10/31/2014. The Pieces of an AOP. Moving AOP thinking forward

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1 Adverse Outcome Pathways: Designing Assays Based on AOPs and in vitro/in vivo Extrapolation Personal Care Products Council - Safety Workshop Wednesday, October 29, 2014 Renaissance Newark Airport Hotel Melvin Andersen, PhD The Hamner Institutes for Health Sciences mandersen@thehamner.org The Pieces of an AOP chemical properties molecular target cellular response tissue response organism response Molecular Initiating Event Toxicity pathway Mode of action Adverse outcome pathway Moving AOP thinking forward 1

2 Moving AOP thinking forward Developing MOA guidelines Using the MoA framework for decision making Thompson C M et al. Toxicol. Sci. 2011;119:20-40 The Author Published by Oxford University Press on behalf of the Society of Toxicology. For permissions, please journals.permissions@oxfordjournals.org. 2

3 We need to plan for utility of the AOP process Key Event - develop fit-for-purpose assays Key Event Assays that are Fit For Purpose and QIVIVE Fit for purpose assays cell-based pathway modeling Measure of Response (e.g., in vitro AC50 concentrations) Point of Departure (in vitro concentration) QIVIVE reverse dosimetry in vivo human safety estimate (mg/kg/day) Looking at the key events differently (AOP oriented) 3

4 Hamner s TT21C: Toxicity Pathways and Network Biology Program INDUSTRY TECHNOLOGY ACEA DuPont Case Studies using MOA, AOPs and Fit-For- Purpose to Organize Risk Assessments China ACADEMIC PARTNERS Fudan University China Medical University Academy of Military Medical Sciences PPARa receptor (liver responses) Bioinformatic tools DNA-damage micronuclei formation Nrf2 & Oxidative Stress AhR receptor (liver ) Computational Systems Pathway Modeling Hamner TT21C Program Estrogen receptor Uterine cell proliferation in vitro systems & High content assays Dosimetry & QIVIVE DNA Damage Pathway Key Events in the AOP Cell Based Adversity Adverse Outcomes Homeostasis Adaptation DNA Damage DNA Repair Micronuclei (mutation) p53 activation Gene transcription Cell cycle Cancer Heritable Mutations arrest 4

5 Cell-based PD modeling Stress Response Pathways p53-mdm2 What should we measure? Whole genome transcriptomics Comparison of dose-response across endpoints BMDL ETP QUE MMS ph2ax p-p53 (s15) Tp WIP MDM p Cell Cycle Apoptosis p-p53 (s46) HCI-Micronucleus Gene Transcription* BMDL 95% lower confidence interval for Benchmark Dose statistical lower confidence interval * Associated enriched categories are Immune Response, Development and Cytoskeleton Remodeling for ETP, QUE, MMS Looking at DNA repair p-h2ax p53 BP1 Overlay Control 1 mm ETP 5

6 Cell proliferation Interpreting DNA damage dose-response data NOEL = 0.5 ng/ml Total DNA repair centers NOEL = 5 ng/ml Unresolved DNA repair centers at 24 hrs Developing a computational systems biology model for dose-response UV DSBs Cell-based Adversity ATR ATM Adaptation Repair foci formation & Micronuclei (mutation) Chk1 Chk2 Homeostasis resolution Apoptosis DNA repair Cycle arrest p53 genes p53 p53 ATM H2AX BRCA1 Non-transcriptional Modulation of Stress p53 Transcriptional Response to Excess Stressor PPARa Pathway - Key Events in the AOP Adaptation Cell-based Adversity Adverse Outcomes Sub-Threshold Doses Binding to PPARa Increased levels of CYPs Cell proliferation Liver Toxicity Liver Weight Liver cancer 6

7 The model- primary hepatocytes with PPARa agonist Patterns of Gene Expression differ in rat and Human: in vitro vs. in vivo PPARα mediated response Humans have only the metabolic responses not the proliferative priming response 7

