1. Photo image area measures 2” H x 6.93” W and can be masked by a collage strip of one, two or three images. The photo image area is located 3.19” from left and 3.81” from top of page. Each image used in collage should be reduced or cropped to a maximum of 2” high, stroked with a 1.5 pt white frame and positioned edge-to-edge with accompanying images. Reeder Sams, Hisham El-Masri, Office of Research & Development USEPA Development of a Quantitative Model Incorporating Key Events in a Hepatotoxic MOA to Predict Tumor Incidence Disclaimer: This presentation has been reviewed by the EPA. The views expressed in this presentation are those of the authors and do not necessarily reflect EPA policy

2. 1 Presentation Outline  Purpose  Biologically Based Dose Response Models  Human Health Risk Assessment Needs  Need for BBDR Models  Possible Avenues to Test Hypothesized MOAs  Development of a BBDR Model for a Cytotoxic MOA  Methods and Modeling (H El-Masri)  Results (H El-Masri)  Conclusions and Steps Forward (El-Masri &Sams)

3. 2 Purpose for Developing BBDR Models? Help organize data and development of hypotheses Allow more robust testing of hypotheses and assumptions based on quantitative information (test MOA hypothesis) Inform shape of the dose response Extrapolate results and make predictions outside experimental conditions Assess relevance of animal model for human risk assessment

4. 3 Quantitative Dose-response Assessment MOA informs low-dose extrapolation? MOA Established? BBDR model? 1. Fit data in observable range 2. Linear extrapolation from POD Use model RfD/RfC or MOE Yes Yes, nonlinear No Yes, linear (including mutagenic MOA)

5. 4 MOA data: Challenges for BBDR Models Having sufficient information on MOA Interpretation of data when multiple modes of action are operative Application of well-established MOA from one chemical to another for which data are limited Determination of MOA data that are not relevant to humans Lack of dose-response information Separating chemical-induced events from natural progression of cancer

6. 5 Mechanistically Based Models Bottom Line –A BBDR is only as accurate as the sum of its individual components. Uncertainty in key assumptions (e.g. MOA), parameters, variables, etc…. must be characterized in multiple predictive outputs.

7. Development of a Quantitative Model Incorporating Key Events in a Hepatotoxic Mode of Action to Predict Tumor Incidence Nicholas S. Luke*Nicholas S. Luke*, Reeder Sams II†Reeder Sams II†, Michael J. DeVito‡Michael J. DeVito‡, Rory B. Conolly§Rory B. Conolly§ and Hisham A. El-Masri§Hisham A. El-Masri§,11 1To whom correspondence should be addressed at U.S. Environmental Protection Agency, 109 T.W. Alexander Drive, Mail Drop B143-01, Research Triangle Park, NC 27711. Fax: (919) 541-4284. E-mail: el- masri.hisham@epa.gov.el- masri.hisham@epa.gov 6

8. 7 Hypothesized MOA: Cytotoxicity → Cellular Regeneration Multiple compounds proposed to induce tumors via cytotoxicity leading to cellular regeneration: –Chloroform –Carbon tetrachloride –1,4-Dioxane –Dimethylarsinic acid –Furan –N,N-Dimethyl formamide Multiple MOAs may be operative

9. 8 Hypothesized MOA: Cytotoxicity → Cellular Regeneration Parent or Metabolite Hyperplasia Clonal expansion Cytotoxicity Regenerative Proliferation Tumors (e.g. liver, kidney) Sustained Identifiable (Measurable) Key Events

10. Choice of Pollutants for a Test Case BBDR Test case MOA based upon carcinogenicity endpoint Considerations for toxicodyamic data –Tumor data is available for numerous pollutants hypothesized to result from a cytotoxic MOA –Is there data for the hypothesized key events? –Limit other variables that may decrease accuracy of a BBDR model Route of exposure Site concordance Rodent species, strain, sex Laboratory Considerations for toxicokinetic data 9

11. Availability of Chemical-Specific Data PBPK ModelCytotoxictyProliferationTumor Data CCl 3 ++++ CCL 4 ++++ DMF -+-+ 10 Key Events (hypothesized)

12. 11 Model Structure

13. 12 Data Needs to Populate Model Pharmacokinetic Data –PBPK models for chloroform and carbon tetrachloride available in literature –Use of available data to develop a PBPK model for DMF Labeling Index Data – Multiple times – Dose Response Measure of Cytotoxicity – SDH, ALT, etc. Tumor Incidence Data – 2 yr bioassay – time to tumor (or intermediate time points)

14. 13 Cytotoxicity Model

15. Cytotoxicity Model Parameters 14 ParameterDescriptionCHCl 3 CCl 4 DMF k dam Proportionality constant relating rate of metabolism to damage (damage units/mg/l) 18.7390.5255 k dam Maximum repair capacity (damage units/h) 95.3 k1k1 Half-maximal damage (damage units) 186.1 β ctrl Cell death rate of control liver (h −1 ) 7.7 × 10 −5 k1k1 Proportionality between amount of damage and death rate ([damage units × h] −1 ) 1.0 × 10 −6 Th Threshold level of damage (damage units) 6.97 α ctrl Cell division rate of control liver (h −1 ) 7.7 × 10 −5 N ctrl Number of cells in control liver 1.69 × 10 8f 1.69 × 10 8 α max Maximum possible division rate (h −1 ) 0.045

16. 15 SDH and k dam From Lundberg et al., 1986 Table: Comparison of SDH and the parameter Linear slope (SDH to dose) Ratio to CHCL 3 CHCL 3 0.207411 CCL 4 3.04414.688.739 DMF0.11260.54280.5255

17. 16 Cytotoxicity Results

18. 17

19. 18 Clonal Growth Model Three cell populations: Normal, Initiated, Malignant Cells move to next population via mutation Normal and Initiated populations undergo division and death/differentiation Malignant cells will lead to tumor after a delay.

20. Initiated Cell Growth 19 Initiated Cells Death disadvantage Initiated Cells Growth advantage OR

21. 20 Tumor Incidences Simulations

22. 21 Clonal Growth ParameterDescriptionCHCl 3 CCl 4 DMF μNμN Probability of a normal cell attaining a mutation 2.6 × 10 −9 μNμN Probability of an initiated cell attaining a mutation 2.6 × 10 −9 BD Death rate reduction for initiated cells 0.7310.5160.466 GA Proliferation rate increase for initiated cells 1.2751.5021.539

23. 22 Cellular Proliferation and Tumor Incidences CHCl 3 CCl 4 DMF Dose (ppm)9025265 Labeling index (%)18 Tumor incidence (%)1285100

24. 23 Conclusions Quantitative modeling was useful to assess a generalized MOA across chemicals: – CHCL 3,CCL 4 and DMF cytotoxic MOA SDH or other measures of cytotoxicity Labeling Indices Quantitative modeling indicates –Possibility of other key events –Possibility of multiple MOAs Identified data needs –Time to tumor data –“Initiated” cells: death and proliferation rates