Problem Formulation to Dose-Response: Advances via the Alliance for Risk Assessment Beyond Science and Decisions Workshops Michael Dourson Toxicology Excellence for Risk Assessment - PowerPoint PPT Presentation

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Problem Formulation to Dose-Response: Advances via the Alliance for Risk Assessment Beyond Science and Decisions Workshops Michael Dourson Toxicology Excellence for Risk Assessment

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Title: Problem Formulation to Dose-Response: Advances via the Alliance for Risk Assessment Beyond Science and Decisions Workshops Michael Dourson Toxicology Excellence for Risk Assessment


1
Problem Formulation to Dose-Response Advances
via the Alliance for Risk Assessment Beyond
Science and Decisions Workshops Michael
DoursonToxicology Excellence for Risk
Assessment
2
Alliance for Risk Assessmentwww.allianceforrisk.o
rg
  • A collaboration of organizations dedicated
    working together to solve public health issues
  • Improve communication among groups
  • Provide transparency in development of products
  • Foster harmonization and consistency in risk
    assessments
  • Share costs and human resources

3
Collaborators for Beyond Science Workshops
4
ARA Science Panel
  • Michael Bolger, U.S. Food and Drug Administration
  • James S. Bus, The Dow Chemical Company
  • John Christopher, CH2M/Hill
  • Rory Conolly, U.S. Environmental Protection
    Agency
  • Michael Dourson, Toxicology Excellence for Risk
    Assessment
  • Adam M. Finkel, UMDNJ School of Public Health
  • William Hayes, Indiana DEM
  • R. Jeffrey Lewis, ExxonMobil Biomedical Sciences,
    Inc.
  • Randy Manning, Georgia Department of Natural
    Resources
  • Bette Meek, University of Ottawa (Chairperson)
  • Paul Moyer, Minnesota Department of Health (MDH)
  • Greg Paoli, Risk Sciences International
  • Rita Schoeny, U.S. Environmental Protection
    Agency
  • On NAS Science and Decisions panel

5
Case Study Process
  • Engagement from wide variety of stakeholders
  • Proposed in brainstorming prior to first workshop
  • Initial vetting in breakout groups at 1st
    workshop
  • Presentations at 2nd workshop
  • Additional case studies identified at 2nd
    workshop
  • 30 case studies proposed
  • 24 case studies presented and reviewed by panel

6
Case Study Process Dose-Response Framework
  • Organization of methods and ability to identify
    gaps into an interactive framework based on NAS
    (2009)
  • Problem formulation
  • DR method
  • Management decision
  • The framework was developed by the panel after
    review of all case studies in the 2nd workshop,
    and was used to prioritize new case studies for
    3rd workshop, focusing on 3 topic areas
  • Problem formulation
  • Mode of action
  • Endogenous background exposures

7
Science and Decisions, NAS (2009) Framework for
Risk Assessment
  • Formulate Problem
  • Plan Conduct
  • Manage Risk
  • Determine problems with conditions
  • Determine options for change
  • What assessments are necessary for risk options?
  • Plan assessment
  • Conduct
  • Hazard ID
  • DR assessment
  • Exposure assessment
  • Risk characterization
  • Confirm Utility
  • Determine
  • Option benefits
  • How options affect other decision factors
  • Justify decision re benefit, cost uncertainty
  • Communicate decision

8
Alliance for Risk Assessment (ARA) Beyond
Science and Decisions Workshop Series
In-Depth Assessment
Qualitative Decision
Quantitative Screening
9
ARA Beyond Science Decisions
Qualitative Decision
  • Exposure and Endpoint Assessment
  • Identify potential health effects
  • Consider strengths and uncertainties in data
  • Identify potential exposure scenarios

Health Assessment Use available data to
assist management decision
Vulnerable Populations Assessment Use available
data to assist management decision
Exposure Assessment Use available data to
assist management decision
Integration
Results Reporting
10
ARA Beyond Science Decisions
Quantitative Screening Decision
  • Exposure and Endpoint Assessment
  • Identify adverse effects and chemical mode of
    action
  • Determine strengths and uncertainties in data
  • Define exposure scenarios get data on exposed
    populations

Health Assessment Use available data to
determine critical effect action mode
Vulnerable Populations Assessment Use available
data to determine potential groups at risk
Exposure Assessment Use available data to
determine upper bound exposures
Exposure Dose-Response Evaluation Based on the
available information, estimate a
health-protective exposure limit
Results Reporting
11
Quantitative Screening Decision
  • Tiered approach case study
  • Low-dose Extrapolation from BMD(L)
  • Threshold of toxicological concern/ of regulation
  • Screening-level safe dose (e.g., RfD)
  • Structure-activity relationships and read-across
    Quantitative SAR   

