Tox21 and ToxCast programs for using in vitro HTS data

71 Pages·2012·11.06 MB·English

Tox21 & ToxCast Programs for using in
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A Chemical Perspective
Ann M. Richard
U.S. EPA, National Center for Computational Toxicology
Cosmetics Inventory Review Meeting, Wash DC
June 11, 2012
Office of Research and Development
National Center for Computational Toxicology This work was reviewed by EPA and approved for presentation
but does not necessarily reflect official Agency policy.
Overview
EEPPAA’ss TTooxxCCaasstt PPrrooggrraamm
Navigating data domains
MMOOAA QQSSAARR
Expanding ToxCast’s chemical landscape
TTox2211 PProjjectt
New cheminformatics approaches
Tox21-COSMOS structure overlaps
OfficeofResearchandDevelopment
NationalCenterforComputationalToxicology
ToxCast Project
PPhhaassee II
++ PPhhaassee ++IIII ee11kk
(309)
(1060e1)k test(in1g 860)
2007 2009 2011 begins 2013
EEPPAA NNCCCCTT llaunchhes 22000088 PPhhase II ddatta 22001100 22001122
Phase II &
ToxCast results Phase II
Full Phase I data e1k data
testing begins
publication/release publication/
release
NAS Repport released
AACCTToRR llaunchhedd
ToxRefDB web access
w/in ACToR
OfficeofResearchandDevelopment
NationalCenterforComputationalToxicology
Problem Statement
Too many chemicals to test with standard
animal-based methods
–Cost, time, animal welfare
Need for better mechanistic data
-
What is human relevance
-
What is the Mode of Action (MOA)?
- What is the Adverse Outcome Pathway (AOP)?
OfficeofResearchandDevelopment
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NationalCenterforComputationalToxicology
R. Judson, SOT Presentation, March 2012
ToxCast Goals
• Identify targets or pathways linked to toxicity
–CChheemmiiccaallss ppeerrttuurrbbiinngg tthheessee ccaann lleeaadd ttoo aaddvveerrssee eevveennttss
• Develop assays for these targets or pathways
––AAssssaayyss pprroobbee “MMoolleeccuullaarr IInniittiiaattiinngg EEvveennttss” oorr “KKeeyy EEvveennttss” [[MMIIEE // KKEE]]
• Develop predictive models: in vitro → in vivo
–“TTooxxiicciittyy SSiiggnnaattuurree”
• Use signatures:
–Prioritize chemicals for targgeted testingg ((“Too Manyy Chemicals” pproblem))
–Suggest / distinguish possible AOP / MOA for chemicals
OfficeofResearchandDevelopment
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NationalCenterforComputationalToxicology
R. Judson, SOT Presentation, March 2012
Toxicity Signature Generation
In Vitro Data
Predictive Models – “Signatures”
In Vivo Data
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NationalCenterforComputationalToxicology
R. Judson, SOT Presentation, March 2012
ToxCast Assays
CCellllullar AAssays
• Cell lines
Biochemical Assays
– HepG2 human hepatoblastoma
• Protein families – A549 human lung carcinoma
– HEK 293 human embryyonic kidneyy
– GGPPCCRR
– NR
• Primary cells
– Kinase
– Human endothelial cells
– Phosphatase – Human monocytes
~660000 TToottaall
– Protease – HHuman kkerattiinocyttes
Endpoints – Human fibroblasts
– Other enzyme
– Human proximal tubule kidney cells
– Ion channel
– Human small airway epithelial cells
– Transporter
– Rat heppatocyytes
– Mouse embryonic stem cells (Sid Hunter)
• Assay formats
• Biotransformation competent cells
– Radioligand binding
– Primary rat hepatocytes
– EEnnzzyymmee aaccttiivviittyy
– Primary human hepatocytes
– Co-activator recruitment
• Assay formats
PPrriimmaarriillyy HHuummaann // RRooddeenntt
– Cytotoxicity
EEEExxxxcccceeeeppppttttiiiioooonnnn:::: ZZZZeeeebbbbrrrraaaaffffiiiisssshhhh ddddeeeevvvveeeellllooooppppmmmmeeeennnntttt ((((SSSS.. PPPPaaaaddddiiiillllllllaaaa))))
– RReeppoorrtteerr ggeennee
– Gene expression
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OfficeofResearchandDevelopment – Biomarker production
NationalCenterforComputationalToxicology
– High-content imaging for cellular phenotype
ToxCast Phase I:Published Models
 Predictive models: endpoints
• liver tumors: Judson et al. 2010, Env Hlth Persp 118: 485-492
• hepatocarcinogenesis: Shah et al. 2011, PLoS One 6(2): e14584
• rat fertility: Martin et al. 2011, Biol Reprod 85: 327-339
• rraatt-rraabbbbiitt pprreennaattaall ddeevvttooxx:: SSiippeess eett aall. 22001111, TTooxxiiccooll SSccii 112244:: 110099-112277
• zebrafish vs ToxRefDB: Sipes et al. 2011, Birth Defects Res C 93: 256-267
 PPreddiicttiive moddells: patthhways
• endocrine disruption: Reif et al. 2010, Env Hlth Persp 118: 1714-1720
• microdosimetryy: Wambauggh and Shah 2010, PLoS Comp Biol 6: e1000756
• mESC differentiation: Chandler et al. 2011, PLoS One 6(6): e18540
• HTP risk assessment: Judson et al. 2011, Chem Res Toxicol 24: 451-462
• angiogenesis: Kleinstreuer et al. 2011, Env Hlth Persp 119: 1596-1603
OfficeofResearchandDevelopment
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NationalCenterforComputationalToxicology
R. Judson, SOT Presentation, March 2012
Developmental Rat 

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Assays
Rat Endpoints
OfficeofResearchandDevelopment
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SSiippeess eett aall.. 22001111,, TTooxxiiccooll SSccii 112244:: 110099--112277
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Understanding Success and Failure
• Why in vitro to in vivo can work:
–Chemicals cause effects through direct molecular interactions
that we can measure with in vitro assays
• Whyy in vitro to in vivo does not alwayys work:
• Pharmacokinetics issues: biotransformation, clearance (FP, FN)
• Assay issues: don’t have all the right assays (FN)
• Tissue issues: mayy need multi-tissue siggnalingg networks ((FN))
Systems
• Statistical power issues: need enough chemicals acting through a
Models
given MOA to be able to build and test model (FN)
• Compensation: system may adapt to initial insult (FP)
• In vitro assays are not perfect! (FP, FN)
• In vivo rodent data are not perfect! (FP, FN)
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NationalCenterforComputationalToxicology
RR.. JJuuddssoonn,, SSOOTT PPrreesseennttaattiioonn,, MMaarrcchh 22001122