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Computational Toxicology Research Program

2007 International Science Forum on Computational Toxicology

Note: EPA no longer updates this information, but it may be useful as a reference or resource.

Forum Agenda

Download the Printable PDF version of the Agenda

Day 1 – Monday, May 21, 2007

Time Opening Events
1:15 PM Welcoming Remarks – Bob Kavlock, U.S. EPA/ORD/NCCT
1:30 PM Opening Address – George Gray, Assistant Administrator for Research and Development and EPA Science Advisor, U.S. EPA

Session I: Plenary Session
2:00 PM Introduction – Multi-Scale Modeling of Tissues – Rory Conolly, U.S. EPA/ORD/ NCCT
2:10 PM A Quantitative Understanding of Dynamic Cellular Processes During Detoxification in Human Hepatocytes (Research Network Within HepatoSys) – Matthias Reuss, Universität Stuttgart, Institut für Bioverfahrenstechnik
2:40 PM Break
2:55 PM The National Biomedical Computation Resource: Computing Technology to Support Development of Computational Tissues – Wilfred Li, San Diego Supercomputer Center, University of California, San Diego
3:25 PM Towards the Virtual Human: Development of Three Dimensional Organ Models for Human Health Risk Assessment – Richard Corley, Pacific Northwest National Laboratory
4:15 PM Mechanistic Cardiac Modeling and Risk Assessment – Anna Georgieva, Novartis
4:45 PM The Virtual Liver Project at the U.S. EPA's National Center for Computational Toxicology and Its Implications for the EPS Mission to Protect Human Health – Imran Shah, U.S. EPA/ORD/NCCT
5:15 PM Break

Time Evening Sessions
5:30 PM Poster Session: Computational Approaches to Risk Assessment
7:30 PM Evening Address: Climate Change: Understanding the Past and Forecasting the Future – Gabriele Hegerl, Duke University
8:30 PM Adjourn

Day 2 – Tuesday, May 22, 2007

Session II: Concurrent Sessions
Time Track A

Signaling as a Determinant for Systems Behavior

Session Co-Chairs: Timothy Elston, University of North Carolina and Imran Shah, U.S. EPA/ORD/NCCT
Track B


Session Co-Chairs: Steve Bryant, NCBI, NIH and Ann Richard, U.S. EPA
8:00 AM


10:00 AM

Computational and Experimental Analysis of Feedback Regulation in Signal Transduction Pathways – Timothy Elston, University of North Carolina

PDGF Receptor-Mediated Signal Transduction: From nm to cm – Jason Haugh, North Carolina State University

Temporal Coding of ERK Signaling Network – Shinya Kuroda, University of Tokyo

Combined, Data-Driven Biomedical Outcome Prediction and Interaction Network Inference from Molecular Profiling Data – Roland Somogyi, Biosystemix, Ltd.

Computational Toxicology – Where Is the Data? – Richard Judson, U.S. EPA/ORD/NCCT

PubChem: An Open Repository for Chemical Structure and Biological Activity Information – Steve Bryant, National Center for Biotechnology Information (NCBI), National Institutes of Health (NIH)

Integrative Pharm-Tox and the NCI-60: Genomics, Proteomics, and Bioinformatics – John Weinstein, National Cancer Institute, NIH

Understanding Toxicity through Chemical and Biological Fingerprints – Chihae Yang, Leadscope, Inc.

Development and Use of Predictive Hazard Modeling in the Categorization and Screening of Existing Substances at Health Canada – Bette Meek, Health Canada

10:00 AM Break

Session III: Concurrent Sessions
Time Track A

Systems Biology Models of the HPG Axis

Session Co-Chairs: Karen Watanabe, Oregon Health & Science University and Michael Breen, U.S. EPA/ORD/NCCT
Track B

Molecular Modeling for Assessing Chemical Toxicity

Session Co-Chairs: Sean Ekins, University of Maryland at Baltimore and James Rabinowitz, U.S. EPA
10:30 AM


12:30 PM

Mathematical Model of Steroidogenesis in Fathead Minnow Ovaries to Predict Biochemical Responses to Endocrine Active Compounds – Michael Breen, U.S. EPA/ORD/NCCT

