In Vitro In Vivo Extrapolation for High-Throughput Prioritization - PowerPoint PPT Presentation

In Vitro – In Vivo Extrapolation for High-Throughput Prioritization and Decision-Making Setting the Stage Barbara A. Wetmore The Hamner Institutes for Health Sciences Research Triangle Park, NC USA 27709 bwetmore@thehamner.org IVIVE Webinar | October 7, 2015

In Vitro -to- In Vivo Extrapolation for High-Throughput Prioritization and Decision-Making • Webinars: First Wednesdays, 11:00AM E.D.T. – October 7 – Barbara Wetmore: Setting the Stage – November 4 – John Wambaugh: Model Development – December 2 – Lisa Sweeney: Model Evaluation – January 6, 2016 – TBD: State of the Science • In-person Meeting: February 17-18, 2016 – US EPA, Research Triangle Park, NC IVIVE Webinar | October 7, 2015

Broad-Based Movement in Toxicology Towards In Vitro Testing and Hazard Prediction IVIVE Webinar | October 7, 2015

High-Throughput Toxicity Testing Data Difficulty Translating Nominal Testing Concentrations into In Vivo Doses Knudsen et al. Toxicology 282:1-15, 2011 IVIVE Webinar | October 7, 2015

In Vitro - In Vivo Extrapolation Definition: Utilization of in vitro experimental data to predict phenomena in vivo • IVIVE-PK/TK (Pharmacokinetics/Toxicokinetics): Fate of molecules/chemicals in body – Considers ADME; uses PK / PBPK modeling • IVIVE-PD/TD (Pharmacodynamics/Toxicodynamics): Effect of molecules/chemicals at biological target in vivo – Assay design/selection important; perturbation as adverse/therapeutic effect, reversible/ irreversible • Both contribute to predict in vivo effects IVIVE Webinar | October 7, 2015

– IVIVE to Predict Pharmacokinetics – Prioritization and Hazard Prediction Based on Nominal Concentrations Can Misrepresent Potential Health Risks Protein Binding Bioavailability van de Waterbeemd and Gifford, Nat Rev Drug Disc 2:192, 2003 Reif et al. Environ Hlth Perspect 118:1714, 2010 Metabolic Clearance IVIVE Webinar | October 7, 2015

-- IVIVE in a HT Environment -- Modeling In Vivo Pharmacokinetics Using In Vitro Assays 3 2 1 Ln Conc (uM) 0 -1 -2 -3 -4 -5 0 50 100 150 Time (min) Human Hepatic Hepatocytes Clearance (10 donor pool) In Vitro - In Vivo Extrapolation Steady State Blood Concentrations Human Plasma Protein Plasma Binding (6 donor pool) IVIVE Webinar | October 7, 2015

-- IVIVE in a HT Environment -- Modeling In Vivo Pharmacokinetics Using In Vitro Assays Dose Rate * Body Weight In Vitro - In Vivo Extrapolation [Conc] SS = CL WholeBody • 100% Oral bioavailability assumed for both CL R and CL H + CL R CL H • Kinetics are assumed to be linear • CL R : renal clearance (L/hr) CL R = F UB * GFR where GFR ≈ 6.7 L/hr • CL H: hepatic clearance (L/hr) • Cl int: intrinsic clearance (L/hr) • GFR: glomerular filtration rate (L/hr) F UB * Q L * CL Int • F uB : fraction unbound in blood CL H = where Q L ≈ 90 L/hr • Q L : hepatic blood flow (L/hr) Q L + F UB * CL Int • HPGL: hepatocytes per gram liver • V L: volume of liver (g) CL Int = HPGL * V L * CL invitro where HPGL ≈ 137 million cells/g V L ≈ 1820 g IVIVE Webinar | October 7, 2015

Integrating Human Dosimetry and Exposure with the ToxCast In Vitro Assays 309 EPA ToxCast Phase I Chemicals ~600 In Vitro ToxCast Assays Least Sensitive Human Liver Human Plasma Assay Metabolism Protein Binding ToxCast AC 50 Value Population-Based IVIVE Model Most Oral Plasma Sensitive Exposure Concentration Assay Upper 95 th Percentile Css Oral Dose Required to Among 10,000 Healthy Achieve Steady State Individuals of Both Sexes Plasma Concentrations Reverse Dosimetry from 20 to 50 Yrs Old Equivalent to In Vitro Bioactivity (mg/kg/day) Rotroff et al., Tox Sci. , 2010 Wetmore et al., Tox Sci., 2012 IVIVE Webinar | October 7, 2015

Integrating Human Dosimetry and Exposure with the ToxCast In Vitro Assays Least Sensitive Oral Equivalent Dose (mg/kg/day) Assay Oral Dose Required to Achieve Steady State Plasma Concentrations Equivalent to In Vitro Bioactivity Most Sensitive Assay ? What are humans ? exposed to? ? Chemical Rotroff et al., Tox Sci. , 2010 Wetmore et al., Tox Sci., 2012 IVIVE Webinar | October 7, 2015

