Categorical Default Approaches to Uncertainty Factor Development in - PowerPoint PPT Presentation

Categorical Default Approaches to Uncertainty Factor Development in y p Chemical Risk Assessment John C. Lipscomb PhD, DABT, F.A.T.S. National Center for Environmental Assessment Assessment, Office of Research and Development, U. S. Environmental Protection Agency, Ci Cincinnati, OH i ti OH

Where Does this Fit in Human Health Risk Assessment? Risk Assessment? NAS 4-Step Paradigm Hazard Assessment & Characterization & Characterization Dose Response Assessment Exposure Assessment & Characteri ation & Characterization & Characteri ation & Characterization Risk Assessment & Risk Assessment & Characterization

Mode Mechanism Detailed Detailed Plausible Plausible Molecular Hypothesis with Description p Measured Key Measured Key of Causality Events Key event: Critical Quantifiable

MOA/HR (WOE) Framework Q1. Is the weight of evidence sufficient to establish the MoA in animals? I Implications of li ti f Kinetic & Dynamic Q2. Fundamental qualitative Data for Data for differences in key events? differences in key events? Dose– Response Q3 Fundamental quantitative Q3. Fundamental quantitative differences in key events?

Biologically (MoA) (MoA) Default Default Based Reference/Acceptable/ Reference/Acceptable/ Tolerable Intakes = N/LO(A)EL or BMC/D N/LO(A)EL BMC/D � Kinetics UF � Dynamics U Uncertainty Factor i F Interspecies Differences ( 10) (x10) Human Variability (x10) Ad Adequacy of database f d t b (x1-100) 5

The Continuum Default � Data-Informed � Default – 10 x 10 � Database - Derived - databases of information, , not group or chemical-specific � Categorical - applies to categories of substances/species based on their characteristics (BSA substances/species based on their characteristics (BSA correction; RFC - gases/particles) � Chemical Specific Adjustment Factors - p j addressing kinetic or dynamic aspects with chemical specific or compound-related information � Fully Data-Derived – biologically-based dose- Fully Data Derived biologically based dose response modelling addressing kinetic and dynamic aspects 6

Where Are We Trying to Go in A Ri k C Risk Context? t t? � Greater predictive power � Higher relevance Hi h l � Moving from default to more biologically b based d � Relevant pathways � Relevant doses Relevant doses � Relevant species

U.S. NRC/NAS Toxicity Testing in the 21 st Century Dose Response Dose Response Assessment Chemical Mode of Action M d f A ti Characterization Population Based Studies C Compounds d Affected Dose Response Pathway Calibrating Analysis for Exposure in vitro and human Perturbations Guideline Assess Dosimetry of Toxicity Biological Pathways Perturbation Perturbation Measures of dose in vitro Metabolite(s) Human Exposure Data Hazard Characterization Exposure Assessment E p u m n Risk Characterization

Categorical Default Approaches to Uncertainty Factor Development in y p Chemical Risk Assessment John C. Lipscomb PhD, DABT, F.A.T.S. National Center for Environmental Assessment Assessment, Office of Research and Development, U. S. Environmental Protection Agency, Ci Cincinnati, OH i ti OH

Categorical Default Approaches to Uncertainty Factor Development in - PowerPoint PPT Presentation

Categorical Default Approaches to Uncertainty Factor Development in y p Chemical Risk Assessment John C. Lipscomb PhD, DABT, F.A.T.S. National Center for Environmental Assessment Assessment, Office of Research and Development, U. S.

Methods for handling uncertainty Default or nonmonotonic logic: Assume my car does not have a

Methods for handling uncertainty Default or nonmonotonic logic: Assume my car does not have a

Uncertainty, Default, and Risk (Welch, Chapter 06-2) Ivo Welch Previous Slides In Perfect

Connecting the categorical and the modal logic approaches to Quantum Mechanics Giovanni Cin` a

Uncertainty, Default, and Risk (Welch, Chapter 06-A) Ivo Welch Maintained Assumptions Perfect

Chapter 12 Dealing with default information CS4811 Artificial Intelligence Nilufer Onder

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F ACTOR graph [1], [2], or more often referred to as the classical factor graph (CFG) in this

Reasoning under Uncertainty: Reasoning under Uncertainty: Issues and Other Approaches Issues and

Estimating Uncertainty of Categorical Web Data Davide Ceolin, Willem Robert van Hage, Wan

Decision-making under uncertainty: Robust approaches for adapting to climate change using

Interval and Symmetry What Do We Know . . . Approaches to Uncertainty Natural . . . What

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Introduction to categorical approaches in topological data analysis I Steve Oudot Inria

An insight into output gap uncertainty: improving total factor productivity cycle estimates by

1 Estimation from outbreaks when R 0 < 1 Estimating R 0 : from epidemic data If case data are

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UNCERTAINTY IN KNOWLEDGE Ch. 9 Uncertainty in Knowledge 1 Sources of Uncertainty

Categorical Default Approaches to Uncertainty Factor Development in - PowerPoint PPT Presentation

Categorical Default Approaches to Uncertainty Factor Development in y p Chemical Risk Assessment John C. Lipscomb PhD, DABT, F.A.T.S. National Center for Environmental Assessment Assessment, Office of Research and Development, U. S.

Methods for handling uncertainty Default or nonmonotonic logic: Assume my car does not have a

Methods for handling uncertainty Default or nonmonotonic logic: Assume my car does not have a

Uncertainty, Default, and Risk (Welch, Chapter 06-2) Ivo Welch Previous Slides In Perfect

Connecting the categorical and the modal logic approaches to Quantum Mechanics Giovanni Cin` a

Uncertainty, Default, and Risk (Welch, Chapter 06-A) Ivo Welch Maintained Assumptions Perfect

Chapter 12 Dealing with default information CS4811 Artificial Intelligence Nilufer Onder

New Approaches to the Analyses of Financial Behaviour under Uncertainty H el` ene Rey

Uncertainty-Aware Lookahead Factor Models for Improved Quantitative Investing Lakshay Chauhan,

F ACTOR graph [1], [2], or more often referred to as the classical factor graph (CFG) in this

Reasoning under Uncertainty: Reasoning under Uncertainty: Issues and Other Approaches Issues and

Estimating Uncertainty of Categorical Web Data Davide Ceolin, Willem Robert van Hage, Wan

Decision-making under uncertainty: Robust approaches for adapting to climate change using

Interval and Symmetry What Do We Know . . . Approaches to Uncertainty Natural . . . What

CHiME Challenge: Approaches to Robustness using Beamforming and Uncertainty-of-Observation

Quantum Factor Graphs: Closing-the-Box Operation and Variational Approaches End-of-Second-Year

Robust Solution Approaches for Optimization under Uncertainty: Applications to Air Traffic

Robust Optimization Approaches for PDE-Constrained Problems under Uncertainty Stefan Ulbrich

Introduction to categorical approaches in topological data analysis I Steve Oudot Inria

An insight into output gap uncertainty: improving total factor productivity cycle estimates by

1 Estimation from outbreaks when R 0 &lt; 1 Estimating R 0 : from epidemic data If case data are

Optimal and Heuristic Approaches for Constrained Flight Planning under Weather Uncertainty Florian

Uncertainty AIMA Chapter 13 Outline Uncertainty Uncertainty Probability Syntax and

Remediation Management of Complex Sites: Tools and Approaches to Reduce Uncertainty Federal

UNCERTAINTY IN KNOWLEDGE Ch. 9 Uncertainty in Knowledge 1 Sources of Uncertainty

1 Estimation from outbreaks when R 0 < 1 Estimating R 0 : from epidemic data If case data are