A Physiologically-Based Computational Model of the HPG Axis in Fathead Minnows: Predicting Effects of Endocrine-Disrupting Chemical Exposure on Reproductive Endpoints – Karen Watanabe, Oregon Health & Science University

Driving Towards the Boundary between Tissue Dosimetry and Dynamics through Integration of Receptor Binding and Pharmacokinetics in a PBPK Model for Estradiol – Justin Teeguarden, Pacific Northwest National Laboratory

Modeling the Ecological Effects of Endocrine Active Compounds on Fish: Scaling from Individuals to Populations – Kenneth Rose, Louisiana State University

Introduction – Virtual Screening for Chemical Toxicity: A Tool for Deriving Hypotheses and Determining Testing Priorities – James Rabinowitz, U.S. EPA

Motion and Antagonism of the Human Xenobiotic Receptor PXR – Matt Redinbo, University of North Carolina

Combining Structure-and-Ligand-Based Approaches to Model Receptor-Mediated Toxic Effects – Markus Lill, Purdue University

Applications of QSAR to Drug Metabolizing Enzymes – Sean Ekins, University of Maryland at Baltimore

Mapping of Proteins for the Binding of Functional Groups from Xenobiotics – Sandor Vajda, Boston University

12:30 PM Lunch (on your own)

Session IV: Plenary Session
Time Computational Tools for Ecological Risk Assessment

Session Chairs: Donald Tillitt, U.S. Geological Survey and
Daniel Villeneuve, U.S. EPA/ORD/NHEERL
1:30 PM Application of Computational Modeling for Assessing the Ecological Risk of Chemical and Non-Chemical Stressors – Nico Van Straalen, Vrije Universiteit
2:15 PM Mining Minnows and Building Models: An Integrated Systems Biology Approach to Link Mechanism of Action to Ecologically-Relevant Outcomes – Daniel Villeneuve, U.S. EPA/ORD/NHEERL
2:45 PM Break
3:15 PM Toxicology Versus Ecology in Population-Level Risk Assessment for Wildlife: What Data Does Your Modeler Really Need? – Matthew Etterson, National Research Council Post-Doc with U.S. EPA/ORD/NHEERL
3:45 PM Keystone Genes in Evolving Genetic Networks – Stephen Proulx, Iowa State University
4:15 PM It's Not the Warming – It's the When and Where of Water – John Petterson, Sequoia Foundation and Impact Assessment, Inc.
4:45 PM Adjourn

Day 3 – Wednesday, May 23, 2007

Session V: Concurrent Sessions
Time Track A

Predicting the Environmental Fate and Transport of Chemical Contaminants
Session Chair: Eric J. Weber, U.S. EPA
Track B

Drug Discovery Techniques for Prioritization

Session Co-Chairs: Raymond Tice, NTP/NIEHS and Keith Houck, U.S. EPA/ORD/NCCT
8:00 AM


10:00 AM

Predicting Chemical Properties and Fate at the Screening Level Using the Estimation Programs Interface (EPI) Suite of Models – Robert Boethling, U.S. EPA/OPPT

Calculating Physiochemical Properties for Environmental Modeling Using SPARC – Lionel Carreira, University of Georgia

Using CATABOL to Predict Persistency, Biodegradation Pathways and Stable Degradants of Chemicals – Ovanes Mekenyan, Bourgas "Prof. As. Zlatarov" University

Modeling Environmental Fate Constants, Vapor Pressure, Partitioning, Solubility, and Environmentally Important Reaction Mechanisms– Christopher Cramer, University of Minnesota

Bioactivity Profiling of Environmental Chemicals – Raymond Tice, NTP/NIEHS and Keith Houck, U.S. EPA/ORD/NCCT

Cellular Systems Biology Profiling of Environmental Chemicals– Kate Johnston, Cellumen, Inc.

Complex Human Cell Systems for Understanding Toxicity Mechanisms– Ellen Berg, BioSeek, Inc.