8 Cell proliferation Model all-or-none cellular process for PPARa mediated pathway activation through mitogen-activated protein kinase cascades Stimulus (GW7647) MKKK MKKK a P MKK MKK P MKK P MAPK MAPK P MAPK P P Transcription Factors & Phenotype Lower doses affect centrilobular region with altered metabolism Higher doses affect periportal region with proliferative profile Endocrine Disruption Estrogen Pathway Alterations Key Events in the AOP Sub-Threshold Doses Adaptation Binding to ER66 (ERa) Induction of Some genes Cell-Based Adversity Uterine cell proliferation Adverse Outcomes Altered reproduction Altered Cycling Endometrial cancer Why uterine proliferation - EDSP Tier 1 Tests Amphibian Metamorphosis (Frog) Androgen Receptor Binding (Rat Prostate) Hershberger (Rat) Male Pubertal (Rat) Fish Short-Term Reproduction Female Pubertal (Rat) Uterotrophic (Rat) Aromatase (Human recombinant protein) Steroidogenesis (H295R cell line) Estrogen Receptor Binding (Rat cytosol, human recombinant ESR1) ESR1 Transcriptional Activation (HeLa cell line) 8

9 Proliferation (Fold-change) IK HEEC [EE], M Estrogenic Signaling requires multiple receptors Make sure the Cells Used function properly Receptor expression Transcriptional activation Phenotypic outcome - enzyme induction - proliferation Understanding Dose Responses for Proliferation with receptor time courses after E2 treatment Adaptation Cell-Based Adversity Sub-Threshold Doses Binding to ER66 Induction of Some genes Interaction of groups of ER receptors to cause uterine cell proliferation 9

10 The other piece Fit for purpose assays cell-based pathway modeling Measure of Response (in vitro concentration) Point of Departure (in vitro concentration) QIVIVE Reverse Dosimetry in vivo human safety estimate (mg/kg/day) The Traditional Role of Pharmacokinetics: Relating Animal Doses to Equivalent Human Exposures Margin of safety Chemical concentrations in human blood from biomonitoring studies Chemical concentrations in animal blood in toxicity studies Pharmacokinetic Modeling Pharmacokinetic modeling Human exposures (Chemical concentrations in environment) Animal exposures (Administered doses in toxicity studies) Traditional risk assessment In the Future: Pharmacokinetics will relate the Concentration in an in vitro Assay to the Equivalent in vivo Human Exposure QIVIVE* In Vitro Toxicity Assays AC 50 or Data on Concentration- Response Estimate of Human Equivalent Dose * Quantitative In Vitro to In Vivo Extrapolation 10

11 Ln Conc (um) Time (min) 1 um initial 10 um initial Ln Conc (um) Time (min) 1 um initial 10 um initial Considerations for QIVIVE Pharmacokinetic factors that affect in vivo toxicity but are not appropriately reflected in in vitro toxicity tests: - Bioavailability - Transport - Protein binding - Clearance processes - Metabolic; Renal; Biliary; Exhalation QIVIVE and Reverse Dosimetry for In Vitro Toxicity Assays (USEPA ToxCast Hamner Collaboration) Nifedipine Hepatocellular Clearance Reverse Dosimetry Equivalent Exposure Plasma Protein Binding Prediction of in vivo clearance Estimated Renal Clearance Concentration from in vitro assay In Vitro Assays for Characterizing Steady-State Pharmacokinetics Nifedipine Human Add Chemical Remove Aliquots Analytical Hepatic Clearance Hepatocytes (1 and 10 um) at 15, 30, 60, 120 Chemistry (10 donor pool) min Plasma Protein Binding Human Add Chemical Equilibrium Analytical Plasma (1 and 10 um) Dialysis Chemistry (6 donor pool) 11

12 Calculation of Steady- State Blood Concentration [Conc] SS = DoseRate * BodyWeight Cl Extrinsic Cl Hepatic Cl Renal F U, BF Portal, M Hepatic F U, GFR *Assuming 100% GI absorption. BF: blood flow Cl: clearance Fu: fraction unbound in blood GFR: glomerular fitlration rate M: metabolism SS: steady-state Comparison of IVIVE results with estimates based on in vivo PK (Wetmore et al. 2012) Chemical In Vivo Derived Css (µm) IVIVE Css (um) 2,4-dichlorophenoxyacetic acid Bisphenol-A < 0.13 d 0.06 Cacodylic acid Carbaryl Fenitrothion Lindane Oxytetracycline dihydrate Parathion Perfluorooctanoic acid 20,120 g 0.4 g Picloram Thiabendazole Triclosan Application: Defining Dosimetry in ToxCast High Throughput Toxicity Screens Toxicokinetic Parameters 398 In Vitro ToxCast Assays Plasma Protein Binding Metabolic Stability ToxCast AC 50 Values Hamner In Vitro-to-In Vivo Extrapolation Predicted Assay Oral Equivalent Doses Upper Level of Human Exposure Chemicals with Potential to Perturb Cellular Pathways at Relevant Human Exposure Levels Estimated Target Tissue Bioactivity Concentration Provided by ToxCast Data Generated In Vitro Data Obtained from Registration Documents Computational Modeling 12