12
ARA Beyond Science Decisions
In-Depth Assessment
  • Exposure and Endpoint Assessment
  • Identify adverse effects and their precursors and
    MOA
  • Identify exposures, endpoints or lifestages
    under-assessed
  • Identify probabilistic exposure scenarios
    focusing on vulnerable populations

Exposure Assessment Identify endogenous
exposures conduct probabilistic exposure
scenarios
Vulnerable Populations Assessment Identify
vulnerable groups, considering exposures,
endpoints and MOA
Health Assessment Chose appropriate
extrapolation based on MOAs and background
disease
Risk Characterization Integrated extrapolation
with probabilistic exposure based on vulnerable
populations
Communicate characterization with uncertainties
13
Dose Response Framework
  • The risk assessor is guided to methods that
    address key issues, such as
  • Mode of action assessment
  • Vulnerable population assessment
  • Endogenous/background exposure
  • Dose-response methods reflecting different
  • Conceptual models
  • Data availability
  • Risk management needs

14
Methods Linked to Real-World Application
  • Summaries that
  • briefly describe dose response method,
  • provide references,
  • outline data requirements,
  • describe strengths and weaknesses
  • In depth full case study
  • Workshop presentation slides

15
The Expert Panel Determined
  • A wide range of problem formulations exist for
    which different dose-response analysis techniques
    are needed.
  • Risk assessors must explain criteria applied in
    the choice of a particular dose-response method,
    and how results will be used in a risk management
    decision.
  • Additional case studies would be useful on topics
    such as
  • Combined exposures
  • Value of information
  • Illustrating an entire risk assessment, from
    problem formulation to conclusion
  • In vitro to in vivo extrapolation

16
Next Steps
  • Framework will be evergreen
  • Updated with additional methods illustrated by
    case studies, and
  • Papers developed addressing resolving
    cross-cutting issues.
  • The National Library of Medicine is hosting the
    Framework.
  • A standing panel will be created to meet twice a
    year to review additional case studies and
    issue/resolution papers.
  • Additional sponsors/participants will be invited
    to join in the overall effort.

17
Framework
  • ARA Dose Response Framework (working beta)
    http//www.allianceforrisk.org/workshop/framework/
    problemformulation.html
  • Part 2 of the symposium presents several sample
    methods and case studies for risk around the RfD

18
ARA Cases on Risk Around the RfD
Areas of Uncertainty to Consider in Noncancer
Dose Response Assessment
Sub-chronic Animal
1
Chronic Human
Chronic Animal
Response
Reproductive
LOAELs
UFL
UFS
UFD
PBPK
NOAELs or BMDs
0.1
UFH
UFA
Dose
19
Case Study 17 Oliver Kroner Lynne Haber, TERA
  • This case study is a characterization of the
    method, and is not intended as endorsement or
    opposition of linear extrapolation.
  • Methods 1 to 4 extend a straight line from the
    chosen BMD or BMDL adjusted to the human
    equivalent dose or concentration (HED or HEC) by
    default or modified uncertainty factors.
  • Method 5 linearize HED(C) dose-response data
    using probit transformation in logarithmic space.
    Fit regression line to the data and extend to the
    low-dose

20
Method 1 Linear extrapolation from BMD
Response
Animal BMD
Human Equivalent Dose
UFS
UFD
UFA
0.1
Dose
21
Factor of 10 Enough?
Dourson, M.L., G. Charnley and R. Scheuplein, 2002
22
Summary of Results
    Method 1 and 4 Linear Extrapolation from BMD(L) Method 1 and 4 Linear Extrapolation from BMD(L) Method 5 Log-Dose, Probit Method 5 Log-Dose, Probit
  Chemical Risk at RfC/RfD From BMD(C)L (Method 1) Risk at RfC/RfD From BMD(C) (Method 4) Risk at RfC/RfD Number of Dose Groups (other than control)
Oral Acrylamide 1 x 10-2 3 x 10-4 1 x 10-3 3
Oral Chlordecone 1 x 10-2 1 x 10-5 2 x 10-3 4
Inhalation 1,3-Dichloropropene 8 x 10-3 6 x 10-4 2 x 10-12 3
Inhalation Nitrobenzene 1 x 10-2 4 x 10-3 5 x 10-1 3
23
Strengths and Limitations
  • Strengths
  • Simple to use and provides risk at any dose
  • Limitations
  • No consideration of underlying Mode of Action
  • Depending on UF, risk could be highly
    conservative
  • ARA Science Panel Comments
  • Possibly useful for screening, but should not be
    construed as accurate estimate of risk
  • Requested exploration of non-cancer linear
    extrapolation in log-dose, probit space

24
Probit Transformation
  • Linearizes biological data
  • Requires population data
  • To allow graphing in log space, response rates
    were converted to Excess Risk added risk(d)
    P(d) - P(0) for each dose group
  • a dataset of at least three test doses above the
    control

