The Tox21 Community

1. The Tox21 Program Christopher P. Austin, M.D.Director, NIH Chemical Genomics CenterThe Future of Chemical Toxicity Testing in the U.S.: Creating a Roadmap to Implement the NRC’s Vision and StrategyJune 21, 2010

2. The Tox21 Community has become…. Tox21

3. The Tox21 Community Tox21

4. Interagency Coordination on Biomolecular Screening • Scientific collaboration began 2005 (NTP-NCGC) – 2006 (NTP-NCGC-EPA) • Memorandum of Understanding on “High-Throughput Screening, Toxicity Pathway Profiling and Biological Interpretation of Findings” (http://ntp.niehs.nih.gov/go/28213) • Signed February 14, 2008 by: • NIH/NIEHS/NTP by Dr. S. Wilson • NIH/NHGRI by Dr. F. Collins • EPA/ORD by Dr. G. Gray • Points of Contact • EPA - Bob Kavlock (Director, National Center for Computational Toxicology) • NCGC - Chris Austin (Director) • NTP - Ray Tice (Chief, NTP Biomolecular Screening Branch) • Public status made available through monthly meetings of the EPA CPCP (Chemical Prioritization Community of Practice) • Leverage • Pools resources for common goal • Overcomes the resource limitations of a single agency • Builds on existing expertise • Avoids the need to create a new administrative and support structure

5. The Tox21 Community

6. Tox21 activity matrix Rodent in vivo Human in vivo Rodent in vitro Human in vitro Historical EPA and NTP data Approved drug data Tox21 Tox21

7. Leadership: meets every 2 wks B. Kavlock (EPA), R. Tice (NTP), C. Austin (NCGC) Working Groups: chairs meet togetherevery 4 wks Compounds, Assays, Informatics, Targeted Testing Co-leads from each agency Community: meets every 3 months Larger group of interested parties from 3 agencies Oversight: component Scientific Advisory Boards Reports at least once/yr Tox21: Organization

8. All have been evaluated in one or more toxicological tests NTP 1408 (1353 unique compounds) 1206 with NTP test data, 147 ICCVAM reference substances MW = 32-1168, calculated log p = -3 to 13.2 EPA: 1462 (1384 unique compounds) MW = 58-516, calculated log p = -2.8 to 8.2 ~400 compound overlap The Current Tox21 Compound Library NTP compounds

9. Proof of Principle Toxicology qHTS

10. Unsupervised clustering in combination with Dunn’s cluster validity index is a robust method for identifying mechanisms of action without requiring a priori knowledge about mechanisms of toxicity.

11. Full Tox21 Chemical Library: Fall 2010 • Sources include NTP, EPA HPV, CCL, OPPIN, OW, Inerts, ToxCast, DSSTox, EU Carcinogenomics, Pharmaceuticals, others

12. Environmental Industrial/Tox Drugs Environmental Industrial/Tox Drugs Food Use Tox21 IDs ToxCast Phase I Tox21 ToxCast Phase II >50 NCCT/EPA NIEHS/NTP NIH/NCGC # Assays >500 # Chemicals 309 ~10,000 ~1000 NIH/NCGC NIEHS/NTP NCCT/EPA Tox21_2_###### Tox21_3_###### Tox21_1_######

13. NIH Chemical Genomics Center • 75 scientists: biology, chemistry, informatics, robotics • >100 collaborations with investigators worldwide • Chemical genomics: biological profiles of chemical activity • Chemical probes of novel targets, rare/neglected diseases

14. NCGC Screening System 1:BSL1/Kalypsys

15. HTS “LTS” “MTS” 10’s/day 1000’s/day 10,000’s/day 100,000’s/day Throughput Molecular mechanism Immediate organismal relevance

16. HTS as done for drug discovery is not suitable for toxicity testing High false positive rate: up to 90% High false negative rate: up to 70% Prior probability of activity low Cannot reliably “bank” or computationally synthesize results Purpose is to generate a few leads for subsequent chemical optimization

17. Quantitative High-Throughput Screening (qHTS) Conventional HTS done at single concentration typically 10 uM qHTS tests all compounds at 15 concentrations Range = 5nM – 92uM Assay volumes 2-6 uL in 1536-well plate format Concentration-response curve generated for each compound from primary screen Produces robust activity profiles of all compounds Dramatically reduced FP and FN Throughput >200,000 concentration-response profiles (2M wells) per week Entire Tox21 collection is tested at 15 concs in single day

18. General toxicity Cytotoxicity assays Cell viability assay (measures ATP) Apoptosis assays Caspase assays (measure activity of Caspase 3/7, 8, 9) Membrane integrity assay LDH release Protease release Mitochondrial Toxicity assay Mitochondrial membrane potential Gene tox assays Micronucleus DNA repair Tox21 assays screened at NCGC to date • “Tox Pathways” • CREB • ER stress • HRE/Hypoxia • NFkB • P53 • ARE • HSE • Targets • Nuclear receptor assays: AR, AhR, ER, FXR, GR, LXR, PPARδ, PPARγ, PXR, RXR, TRβ, VDR, ROR • hERG channel • Inter-individual variation • 87 HapMap lines

19. Rapidly access (inhouse) biological profiles of chemical series Browse via interactive heatmap that provides details of assay response Cluster heatmap by assay response and chemical similarity

20. Approaches for Identifying Key Toxicity Pathways • - Toxicogenomic data • - Human disease - genetic associations • - The Pathway Universe • - Contract Research Organizations

21. Not all in vitro assays are suitable for HTS and not all substances can be tested in vitro (volatiles, solvent requirement, practical concentration limitation) Responses are for the most part limited to cell-autonomous effects of parent compound Exposure (route, extent), metabolism Genetic heterogeneity relating to differences in sensitivity (A gene is not a pathway, a pathway is not a cell, a cell is not an organ, an organ is not an animal……) Limitations

22. View all results with skepticism“All results are artifacts until proven otherwise” Confirm results in other assays of same phenomenon and/or lower-throughput more physiological systems Test same pathway/readout in multiple different assays/approaches Move from cell lines to primary cells Incorporate metabolism (e.g., co-culture, S9) Determine responses in cells from differing genetic backgrounds Ways to address these limitations

23. Determine which cell types (human vs rodent cell lines, primary cells, stem cell-derived cells, etc.) are most useful for HTS Develop comprehensive battery of pathway and phenotypic assays for testing Incorporate metabolism and genetic heterogeneity Secondary assays to evaluate compounds ID’ed in HTS (e.g., in vitro 3D organ models, C. elegans, zebrafish?) Obtain existing in vitro, experimental animal, and human data on compounds from industry Developing cross-assay meta-analysis informatics algorithms/browsers that enable identification of correlations among the many in vitro assays and in vivo readouts Validate resulting testing strategies for reliability and relevance, develop strategies for incorporation into regulatory decision-making Needs

24. Prediction is very difficult, especially if it's about the future. - Niels Bohr

25. Contact Information Chris Austin, NCGC: austinc@mail.nih.gov Ray Tice, NTP: tice@niehs.nih.gov Bob Kavlock, EPA: kavlock.robert@epamail.epa.gov