Note: The most up-to-date agenda is available in the detailed Program .
On this page:
Agenda
| Time |
Topic |
|
April 24, 2024
|
| 7:45 – 8:50 a.m. |
Entry to campus, registration |
| 9:00 – 9:10 a.m. |
Welcome |
| 9:10 – 9:30 a.m. |
Introductions |
| 9:30 – 10:00 a.m. |
History of NAMs, Where Are We Now, the Way Ahead |
| 10:00 – 10:15 a.m. |
Break |
| 10:15 – 10:35 a.m. |
Overview of NAMs training resources, online tools, and other informatics tools |
| 10:35 – 11:35 a.m. |
Tool Introductions Part 1 (10 minutes per) |
| 11:35 a.m. – 12:50 p.m. |
Lunch (on campus) |
| 12:50 – 2:00 p.m. |
Tool Introductions Part 2 (10 minutes per) |
| 2:00 – 2:15 p.m. |
Break |
| 2:15 – 3:15 p.m. |
Choose your own adventure!
- Opportunity to engage with tool and data experts
- Introduction to R/R Studio
- Chemical Evaluation from Nuts to Bolts: RapidTox and NTA WebApp
|
| 3:15 – 3:30 p.m. |
Flex time |
| 3:30 – 5:00 p.m. |
Concurrent Session #1 (4 options) |
| 5:00 – 5:15 p.m. |
Closing |
| 5:30 – 6:30 p.m. |
Optional Off-Site Networking Event |
|
April 25, 2024
|
| 7:45 – 8:50 a.m. |
Entry to campus |
| 9:00 – 9:30 a.m. |
Open discussion, address day 1 questions |
| 9:30 – 11:00 a.m. |
Concurrent Session #2 (4 options) |
| 11:00 a.m. – 12:00 p.m. |
Lunch |
| 12:00 – 1:30 p.m. |
Concurrent Session #3 (3-4 options) |
| 1:30 – 1:45 p.m. |
Break |
| 1:45 – 3:15 p.m. |
Concurrent Session #4 (3 options) |
| 3:15 – 4:15 p.m. |
Tool Mentoring: All tools and data |
| 4:15 – 5:00 p.m. |
Open discussion and workshop close |
|
April 26, 2024
|
EPA Only
9:00 a.m. – 1:00 p.m. |
EPA-only discussions, likely to include case studies with Program Office and/or regional partners. Under development. |
Descriptions for Agenda Activities
Tool Introductions: 10-minute presentations providing a brief overview and relevant highlights of each tool.
New Tools Sneak Peek: Chemical Evaluation from Nuts to Bolts: Using the NTA WebApp and RapidTox
Engage with and Learn from Tool and Data Experts
- Day 1: Informal chats with tool owners – Ask quick questions to help map out your concurrent sessions. Tool owners and data experts will be available for clarifying questions to help attendees choose which concurrent sessions to attend or focus on based on interest and needs.
- Day 2: Tool Mentoring – Now that you have seen the tools in action, meet with experts to get direction on how you might use the tools for your work. Representatives for all tools, datasets, models, etc., covered during the workshop will be available to answer questions from attendees.
Concurrent Sessions: Concurrent Sessions will offer simultaneous tool deep-dives that participants may choose from. Use one of our suggested Concurrent Session Tracks to inform your session choices or choose your own path! These sessions, led by tool owners, will offer in-depth tool overviews as well as opportunities for participants to engage with the featured tool. (Tracks and session descriptions are still under review.)
| Concurrent Session |
Bioactivity & Hazard |
Exposure |
Chemistry |
Ecotoxicology |
| 1 |
Joint tool session: Part 1 |
httk R Package |
DSSTox/CCD General/Chemistry |
ECOTOX |
| 2 |
Joint tool session: Part 2 |
ChemExpo |
TEST |
SeqAPASS |
| 3 |
AOP Wiki |
SHEDS-HT |
Cheminformatics Analysis Modules |
(attend AOP-Wiki) |
| 4 |
GenRA |
SEEM Case Study |
(Attend GenRA) |
Case Study Session |
Sessions displaying a file icon have materials available for download. Click the icon to navigate directly to the Workshop Materials page.
