Integration of Pharmacokinetic (PK) and Pharmacodynamic (PD) Modeling of Arsenic to Inform the Risk Assessment Process

1. Integration of Pharmacokinetic (PK) and Pharmacodynamic (PD) Modeling of Arsenic to Inform the Risk Assessment Process Elaina M. Kenyon Hisham A. El-Masri Rory B. Conolly U.S. EPA, ORD

2. Disclaimer ! • This presentation does not necessarily reflect EPA policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. • This work is a work in progress!

3. Susceptibility Susceptibility Exposure-Dose-Response Paradigm Exposure bioavailability Internal Dose Biologically Effective Dose Early Biological Effects Altered Function/Structure Clinical Disease Prognostic Significance Modified from Schulte, 1989

4. What Makes Arsenic Unique? • Pancarcinogenic in humans, whereas rodents are much less responsive • Large cross-species differences in metabolism • Tissue-specific differences in metabolite accumulation • Toxicity most likely mediated by metabolism • Known variations in metabolism due to age and ethnicity in humans • Polymorphisms identified in AS3MT, the principal As metabolizing enzyme

5. IAsV Methylation Reduction (1) Inhibit DNA repair (9). Non tumorigenic to mice and rats (14). (1) Induce chromosomal aberrations (4), genetic instability (5). Induce alterations in methylation patterns (6). Generate reactive oxygen species (7) and 8-oxo-dG adducts (8). Interfere with DNA repair (9). Induce p53 (10) and cell proliferation (11). Mouse carcinogen (12) and co-carcinogen (13). Induce DNA damage (19) and 8-oxo-dG adducts (20). Induce p53 (10) and cell proliferation (11). Rat bladder carcinogen (20) and rat bladder tumor promoter (21). MMAsV (1) (1) DMAsV Induces 8-oxo-dG adducts (17). Rat liver carcinogen (24). (2) Induce chromosomal aberrations and DNA breaks (15). Generate reactive oxygen species (16) and 8-oxo-dG adducts (17). Induce cell proliferation (18). Inhibit DNA repair (9). (2) Induce chromosomal aberrations and DNA breaks (15,22) Generate reactive oxygen species (16) Inhibit DNA repair (9) Induce p53 (10) and cell proliferation (23). TMAsV (3) TMAs(-III)

6. Accumulation of Arsenicals Varies Significantly Across Tissues Female C57Bl6 Mice - 12 week drinking water exposure to As(V)

7. 1 1 0.1 0.1 82m 81m 82m 80r 75k 76k 78k 81m 79k 77k 75k Role of PBPK and BBDR Models INTERNAL DOSE AT TARGET (e.g., TISSUE, ORGAN) APPLIED DOSE RESPONSE PBPK MODEL BBDR MODEL 83c 83c 83c • Biological Response • (chemical’s effect on the body) • Information to Develop BBDR Model • Target site. • Adverse effect (what constitutes a significant deviation from normal). • Mode of Action (i.e., key events leading to an effect). • Best measure of effect (s). • Chemical Disposition • (bodies effect on the chemical) • Information to Develop the PBPK Model • Target site (s) (organ, tissue, cell). • Chemical specific ADME rates. • Species specific parameter values (tissue volumes, blood flow rates. • Which internal dose metric to use (based on mode of action).

8. Biological Hypothesis Physiological Biochemical Parameters PBPK Model Model Simulations (tissue levels) Model-Designed Experiments Disagree { Experimental Data Model Evaluation Agree

9. PK/PD Model Utility in Risk Assessment? • Relate Exposure to target tissue dose of parent chemical or metabolite(s) • Tissue dose is related to injury • Predictions at different exposure levels • Relate tissue dose between species • Animals to humans • Biologically based model to address variability and uncertainty • Exposure variability • Physiological and biochemical variability • Experimental design to test hypotheses

10. Key Question Given that arsenic toxicity is most likely mediated by metabolism, what are the implications of interspecies differences in metabolism and tissue accumulation? Use the model to assess the relationship between measures of arsenical dose to target tissue and toxic outcomes across species

11. An ExampleDMAV-Induced Bladder Cancer • Putative mode of action is cytotoxicity and regenerative cell proliferation • Rat bladder urothelium is highly responsive by several endpoints • Mouse is almost non-responsive (some evidence of cytotoxicity) • DMAV metabolism (2000) • DMAV￫ DMAIII￫TMAO

12. DMAV Metabolism (2007) DMTAV DMAV DMAIII DMTAIII TMAO TMA TMASV Adair et al., 2007

13. What makes the rat different? • Much longer t1/2 (weeks) compared to mice (days) or humans • Binding of DMAIII to rat hemoglobin creates large storage depot • Metabolism more extensive • Pharmacodynamics – is rat urothelium intrinsically more sensitive?