From Casarett Doull 2009
25
Method 5 Linear Extrapolation in Log-Dose,
Probit Space
Probit Response
Animal Data
Human Equivalent Dose
5
UFS
UFD
UFA
Log Dose
26
Probit Response
Log(10) Dose
27
Summary of Results
    Method 1 and 4 Linear Extrapolation from BMD(L) Method 1 and 4 Linear Extrapolation from BMD(L) Method 5 Log-Dose, Probit Method 5 Log-Dose, Probit
  Chemical Risk at RfC/RfD From BMD(C)L (Method 1) Risk at RfC/RfD From BMD(C) (Method 4) Risk at RfC/RfD Number of Dose Groups (other than control)
Oral Acrylamide 1 x 10-2 3 x 10-4 1 x 10-3 3
Oral Chlordecone 1 x 10-2 1 x 10-5 2 x 10-3 4
Inhalation 1,3-Dichloropropene 8 x 10-3 6 x 10-4 2 x 10-12 3
Inhalation Nitrobenzene 1 x 10-2 4 x 10-3 5 x 10-1 3
28
Strengths and Limitations
  • Strengths
  • Simple, and provides risk at any dose
  • Consistent with toxicological theory of
    probit/logarithmic dose response
  • Limitations
  • Restrictive data requirements permitted the use
    of only 4 of 25 chemicals such restriction could
    be relaxed
  • Differing results may be due to expected
    differences among chemicals in adverse responses,
    or different amounts of dose response data.

29
Case Study 11Elizabeth Spalt, IDEM Oliver
Kroner, TERA
  • Straightforward application of Swartout et al.
    (1998).
  • A single distribution is assumed for all factors,
    specifically, lognormal with a median of 100.5
    and a 95th value of 10.
  • Various probabilities of Swartout et al. (1998)
    are combined by multiplication. Other
    combinations may be possible.
  • Method indirectly addresses recommendation of NAS
    (2009) to develop probabilities for RfDs, but
    probabilities state whether RfD is correctly
    identified as a sensitive human NOAEL or BMDL.

30
Comparison of RfD Values for Three Compounds with
an IRIS RfD of 0.03
31
Strengths and Limitations
  • Strengths
  • Method shows how different factors result in RfDs
    with different probabilities of being correctly
    identified as a sensitive human NOAEL.
  • Method is straightforward and simple and can be
    used to judge among given RfDs or used to
    standardize all RfDs.
  • Limitations
  • Method assumes a similar distribution for all
    factors although conservative, it may not
    represent all chemicals.
  • The probability is the likelihood that the stated
    RfD is a sensitive human NOAEL, rather than
    describing the probability of a response in a
    population.

32
Case Study 21Robinan Gentry Cynthia Van
Landingham, EnvironLesa Aylward Sean Hays,
Summit
  • Extension of the Benchmark Dose (BMD) method
  • Development of risk values at doses above the
    Reference Dose (RfD)
  • Methylmercury
  • Dose-response information in humans
  • BMDs estimated using biomarkers (i.e., levels
    in hair and
  • cord blood)
  • Multiple BMDs available
  • Sensitive human subpopulation (children exposed
    in utero)

33
4 Approaches
  • Approach 1 - A straight line is drawn from both
    the BMDL and BMD to the RfD, where the RfD is
    considered to be zero risk
  • Approach 2 - The appropriate BMD model is
    extrapolated to the RfD and then the risk at the
    RfD is truncated to zero
  • Approach 3 - The appropriate BMD model is
    extrapolated to the RfD and this risk is allowed
    to stand as an upper bound
  • Approach 4 - The appropriate BMD model is
    extrapolated using a threshold term, where the
    threshold value is judged to be the RfD, or some
    higher value.

34
2 BMDL
1 BMDL
1 BMD
3 BMDL
3 BMD
2 BMD
35
Strengths and Limitations
  • Strengths
  • Use of a biomarkers, typically closer to the
    target tissue
  • Ability to evaluate the potential fraction of
    people exposed above and below the RfD to assess
    the likelihood of adverse effects
  • internal concentration may be extended to an
    exposure level
  • Limitations
  • Uncertainties for other compounds as to the
    relationship between biomarker and effects of
    concern
  • Information characterizing the potential shape of
    the dose-response curve below the BMD/BMDL

36
Summary
  • A wide range of problems exist for which
    different dose-response methods and case studies
    are needed
  • Combined exposures
  • Value of information
  • Illustrating an entire risk assessment
  • In vitro to in vivo extrapolation
  • Assessors must explain choice of a particular
    method and its usefulness in a management
    decision.
  • A standing panel is being formed to review
    additional methods, case studies and
    issue/resolution papers.
  • Additional folks are invited to join the effort.

37
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