = f(Exposure + Chemical properties + In vitro assays + Pathways)

Incorporate additional components (slices) from other domains:( )

- Exposure- Chemical properties- QSAR


Range of in vitro AC50 l t d t s

TriclosanPyrithiobac-sodium

values converted to human in vivo daily dose

kine

tics

g/da

y)

oxic

ok

log

(mg/

kg

rse

To

Margin

Rev

e

xazo

lem

ectin

ofez

inha

late

trobi

nat

hion

xabe

nod

ium

azon

em

phos

2,4-

Det

hrin

MG

Kaz

ine

omac

ilxy

carb

nuro

nat

hion

clos

anen

one

rodi

nil

fluto

lem

iprid

amid

eDi

uron

sulid

e oz

olin

ne D

Hop

hos

buzi

nm

efon

azop

yrip

hos

anid

inen

ol-A

achl

oroc

hlor

zoxo

nor

vos

-oxo

n

Estimated Exposure


Etox

Emam

Bupr

oDi

buty

l pht

hPy

racl

ost

Para

Isox

Pryr

ithio

bac-

soBe

nta

Prop

etam

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Feno

xFo

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ethy

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teCy

prIs

oxaf

Acet

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tetra

cycl

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sphe Al

aAc

eto

Diaz

Dich

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lorp

yrip

hos-

Rotroff, et al. Tox.Sci. In Press

29

Systems Approaches to Modeling Toxicity:From Pathways to Virtual Tissues

chemicals pathways networks cell states tissue function

Moving beyond empirical models, to

Identify Key Targets and Pathways For Prioritization

Quantitative Dose-Response

Models Next Generation

Risk assessments

multi-scale models of complex biological systems: vLiver,

vEmbryo…


30SOT 2010

vEmbryo…

HIGH THROUGHPUT SCREENING and CHARACTERIZATION OF HAZARD & RISKCHARACTERIZATION OF HAZARD & RISK

Tissues

Cellular SystemsToxicityCell

ChangesMolecular

TargetsCellularNetworks

TissueDose

Molecular

Exposure

Pathways

IN VITRO: concentration responseIN VITRO: concentration response

Animal IN VIVO: exposure dose response

Human IN SILICO: exposure dose response


SOT 2010

Animal IN VIVO: exposure dose response

ToxCast Phase I Publications & Data Release


32SOT 2010http://epa.gov/ncct/toxcast/

Acknowledgements

Tom KnudsenImran ShahJ h W b h

Robert Kavlock Keith HouckMatt Martin

Ray TiceChris AustinJohn WambaughMatt Martin

Richard JudsonAnn RichardDavid Reif

Chris Austin

Daniel RotroffWoody SetzerHolly MortensonA d B

http://www.epa.gov/ncct/

Andrew Beam


SOT 2010

toxcast and tox21: high throughput screening for hazard ... · high throughput screening 101 (hts)...

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