Toxicity Profiling of Nanomaterials – Fanqing Frank Chen, Lawrence Berkley National Laboratory

Alternative Models of Toxicity – Thomas Hartung, ECVAM/JRC

10:00 AM Break

Sessions VI: Concurrent Sessions
Time Track A

Dose-Response and Uncertainty

Session Co-Chairs: Wout Slob, RIVM and Woodrow Setzer, U.S. EPA
Track B

Using Genomics to Predict Potential Toxicity

Session Co-Chairs: Rusty Thomas, The Hamner Institutes for Health Sciences and David Dix, U.S. EPA
10:30 AM


12:30 PM

Probabilistic Approaches to Hazard Characterization and Integrated Probabilistic Risk Assessment – Wout Slob, RIVM

Characterizing Dose-Response Model Uncertainty Using Model Averaging – Matt Wheeler, CDC/NIOSH

Quantifying Variability and Uncertainty with PBPK Models – Harvey Clewell, The Hamner Institutes for Health Sciences

Comparison and Evaluation of Sensitivity Analysis Methods for Probabilitic Risk Assessments – H. Christopher Frey, North Carolina State University

Introduction: Predictive Toxicogenomics as a Component of the ToxCast™Program – David Dix, U.S. EPA

Identifying Gene Expression Biomarkers to Predict Rodent Cancer Bioassays – Rusty Thomas, The Hamner Institutes for Health Sciences

Prediction System for Chemical Safety using Percellome Toxicogenomics – Jun Kanno, National Institute of Health Sciences, Japan

Application of In vitro Toxicogenomics towards Drug Safety Evaluation – Jeff Waring, Abbott Laboratories

Characteristics of In Vivo and In Vitro Toxicogenomic Signatures Predictive of Toxicological Outcomes – Mark Fielden, Roche Palo Alto, LLC

Utility of Genomics and HTS Approaches for the Assessment of Industrial Chemicals – Philip Sayre, U.S. EPA

12:30 PM Lunch (on your own)

Session VII: Plenary Session
Time Genetic Variation, Gene-Environment Interactions and Environmental Risk Assessment
Session Chairs: Elaine CohenHubal, U.S. EPA and Richard Judson, U.S. EPA
1:30 PM Population Genetics Analysis Techniques for Finding Gene-Environment Interactions – Clay Stephens, Motif BioSciences, Inc.
2:10 PM Pharmacogenomics: Science and Translation – Richard Weinshilboum, Mayo Clinic
2:50 PM Break
3:05 PM The Epigenetic Determinants of the Early Life Programming of Disease – Amanda Drake, University of Edinburgh

Time Closing
3:45 PM Closing Remarks
4:00 PM Adjourn

Plenary Sessions

Virtual Tissues – The Next Big Step for Computational Biology. Implications for Toxicology and Risk Assessment: Relatively simple computational models of biological systems, best exemplified by PBPK models, have provided a new level of rigor for the analysis of the pharmacokinetic data and for our understanding of how pharmacokinetics influences dose-response. The "omics" revolution in the laboratory, and parallel developments in computer software and hardware, have moved the idea of virtual tissues (VT) from the realm of science fiction to forming the basis for a new, if ambitious, field of research. The potential payoffs from development of VT in toxicology are significant. VT development will build on current successes with PBPK modeling and take the development of quantitative descriptions of biological mechanisms to a new level of complexity. VT will have much greater capabilities than PBPK models for providing insights into dose-response and time-course behaviors and will promote inclusion of larger amounts of integrated biological data into risk assessment.

Computational Tools for Ecological Risk Assessment: Ecological risk assessments need to focus on responses across multiple biological levels of organization. An understanding of processes at molecular, biochemical and cellular levels of organization enables insights into mechanisms underlying biological changes and, as such, provides a basis for extrapolation across species and chemicals. However, to make decisions about possible risk it is necessary to link alterations at these lower levels of organization to adverse effects in individuals and populations. An ultimate goal would be to understand how changes in populations of plants or animals affect specific ecosystems. This session will explore how computational approaches can be used as the basis for understanding and predicting effects of chemical stressors across the biological continuum of molecules to ecosystems.