Pharmacokinetic Data Across 440 Chemicals Provides Insights into Distributions Across Tested Space Distribution of Chemical C ss ( µ M) 80 100 Cumulative Percent Number of Values 80 60 Distribution Information 60 1 µ M Median 40 Upper 90 th %ile 111 µ M 40 Upper 95 th %ile 230 µ M 20 20 0 0 0 0 0 0 2 5 0 0 5 1 - . 0 5 2 2 - - - 0 2 . > - 0 0 0 1 > > 5 > > 50 50 Distribution Summary Statistics Distribution Summary Statistics 45 45 Median 7.83 Median 5.4 40 40 Lower Quartile 0.00 20 20 Lower Quartile 0.5 % of Compounds Upper Quartile 36.70 % of Compounds Upper Quartile 19.2 16 16 12 12 8 8 4 4 0 0 0-5 >5-10 >10-20 >20-30 >30-40 >40-50 >50-60 >60-70 >70-80 >80-90 >90-100 0-5 >5-10 >10-20 >20-30 >30-40 >40-50 >50-60 >60-70 >70-80 >80-90>90->100 % Unbound Hepatic Clearance ( µ L/min/10 6 cells) IVIVE Webinar | October 7, 2015

How good are we at predicting in vivo C ss ? ToxCast Phase I Chemicals ToxCast Phase II Chemicals IVIVE In vivo - IVIVE IVIVE IVIVE Caco-2 c In vivo - Derived C ss Chemical a,b (µM) a,b (µM) a,b µM) Caco-2 c C ss C ss C ss Chemical Derived (µM) a,b µM) C ss C ss (µM) 0.57 Acetaminophen 1.1 0.52 40.43 2,4-D 9.05-90.05 39.25 0.58 2-Chloro-2’-deoxyadenosine 0.28 1.36 < 0.13 d 0.09 0.09 Bisphenol-A 15.40 0.01-0.02 13.63 Coumarin -- e Cacodylic acid 1.80 3.06 3.57 0.11-0.16 3.18 Diphenhydramine HCl 0.01 Carbaryl 0.03 0.01 1.80 6-Propyl-2-thiouracil 1.10 1.58 2.28 Fenitrothion 0.03 2.28 0.27 0.022 0.24 Chlorpyrifos 0.46 1.27 1.29 Lindane 2.5 0.2-1.8 11.6 Sulfasalazine Oxytetracycline 0.36 2.00 0.44 Candoxatril 0.14 0.023 0.18 dihydrate Flutamide 0.64 Parathion 2.56 0.004-0.005 0.57 0.17 2.48 171.51 f PK 11195 0.66 PFOS 19,990 f 153.23 f 0.14 0.58 15.92 f PFOA 20,120 f 13.25 f 1.59 4.92 1.59 5,5’-Diphenylhydrantoin 0.27 57.19 32.01 Picloram 0.002 0.05-0.29 0.004 Triamcinolone 15.20 Thiabendazole 0.45 13.76 0.03 0.037 0.03 Volinanserin 2-10 0.07 0.07 Triclosan 0.64 2.86 0.57 Zamifenacin IVIVE Webinar | October 7, 2015

How good are we at predicting in vivo C ss ? ToxCast Phase I Chemicals ToxCast Phase II Chemicals 27 Chemicals: ~60% are within 10-fold of in vivo C ss values IVIVE In vivo - IVIVE IVIVE IVIVE Caco-2 c In vivo - Derived C ss Chemical ~80% are within 20-fold of in vivo C ss values a,b (µM) a,b (µM) a,b µM) Caco-2 c C ss C ss C ss Chemical Derived (µM) a,b µM) C ss C ss (µM) 0.57 Acetaminophen 1.1 0.52 40.43 2,4-D 9.05-90.05 39.25 0.58 2-Chloro-2’-deoxyadenosine 0.28 1.36 < 0.13 d 0.09 0.09 Bisphenol-A 15.40 0.01-0.02 13.63 Coumarin -- e Cacodylic acid 1.80 3.06 3.57 0.11-0.16 3.18 Diphenhydramine HCl 0.01 Carbaryl 0.03 0.01 1.80 6-Propyl-2-thiouracil 1.10 1.58 2.28 Fenitrothion 0.03 2.28 0.27 0.022 0.24 Chlorpyrifos 0.46 1.27 1.29 Lindane 2.5 0.2-1.8 11.6 Sulfasalazine Oxytetracycline 0.36 2.00 0.44 Candoxatril 0.14 0.023 0.18 dihydrate Flutamide 0.64 Parathion 2.56 0.004-0.005 0.57 0.17 2.48 171.51 f PK 11195 0.66 PFOS 19,990 f 153.23 f 0.14 0.58 15.92 f PFOA 20,120 f 13.25 f 1.59 4.92 1.59 5,5’-Diphenylhydrantoin 0.27 57.19 32.01 Picloram 0.002 0.05-0.29 0.004 Triamcinolone 15.20 Thiabendazole 0.45 13.76 0.03 0.037 0.03 Volinanserin 2-10 0.07 0.07 Triclosan 0.64 2.86 0.57 Zamifenacin IVIVE Webinar | October 7, 2015

Reasons for C ss Overprediction - Opportunities for Refinement - • Not all routes of metabolic clearance are captured • Extrahepatic (intestinal, renal, etc.) metabolism • Nonhepatocyte-mediated clearance • Hepatocyte suspensions unable to detect clearance of low turnover compounds • Absorption / Bioavailability assumed 100% • Restrictive vs. Nonrestrictive clearance • Conservative assumptions drive poor predictivity for chemicals known to be rapidly cleared in vivo IVIVE Webinar | October 7, 2015

Toxicokinetic Triage for Environmental Chemicals Wambaugh et al., Tox Sci., 2015 IVIVE Webinar | October 7, 2015