13 mg/kg/day Pyrithiobac-sodium AC 50 Concentration (µm) Pyrithiobac-sodium Results From Reverse Dosimetry Analysis: The Same EC50 Does Not Imply the Same Exposure! Est Oral Minimum EC50 Equivalent Chemical ToxCast Endpoint or LEL (um) (mg/kg/day) Acetamiprid BSK_BE3C_uPAR Atrazine BSK_KF3CT_IP Bromacil BSK_BE3C_IP Forchlorfenuron BSK_BE3C_uPAR Metribuzin BSK_hDFCGF_MMP Isoxaflutole BSK_hDFCGF_EGFR Dicrotophos BSK_hDFCGF_PAI Clothianidin BSK_hDFCGF_EGFR Diazoxon BSK_KF3CT_IP Oxytetracycline BSK_BE3C_IL1a ,4-D BSK_BE3C_IL1a Similar LEL Values (in vitro potency) Different Oral Equivalents (in vivo potency) This Simple Implementation of IVIVE for HTS shows that Kinetics is Crucial (Rotroff et al. 2010) Pyrithiobac-sodium Triclosan Greater than 4 orders of magnitude difference in potencies in vivo Triclosan Pyrithiobac-sodium Emamectin Benzoate Buprofezin Pyraclostrobin Etoxazole Parathion Isoxaben Pryrithiobac-sodium Bentazone 2,4-D Propetamphos Atrazine Bromacil Fenoxycarb Rotenone Forchlorfenuron Methyl Parathion Cyprodinil Isoxaflutole Acetamiprid Triclosan Zoxamide MGK Diuron Bensulide Oxytetracycline DH Dicrotophos Thiazopyr Triadimefon Metribuzin Fenamiphos Clothianidin Bisphenol-A Alachlor Acetochlor Diazoxon By themselves, in vitro assay effect concentrations are quantitatively meaningless for risk assessment Emamectin Benzoate Buprofezin Pyraclostrobin Etoxazole Parathion Isoxaben Pryrithiobac-sodium Bentazone 2,4-D Propetamphos Atrazine Bromacil Fenoxycarb Rotenone Forchlorfenuron Methyl Parathion Cyprodinil Isoxaflutole Acetamiprid Triclosan Zoxamide MGK Diuron Bensulide Oxytetracycline DH Dicrotophos Thiazopyr Triadimefon Metribuzin Fenamiphos Clothianidin Bisphenol-A Alachlor Acetochlor Diazoxon Need tools to create generic Physiologically Based Pharmacokinetic Models for more diverse exposures 13

14 In Vitro Metabolism for QIVIVE (Yoon et al. 2012) Key data needs for metabolism in the PBPK model in vitro incubation: measurement of rates of metabolism Identification of key metabolism pathways in vitro kinetic model for metabolism in vitro enzyme kinetic parameters in vitro to in vivo extrapolation of metabolism parameters Incorporation of the scaled in vivo metabolism parameters in the PBPK model Getting from AOPs to Safety Assessment & Predictive Toxicology AOP framework provides discipline in organizing knowledge about adverse responses to chemicals AOP narratives can guide development of fit-for-purpose cell based pathway assays and their regulatory use Continuing refinements of QIVIVE and computational systems biology pathway modeling tools will enhance the relevance of these fit-for-purpose in vitro assays results for in vitro only safety assessments AOPs The Promise New Directions in Safety Assessments from a 43 year perspective Mode-of-Action/Toxicity Pathway/Key Event /Adverse Outcome Pathway process is now possible based on deep biological understanding and opportunities in systems toxicology Focus on key events with assays fit for purpose i.e., outputs that will be adequate for safety/risk assessment 14

15 Some Acknowledgements Hamner: Rebecca Clewell Bin Sun Sudin Bhattacharya Patrick McMullen Sudin Bhattacharya Qiang Zhang Ed LeCluyse Sponsors: Unilever TT21C Consortium ACC-LRI Harvey Clewell Barbara Wetmore Miyoung Yoon Jenny Pedersen 15