Genetic Variation, Gene-Environment Interactions and Environmental Risk Assessment: It is well known that different species and individuals within species react in different ways to identical exposures to environmental chemicals. This is in part driven by genetic variation in systems ranging from adsorption, transport, metabolism and receptor interactions. Understanding the mechanisms behind variable response can help determine vulnerable individuals and species. This can in turn drive testing protocols and (potentially) regulatory thinking. Additionally, performing toxicogenomic experiments in genetically heterogeneous populations can help to determine the connectivities in complex biochemical networks. Application of emerging tools in molecular biology is facilitating investigation of genetic contributions to consequences of environmental exposures. The objective of this session is to consider available tools and approaches for studying gene-environment interactions with a specific focus on improving environmental risk characterization.

Concurrent Sessions

Signaling as a Determinant for Systems Behavior: The goal of this session is to describe how biological signaling processes lead to overall systems behaviors (e.g., dose-response relationships). Modeling simpler and more complex systems provides insights into how different regulatory modules function. The modeling can provide insights into the relationships between the behaviors of parts of the system and the overall behavior when the parts are combined. Once the behavior of the biological system has been described, questions can be raised about perturbations of the system. Such perturbations can include altered physiological states (e.g., stress), disease states, and exposures to pharmaceutical or environmental compounds.

Toxico-Cheminformatics: This session will cover the integration of chemical and toxicity data, toxicity data models, chemoinformatics, and the harnessing of legacy toxicity data to advancing predictive technologies.

Systems Biology Models of the HPG Axis: Over the past decade there has been a focused international effort to identify possible adverse effects of endocrine active compounds (EAC) on humans and wildlife. Effects on development, reproduction, aging, and hormone-sensitive cancers mediated through alterations in the hypothalamus-pituitary-gonadal (HPG) axis have been of particular concern. The development and application of computational models of the HPG axis can improve our understanding of the complex linkages between chemical exposures, biological dose, and effects of EAC to help predict the dose-response behavior and identify predictive biomarkers indicative of adverse effects. This session will focus on the development of computational models of the HPG axis at all levels of biological organization (i.e. intracellular, tissue, multi-organ systems), and the use of EAC to perturb the HPG axis to understand function and/or dynamic.

Molecular Modeling for Assessing Chemical Toxicity: This session will cover research modeling the modes and mechanisms for chemical toxicity from the viewpoint of the physico-chemical interactions between molecules in biological systems. This will deal primarily with a causal approach to this problem. It will also include advanced methods that increase the speed of these computationally rigorous applications so they may be used for screening.

Predicting the Environmental Fate and Transport of Chemical Contaminants: Exposure assessment requires knowledge of the environmental concentration and speciation of the chemical contaminant(s) of interest. This session will focus on: (1) the presentation of the computational tools currently available for predicting/simulating the fate and transport of chemicals in the environment; and (2) the identification of the most significant sources of uncertainty concerning our ability to predict chemical fate and transport.

Discovery Techniques for Prioritization: Use of modern drug discovery technologies, including high-throughput biochemical and cellular assays, provides a new opportunity to survey environmental chemicals for potential for hazard. This session will focus on methods traditionally used in the drug discovery process for characterizing the bioactivity of small molecules with regard to target specificity and toxicity and how they can be applied to the field of environmental toxicology.

Dose Response and Uncertainty: This session will examine some issues surrounding probabilistic dose-response assessments. While the Agency has some experience using probabilistic methods in risk assessment, virtually all of it is in using probabilistic methods to characterize uncertainty and variability in exposure. The goals of this session are to: (1) explore some methods for better characterizing the uncertainties inherent in estimating dose-response from toxicity data; (2) look at issues involved in extrapolating from animal to human dose-response: (3) look at approaches to dose-response assessment that probabilistically characterize uncertainty.

Using Genomics to Predict Potential Toxicity: Genomics provides detailed molecular data about the underlying biochemical mechanisms of disease or toxicity, and could represent sensitive measures for detecting effects of environmental exposures. Thus genomics can provide useful data along the source-to-outcome continuum, when appropriate bioinformatic and computational methods are available for integrating molecular, chemical and toxicological information.

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