14. Use the PBPK Model to Evaluate the Basis for Interspecies Differences in Response • Incorporate PK features that account for known interspecies differences in ADME • Hemoglobin binding • Metabolism • Simulate long-term exposure scenarios • Assess relationship between measures of internal dose and differences in response among species

15. Previous As PBPK Models Yu (1999) model: • Partition coefficients were solely determined using a child poisoning case. This study provided total arsenic levels only. There was no information in poisoning study that would help the researchers to determine the partition coefficients for arsenic and its metabolites (MMA and DMA) as was published and referenced in the Yu (1999) publication. • Yu (1999) stated in their publication that they used the child poisoning study to determine metabolic parameters such as Vmax and Km. The child poisoning study did not have any information that can lead to these estimates. • Yu (1999) model simulations were not tested against data.

16. Previous As PBPK Models Mann et al. (1996) model: • The modeling effort for the humans was based on modification of an earlier one that was established for rabbits and hamsters. Both models did not include descriptions of current knowledge about metabolism of arsenic (such as the inhibition effects of Arsenic and MMA). • The model calibration relied heavily on “global” optimization of parameters such as partition coefficients, first order oral absorption constant, methylation rate constants, oxidation and reduction constants. All of these parameters were optimized using urine data. “Global” optimization would yield a set of unidentifiable parameters.

17. Development of a Human PBPK Model for Arsenic El-Masri, H. and Kenyon, E.M. 2007. Development of a Human Physiologically-Based Pharmacokinetic (PBPK) Model for Inorganic Arsenic and its Mono- and Di-methylated Metabolites. Journal of Pharmacokinetics and Pharmacodynamics, epub.

18. As Human PBPK Model • A physiologically-based pharmacokinetic (PBPK) model was developed to estimate levels of arsenic and its metabolites in human tissues and urine after oral exposure to arsenate (AsV), arsenite (AsIII) or organoarsenical pesticides. • The overall model consists of interconnected individual PBPK models for Asv, AsIII, monomethylarsenic acid (MMAv), and, dimethylarsenic acid (DMAv). • Metabolism of inorganic arsenic in liver was described as a series of reduction and oxidative methylation steps incorporating the inhibitory influence of metabolites on methylation. • Unique aspects of this model development effort are that it addresses parameter sensitivity and identifiably, utilizes human data whenever possible and incorporates new data on arsenic methylation

19. Lung Lung Lung Lung Liver Liver Liver Liver Blood Blood Blood Blood Kidney Kidney Kidney Kidney GI GI GI GI Heart Heart Heart Heart Muscle Muscle Muscle Muscle Skin Skin Skin Skin Brain Brain Brain Brain

20. Noncompetitive inhibition GSH AS3MT GSH AsV AsIII MMAV MMAIII DMAV Reduction AS3MT Reduction GSH oxidation Reduction oxidation oxidation DMAIII Noncompetitive inhibition

21. Table 3. An example of some of the biochemical Parameters

22. Utility of Urine Data

23. Model Calibration (DMA Dose)

24. Model Calibration (MMA Dose)

25. Model Calibration (As Dose)

26. Model Evaluation

28. Table 3. Biochemical Parameters Values Conclusions • The current As Human PBPK model was developed to include complex metabolic pathways consistent with recent experimental observations of the interrelations between arsenic and its metabolites. • Model parameterization was largely based on up-to-date in vitro studies, and optimization of parameters that are only sensitive to the shape of the urinary excretion curve. • The current model was calibrated and evaluated using human urine data obtained from several sources • The current model can be used to assess the relationship between target tissue dose of arsenic metabolites (including MMAIII, DMAIII or both) and response in conjunction with BBDR. • Because the model describes physiological and biochemical processes, it can be used to quantitatively assess kinetic variability such as ones related to polymorphisms in human arsenic metabolizing enzymes.