Bioactivity & Hazard: EPA researchers use rapid chemical screening to test thousands of chemicals quickly and efficiently for potential human and environmental effects. This track will focus on tools that allow you to access and use EPA’s wealth of chemical bioactivity and hazard information to help fill gaps and inform decision-making.
Exposure: EPA's rapid exposure and dosimetry research develops methods, data, tools, models, and approaches to rapidly generate exposure and dosimetry estimates for chemicals and mixtures found in commerce and in the environment. This track will explore the functions of EPA’s exposure forecasting tools, allowing you to generate exposure and dose estimates and more.
Chemistry: EPA’s chemical characterization and informatics research includes models to predict physicochemical properties (e.g., molecular weight, melting point, boiling point, vapor point) and chemical transformation as well as approaches for read-across (a data gap filling technique) and cross-species extrapolation of toxicity. This track will focus on EPA computational tools used for interpreting and predicting chemical and biological data.
Ecotoxicology: EPA’s ecotoxicological assessment models span the sequence of events typical of ecological toxicity, including environmental release, fate and transport, exposure, internal dosimetry, metabolism, and toxicological responses. This track will explore EPA’s ecotoxicology and computational toxicology tools, as well as conceptual frameworks that assemble existing knowledge about biological events that lead to adverse health effects in human populations and ecosystems.
EPA Presenters
Marina Evans
Dr. Marina V Evans is a biomedical engineer in the Center for Computational Toxicology & Exposure within the U.S. EPA. Her Ph.D. focused on development and evaluation of pulmonary models used for clinical measurements. She joined the U.S. EPA with the goal of generating experimental data used to calibrate inhalation PBPK models. An engineer and systems physiologist by training, her research has focused on modeling of multiple organs systems and evaluation using experimental data. At EPA, she has focused on the development of PBPK models and their application in risk assessment.
Logan Everett
Dr. Logan Everett is an experienced scientist with a wealth of expertise in bioinformatics, computer science, genomics, statistics, genetics and molecular biology. His research at CCTE is focused on advancing the application of high-throughput transcriptomics in chemical screening. He received a B.S. in Computer Science and Ph.D. in Genomics and Computational Biology, followed by extensive post-doctoral training in various applications of next-generation sequencing data analysis.
Madison Feshuk
Ms. Feshuk is a biologist in the Center for Computational Toxicology & Exposure. She supports multi-disciplinary scientific research efforts by developing and applying innovative data science solutions. These efforts are crucial to promote the adoption of new approach methodologies (NAMs) and increase data interoperability to ultimately achieve reductions in animal testing and improve environmental risk assessment and regulatory decision-making. Her expertise includes database development and maintenance, data wrangling and analysis, project management, user acceptance testing, and quality evaluation efforts, specifically supporting in vitro chemical screening data in the Toxicity Forecaster (ToxCast)’s invitroDB and legacy in vivo toxicity study curations in the Toxicity Reference Database (ToxRefDB).
Annette Guiseppi-Elie
Dr. Annette Guiseppi-Elie is the Director of the Chemical Safety for Sustainability National Research Program in the Office of Research and Development. Annette first joined EPA in 2015 as the Associate Director for Exposure Science at EPA’s National Exposure Research Laboratory. Annette first joined EPA in 2015 as the Associate Director for Exposure Science at EPA’s National Exposure Research Laboratory. Annette is also a Fellow of the American Institute of Medical and Biological Engineering.
Sakshi Handa
Sakshi Handa currently serves as a Biologist/Data Lead within the Scientific Computing and Data Curation Division (SCDCD) of the Center for Computational Toxicology and Exposure (CCTE). She has been with EPA since 2017, beginning as an ORISE participant in toxicokinetic modeling. She graduated from NCSU with a Bachelor of Science in Biological Engineering. She currently acts as the data lead for Factotum, an internal data curation tool, as well as the related public-facing ChemExpo tool for surfacing consumer product and exposure relevant data.
