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Dose-Response Modeling: Past, Present, and Future

Dose-Response Modeling: Past, Present, and Future. Rory B. Conolly, Sc.D. Center for Computational Systems Biology & Human Health Assessment CIIT Centers for Health Research (919) 558-1330 - voice rconolly@ciit.org - e-mail

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Dose-Response Modeling: Past, Present, and Future

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  1. Dose-Response Modeling: Past, Present, and Future Rory B. Conolly, Sc.D. Center for Computational Systems Biology & Human Health Assessment CIIT Centers for Health Research (919) 558-1330 - voice rconolly@ciit.org - e-mail SOT Risk Assessment Specialty Section, Wednesday, December 15, 2004

  2. Outline • Why do we care about dose response? • Historical perspective • Brief, incomplete! • Formaldehyde • Future directions

  3. Perspective • This talk mostly deals with issues of cancer risk assessment, but I see no reason for any formal separation of the methodologies for cancer and non cancer dose-response assessments • PK • Modes of action • Tumors, reproductive failure, organ tox, etc.

  4. Dose Typical high dose rodent data – what do they tell us? Response

  5. Interspecies Dose Not much! Response ?

  6. Interspecies Dose Possibilities Response

  7. Interspecies Dose Possibilities Response

  8. Interspecies Dose Possibilities Response

  9. Interspecies Dose Possibilities Response

  10. Benzene Decision of 1980 • U.S. Supreme Court says that exposure standards must be accompanied by a demonstration of “significant risk” • Impetus for modeling low-dose dose response

  11. 1984 Styrene PBPK model(TAP, 73:159-175, 1984) A physiologically based description of the inhalation pharmacokinetics of styrene in rats and humans John C. Ramseya and Melvin E. Andersenba Toxicology Research Laboratory, Dow Chemical USA, Midland, Michigan 48640, USAb Biochemical Toxicology Branch, Air Force Aerospace Medical Research Laboratory (AFAMRL/THB), Wright-Patterson Air Force Base, Ohio 45433, USA

  12. Biologically motivated computational models(or)Biologically based computational models • Biology determines • The shape of the dose-response curve • The qualitative and quantitative aspects of interspecies extrapolation • Biological structure and associated behavior can be • described mathematically • encoded in computer programs • simulated

  13. Risk assessment Experiments to understand mechanisms of toxicity and extrapolation issues Biologically-based computational models: Natural bridges between research and risk assessment Computational models

  14. Garbage in – garbage out • Computational modeling and laboratory experiments must go hand-in-hand

  15. Interspecies Dose Refining the description with research on pharmacokinetics and pharmacodynamics (mode of action) Response

  16. Interspecies Dose Refining the description with research on pharmacokinetics and pharmacodynamics (mode of action) Response

  17. Interspecies Dose Refining the description with research on pharmacokinetics and pharmacodynamics (mode of action) Response

  18. Interspecies Dose Refining the description with research on pharmacokinetics and pharmacodynamics (mode of action) Response

  19. Formaldehyde nasal cancer in rats:A good example of extrapolations across doses and species

  20. 1980 - First report of formaldehyde-induced tumors Swenberg JA, Kerns WD, Mitchell RI, Gralla EJ, Pavkov KLCancer Research, 40:3398-3402 (1980)Induction of squamous cell carcinomas of the rat nasal cavity by inhalation exposure to formaldehyde vapor.

  21. 60 Kerns et al., 1983 50 Monticello et al., 1990 40 30 (%) Tumor Response 20 10 0 0 0.7 2 6 10 15 Exposure Concentration (ppm) Formaldehyde bioassay results

  22. Mechanistic Studies and Risk Assessments

  23. What did we know in the early ’80’s? • Formaldehyde is a carcinogen in rats and mice • Human exposures roughly a factor of 10 of exposure levels that are carcinogenic to rodents.

  24. 1982 – Consumer Product Safety Commission (CPSC) voted to ban urea-formaldehyde foam insulation.

  25. 1983 - Formaldehyde cross-links DNA with proteins - “DPX” Casanova-Schmitz M, Heck HDToxicol Appl Pharmacol 70:121-32 (1983)Effects of formaldehyde exposure on the extractability of DNA from proteins in the rat nasal mucosa.

  26. DPX

  27. 1984 - Risk Assessment Implications Starr TB, Buck RDFundam Appl Toxicol 4:740-53 (1984)The importance of delivered dose in estimating low-dose cancer risk from inhalation exposure to formaldehyde.

  28. 1985 – No effect on blood levels Heck, Hd’A, Casanova-Schmitz, M, Dodd, PD, Schachter, EN, Witek, TJ, and Tosun, T Am. Ind. Hyg. Assoc. J. 46:1. (1985) Formaldehyde (C2HO) concentrations in the blood of humans and Fisher-344 rats exposed to C2HO under controlled conditions.

  29. 1987 – U.S. EPA cancer risk assessment • Linearized multistage (LMS) model • Low dose linear • Dose input was inhaled ppm • U.S. EPA declined to use DPX data

  30. Summary: 1980’s • Research • DPX – delivered dose • Breathing rate protects the mouse (Barrow) • Blood levels unchanged • Regulatory actions • CPSC ban • US EPA risk assessment

  31. Key events during the ’90s • Greater regulatory acceptance of mechanistic data for risk assessment (U.S. EPA) • Cell replication dose-response • Better understanding of DPX (Casanova & Heck) • Dose-response modeling of DPX (Conolly, Schlosser) • Sophisticated nasal dosimetry modeling (Kimbell) • Clonal growth models for cancer risk assessment (Moolgavkar)

  32. 1991 – US EPA cancer risk assessment • Linearized multistage (LMS) model • Low dose linear • DPX used as measure of dose

  33. 1991, 1996 - regenerative cellular proliferation Monticello TM, Miller FJ, Morgan KT Toxicol Appl Pharmacol 111:409-21 (1991)Regional increases in rat nasal epithelial cell proliferation following acute and subchronic inhalation of formaldehyde.

  34. Normal respiratory epithelium in the rat nose

  35. Formaldehyde-exposed respiratory epitheliumin the rat nose (10+ ppm)

  36. (Raw data) ppm formaldehyde Dose-response for cell division rate

  37. DPX submodel – simulation of rhesus monkey data

  38. Summary: Dose-response inputs to the clonal growth model • Cell replication • J-shaped • DPX • Low dose linear

  39. CFD Simulation of Nasal Airflow(Kimbell et. al)

  40. Division (aN) (aI) Mutation (mI) Mutation (mN) Normal cells (N) Cancer cell Initiated cells (I) (delay) Death/ differentiation (bN) (bI) Tumor 2-Stage clonal growth model(MVK model)

  41. (Hockey stick transformation) (Raw data) ppm formaldehyde ppm formaldehyde Dose-response for cell division rate

  42. Simulation of tumor response in rats

  43. CIIT clonal growth cancer risk assessment for formaldehyde(late ’90’s) • Risk assessment goal • Combine effects of cytotoxicity and mutagenicity to predict the tumor response

  44. Cancer model (LMS) Tumor response 1987 U.S. EPA Inhaled ppm

  45. Tissue dose (DPX) Cancer model (LMS) Tumor response 1991 U.S. EPA Inhaled ppm

  46. CFD modeling Cell proliferation Cell killing Tissue dose Cancer model (Clonal growth) Mutagenicity (DPX) Tumor response 1999 CIIT Inhaled ppm

  47. Formaldehyde: Computational fluid dynamics models of the nasal airways F344 Rat Rhesus Monkey Human

  48. Human assessment

  49. Baseline calibration against human lung cancer data

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