29. What is the Utility of the Human Arsenic Model Now and in the Future? • Assess the impact of human variability in arsenic metabolism • Evaluate assumptions used in default risk analysis methods against experimental data • Linking with Exposure Models (multi-media, multi-pathway) • Examine the role of kinetics in cross-species extrapolation • Essential to Link with BBDR models for multiple arsenicals and modes of action

30. Key Question: What are the implications of polymorphisms and age-dependent variation in arsenic metabolism? Use the Model to Estimate the Impact of Variability in Human Metabolic Profiles (and its relationship to disease outcome measures)

31. What is Needed? • Physiological parameter distributions (literature) • Biochemical parameter distributions (e.g. methylation rate constants) • Human data collected at the level of the individual subject, especially exposure and urinary metabolite profiles

32. Advantages of this Approach • Incorporate and consider data from a variety of sources • in vitro metabolism studies (human hepatocytes) • Genetic association studies • Epidemiologic investigations • Assess the impact of variability in sensitive parameters on model predictions • Identify key uncertainties in model parameterization

33. From tissue dose to toxic response

34. Biological mechanisms determine dose-response Tissue dose Tissue interaction Exposure Tissue interaction Sequence of events (MoA) Cancer

35. Early Intermediate Late Organism Tissue Cellular Molecular

36. Information Reduce uncertainty by describing the system more accurately

37. Arsenical Exposure Tissue Dose (PBPK modeling) ROS - SH reactivity D DNA methylationenzymes D DNA repairenzymes lipid oxidation protein oxidation Change in cell phenotype D cell cycle / apoptosis DNA damage D chromosome copy number altered DNA methylation Genomic instability (chromosome damage/ mutation accumulation) cell proliferation Cancer: self sufficiency in growth signals, evading apoptosis, insensitivity to anti-growth signals, limitless replicative potential

38. Arsenical Exposure Tissue Dose (PBPK modeling) ROS - SH reactivity D DNA methylationenzymes D DNA repairenzymes lipid oxidation protein oxidation Change in cell phenotype D cell cycle / apoptosis DNA damage D chromosome copy number altered DNA methylation Genomic instability (chromosome damage/ mutation accumulation) cell proliferation Cancer: self sufficiency in growth signals, evading apoptosis, insensitivity to anti-growth signals, limitless replicative potential

39. Overall dose-response and time-course is built up from the key event relationships (dosimetry) Dose-response and time-course Regulatory endpoint

40. Arsenical Exposure Tissue Dose (PBPK modeling) ROS - SH reactivity D DNA methylationenzymes D DNA repairenzymes lipid oxidation protein oxidation Change in cell phenotype D cell cycle / apoptosis DNA damage D chromosome copy number altered DNA methylation Genomic instability (chromosome damage/ mutation accumulation) cell proliferation Cancer: self sufficiency in growth signals, evading apoptosis, insensitivity to anti-growth signals, limitless replicative potential

41. Arsenical Exposure Tissue Dose (PBPK modeling) ROS - SH reactivity Dose-response and time-course for each key event!!!! D DNA methylationenzymes D DNA repairenzymes lipid oxidation protein oxidation Change in cell phenotype D cell cycle / apoptosis DNA damage D chromosome copy number altered DNA methylation Genomic instability (chromosome damage/ mutation accumulation) cell proliferation Cancer: self sufficiency in growth signals, evading apoptosis, insensitivity to anti-growth signals, limitless replicative potential

42. Skin dose Arsenic dosimetry Lung dose Bladder dose MOAbladder MOAskin MOAlung Bladder cancer Skin cancer Lung cancer

43. In vitro studies of MOA Available data Epi cancer dose-response Lab animal in vivo dose-response & time-course

44. In vitro studies of MOA Relevance to model development Epi cancer dose-response Very! Informs MOA, but generally lacking dose-response and time course. Also relevance issues (i.e., transformed cell lines). Lab animal in vivo dose-response & time-course Very!

46. 85 ppm in drinking water • 1 applied dose

48. 15 ppm in drinking water • 1 applied dose • human relevance?

49. As(III) causes oxidative DNA damage Concentration (M) Incubation time (hr)

50. As(III) causes oxidative DNA damage Ke Jian “Jim” Liu, Ph.D. College of Pharmacy University of New Mexico Health Sciences Center Concentration (M) Incubation time (hr)