260 likes | 281 Views
Melvin Andersen (CIIT) Matthew Bogdanffy (DuPont) James Bus (Dow) Rory Conolly (CIIT) Raymond David (Kodak) Christopher DeRosa (ATSDR) Nancy Doerrer (HESI) John Doull (University of Kansas) William Farland (EPA) Penelope Fenner-Crisp (ILSI RSI) David Gaylor (Gaylor and Associates).
E N D
Melvin Andersen (CIIT) Matthew Bogdanffy (DuPont) James Bus (Dow) Rory Conolly (CIIT) Raymond David (Kodak) Christopher DeRosa (ATSDR) Nancy Doerrer (HESI) John Doull (University of Kansas) William Farland (EPA) Penelope Fenner-Crisp (ILSI RSI) David Gaylor (Gaylor and Associates) Dale Hattis (Clark University) Gary Kimmel (EPA) Christopher Portier (NIEHS) Bernard Schwetz (FDA) R. Woodrow Setzer, Jr. (EPA) William Slikker, Jr. (FDA) Bob Sonawane (EPA) James Swenberg (University of NC) Kendall Wallace (University of MN) Mildred Williams-Johnson (ATSDR) Workshop Organizing Committee
Publications Slikker, W., Jr., Andersen, M.E., Bogdanffy, M.S., Bus, J.S., Cohen, S.D., Conolly, R.B., David, R.M., Doerrer, N.G., Dorman, D.C., Gaylor, D.W., Hattis, D., Rogers, J.M., Setzer, R.W., Swenberg, J.A., Wallace, K., 2004a. Dose-dependent transitions in mechanisms of toxicity. Toxicol. Appl. Pharmacol. 201, 203-225. Slikker, W., Jr., Andersen, M.E., Bogdanffy, M.S., Bus, J.S., Cohen, S.D., Conolly, R.B., David, R.M., Doerrer, N.G., Dorman, D.C., Gaylor, D.W., Hattis, D., Rogers, J.M., Setzer, R.W., Swenberg, J.A., Wallace, K., 2004b. Dose-dependent transitions in mechanisms of toxicity: case studies. Toxicol. Appl. Pharmacol. 201, 226-294
Absorption Active or passive via GI or respiratory tract Distribution Protein binding, active transport Elimination Renal organic anion transport Chemical transformation Activation Butadiene Detoxification Vinyl chloride, Methylene chloride Enzyme saturation Vinylidine chloride, Ethylene glycol Co-substrate depletion Acetaminophen Receptor interaction PPAR, progesterone/hydroxyflutamide Repair or reversal Vinyl chloride Altered homeostasis Propylene oxide, Formaldehyde Induction Vinyl acetate, Manganese, Zinc Metabolic switch Cell proliferation Examples of Dose-Dependent Transitions in Kinetic Disposition and Dynamic Expression
Mode of action CYP 2E1 catalyzed: CH2Cl2 CHOHCl2 HCOCl CO + CO2 formyl chloride COHb GST catalyzed: CH2Cl2GSCH2Cl GSCH2OH HCHO chloromethylglutathione GSCHO HCOOH CO2
20 15 10 5 0 Human data 40 35 30 25 Vmaxc/Km (/hr) 1 2 3 4 5 6 7 8 9 C B E D 10 11 12 13 A Johanson (2001) Expert Elicitation Individual Values (Jonsson et al. (2001) Clewell (1995) OSHA Posterior Jonsson and Individual Values (Sweeney et al., 2004) OSHA Prior Population Values
Key components of the formaldehyde risk assessment (I) • Regional dosimetry and effects data in the respiratory tract • DPX • Labeling index • Time-course and dose-response data • Labeling index • DPX • tumors • Sophisticated extrapolation tools • CFD modeling • Rat and rhesus
Key components of the formaldehyde risk assessment (II) • Sophisticated extrapolation tools • CFD modeling • Effects data from rat and rhesus monkey • Human physiology
Q1--Improvements to Exposure and Dose Monitoring--Beyond “Dose-Response” • Need to think in terms of dose-time-response relationships to inform collection or modeling of external exposure and dose information in relevant time periods. • Both exposure duration and age-at-exposure and are relevant, especially for developmental effects. • Sensitivity is not necessarily constant within a “window of vulnerability” (e.g. per modeling by Luecke)
Q3--Does modeling of adaptive responses require any changes in current regulatory testing strategies? In assessment approaches? • In general it is not sufficient for a good assessment to establish the presence of “adaptive responses” at particular dose levels to assure safety. Such responses are not necessarily biologically costless or perfectly effective in preventing adverse effects in all people.
Q4--What type of dose-response models or approaches might be “better” used to integrate the diverse data? For characterizing variability and uncertainty? • There is need to replace all the “uncertainty factor’s with distributions based on empirical data for analogous cases. See, as a preliminary effort, http://www2.clarku.edu/faculty/dhattis. This is, among other things, the only way to produce estimates of finite exposure control benefits to juxtapose with exposure control costs. • In general, the more non-linear the model is at relevant exposure levels, the more important it is to make quantitative assessments of uncertainty and variability—both for judging risks to relatively sensitive segments of the population and for producing “expected value” estimates of risk and cost.
Relationships of Exposure and Dose to Risk • Individual versus Population Risks • Risk Descriptors • Central Estimates • High End • Reasonable Worst Case • Theoretical Upper Bound Estimate (TUBE)
Typical non-linear, “threshold”, dose-response relationship (R=Ad3)* R(Response) d(Dose) * Adapted from Heitzmann and Wilson (1997)
Additivity to Background * R(Response) d(Dose) * Adapted from Heitzmann and Wilson (1997)
Comparison of Slopes * R(Response) Linear response (high dose) ßinc(high dose) ßinc(low dose) RO dh dO d(Dose) * Adapted from Heitzmann and Wilson (1997)
Tumor Incidence in Heterogeneous Population Lutz, 1990 Monogenic Determination of Sensitivity Max. Population B Population A Spont. Carcinogen Dose
Tumor Incidence in Heterogeneous Population Lutz, 1990 Polygenic Determination of Sensitivity Max. Spont. Carcinogen Dose
Tumor Incidence in Heterogeneous Population Lutz, 1990 Sensitivity Governed by Multiple Genes + Modulation by Lifestyle Max. Spont. Carcinogen Dose
Tumor Incidence in Heterogeneous Population Lutz, 1990 Monogenic Determination of Sensitivity Polygenic Determination of Sensitivity Sensitivity Governed by Multiple Genes + Modulation by Lifestyle
Dose-Dependent Transitions in Mechanisms of Toxicity:Impact of Testing Strategies and Risk Assessment ApproachesSociety of Toxicology, March 7, 2005 David Jacobson-Kram, Ph.D., DABT Center for Drug Evaluation and Research Office of New Drugs
Center for Drug Evaluation and Research, FDA • CDER generally does not perform quantitative risk assessment except for drug impurities and degradation products • CDER generally has rigorous exposure and metabolism data in humans and animals, often at comparable doses • Safety studies for specific human populations can be modeled in parallel animal studies, eg. Juvenile animal tox studies, geriatric possible but not practical
Challenges for CDER • Detection of rare adverse events (eg Vioxx) • Development of animal models capable of predicting rare AEs • Animals engineered with rare genetic polymorphisms • Animal models compromised because of other exposures, pharmaceutical, life style or environment