# Presentation: 500034

## Considerations for Improving High to Low Dose Extrapolation

- 		Lauren Zeise
- 		US EPA BOSC presentation
- 		February 2, 2005

## Considerations for improvements in

- Non-cancer dose response
- Cancer risk assessment
- Modeling and characterization processes

## Non-cancer dose response characterization issues

- Single number characterizes entire dose response relationship
- No risk estimation and low dose prediction
- Threshold dose response nearly always assumed
- Background exposure not typically considered

## RfD from typical experiment: Adjusted NOAEL or Benchmark Dose

- NOAEL

- BMD

**Notes:**
Assumption is that Average Human more sensitive than test animals.  Has a pharmacokinetic component and pharmacodynamic component.  Scaling by BW3/4 produces similar numbers for rat, but higher UF for mice.

## Low dose risk estimation:  “Probabilistic RfD” method

- Adjustment & uncertainty factors are probability distributions
- Human non-cancer dose response is a dose vs. risk function
- RfD is dose at a *de minimis* risk level
- Uncertainty in RfD estimated

## Construction of “probabilistic dose response”

- ED01 Distribution

## US EPA Dioxin Risk Assessment:  Recognition of background

- Recognizes background exposures
- Does not establish RfD
- Characterizes the margin of exposure =
-                 exposure inducing 1% risk
-   		   human background exposure level

- Nursing Infant

## Background Exposures

- Risk

- Axis translation

## Non-carcinogenic effects where threshold not apparent

- Lead
- PM
- Ozone
- Methylmercury
- Arsenic
- Benzene

- “ ...recent epidemiological studies ... suggest that there is no threshold concentration for O3, Pb, and PM”

- National Research Council, 2004

## Cancer Dose Response 

## Creating tools to translate biological data on variability into mathematical models of human cancer risk   

**Creating tools to translate biological data on ****variability**** into mathematical models of human cancer risk  **** **

## Combining models of human variability and cancer

## Total risk when agent causes cancer at multiple sites 

- Dimethoxybenzidine

- Needed: Tools to calculate lower bounds on e.g. ED01 and ED10

## Rodent Bioassays:  

- Dosing Periods and Critical Windows

- conception

- birth

- 6 wks

- 8 wks

- 2 years

- 3 years

- Standard Assay

## Tumors of nervous system in rats treated with N-ethylnitrosourea (ENU) at different ages (Naito et al., 1981) 

- Birth

**Tumors of nervous system in rats treated with N-ethylnitrosourea (ENU) at different ages (Naito et al., 1981)**

**Total nerve tumors**

- McDonald, 2002

## Background exposures, “non-linear” carcinogens, & incomplete carcinogens

## Probabilistic RfD compared to EPA standard cancer assessment

**Cancer**
- Non-threshold model
- Variability in susceptibility not addressed
- Assumes background important
- Full uncertainty in estimates typically not modeled

**Non-cancer Prob RfD**
- Threshold model
- Individual thresholds vary — Variable susceptibility addressed
- Background exposures ignored
- Uncertainty expressed as  probability distribution

## Harmonization of cancer and non-cancer approaches

- Limitations in both approaches
- Expand existing approaches to more optimal “harmonized” approach? Explore new approaches?
- Address background, human variability, and uncertainty
- Incorporate qualitative measures of uncertainty
- Some possible critical features – chemical persistence, subtlety of effect, complexity of toxicological process

## Terminology

- Uncertainty — Variability
- NOAEL — NOEL
- Uncertainty Factor — Adjustment Factor
- “Non-linear” — “Linear” — “Low dose linear”

- Low Dose Linear

- Supralinear

- Sublinear

## Mechanistic models and pharmacokinetic model adjustments for high to low dose extrapolation

- Model: series of differential equations:

## Developments for pharmaco- kinetic and dynamic models

- Site specificity assumption
- Model and parameter uncertainty characterization (e.g., hierarchical Bayesian approach)
- Statistical evaluation
- Overall model validation
- Expert review

## Risk Management Considerations

- Dose response so that risk characterizations  adequately inform decision making
- Support routine decision making (e.g., permitting)
- Support decision making broad in scope

- National Research Council, 1996