Kristin Isaacs
Dr. Kristin Isaacs is a Research Physical Scientist in the Center for Computational Toxicology and Exposure at the U.S. EPA. Since 2014, she has been a co-lead of ORD’s Exposure Forecasting (ExpoCast) project under its Chemical Safety for Sustainability National Research Program. Her research focuses on characterizing chemical exposure pathways for human and ecological receptors and developing high-throughput computational approaches for quantifying exposures for use in chemical safety decision-making. She is currently a Government Councilor the Board of Directors of the International Society for Exposure Science and serves on a variety of national and international workgroups related to advancing exposure science.
Marissa Jensen
Ms. Marissa Jensen received her Master's degree in Integrated Biosciences from the University of Minnesota-Duluth, where she was advised by Dr. Carlie LaLone (U.S. EPA/CCTE). Her Master's research focused on broadening the definition of the taxonomic domain of applicability of adverse outcome pathways through bioinformatics approaches. Currently, Ms. Jensen is pursuing a PhD at the University of Minnesota-Duluth continuing under the direction of Dr. LaLone. Her research focus includes furthering adverse outcome pathway application and studying effects of pesticides across multiple species.
Carlie Lalone
Dr. Carlie LaLone's primary research interest is developing tools for researchers and decision makers to extrapolate biological knowledge from one species to the diversity of species and predict chemical susceptibility to species that could never be tested in the laboratory. Her research uses complex bioinformatics approaches and translates them into user friendly pipelines and web-based tools useful for making predictions of chemical susceptibly across hundreds to thousands of species. Therefore, Dr. LaLone's research interests span understanding adverse effects of chemical and non-chemical stressors across species, with an emphasis on aquatic organisms. She leads a research team that integrates computational and laboratory studies to evaluate pharmaceuticals, veterinary drugs, pesticides, endocrine disrupting chemicals, and current chemicals of concern to the Agency. Specifically, the focus of her research is on applied science relative to developing methodology and computer applications to be used in ecological risk assessment, based on sound scientific supporting evidence.
Jason Lambert
Dr. Jason Lambert is a board-certified toxicologist and human health risk assessor in the Center for Computational Toxicology & Exposure within the U.S. EPA, who spent 14 years serving as Chemical Manager for over 30 IRIS or PPRTV human health assessments. In 2007, Dr. Lambert founded an Alternative Methods team which led the integration of read-across into PPRTVs for data-poor chemicals. He has also led or co-authored multiple EPA methods and approaches documents pertaining to chemical mixtures risk assessment. Dr. Lambert earned a PhD (2003) and MS (2001) in Pharmacology and Toxicology, and previously a BS (1998) in biology with a double-major in recombinant genetics and chemistry. His research expertise includes mechanisms of hepatic and gastrointestinal injury and repair, molecular and cellular signal transduction, and development of cellular therapeutics such as recombinant probiotics.
Charlie Lowe
Charles (Charlie) Lowe is a computational chemist in ORD/CCTE/CCED/CCCB. He received his bachelor’s degrees in chemistry and applied mathematics from Marshall University and his doctorate in physical (computational) chemistry from Clemson University. During his postdoctoral research, he gained expertise in the analysis of environmental exposure data generated through non-targeted and suspect screening analyses, constructed machine learning models to predict the amenability of chemicals to LC-MS and developed cheminformatics tools to rapidly acquire, curate, and model environmentally-relevant chemical data. As a principle investigator, his interests involve the continued addition and curation of chemical data for DSSTox, the development of new models for physicochemical properties to support other research within the Agency, and the development of a new database, VSSTox, to capture virtual chemicals not necessarily identified in existing scientific literature. In his free time, he enjoys hiking, cooking, and managing a large collection of plastic models.
Todd Martin
Dr. Todd Martin is an expert in computational toxicology with over twenty years of experience. He is the lead developer of TEST (Toxicity Estimation Software Tool) which allows users to easily estimate toxicity and physical property endpoints from molecular structure.
Jennifer Olker
Dr. Jennifer Olker is the Coordinator for the ECOTOX Knowledgebase in the Center for Computational Toxicology & Exposure within the U.S. EPA. Through the ECOTOX project, Dr. Olker works to support criteria development, assessments, and research in EPA Program Offices, Regions, and ORD using systematic methods to identify and curate ecotoxicity data. In addition, she is involved in research at the Duluth lab on endocrine disruption utilizing in vivo and in vitro assays and the development of Adverse Outcome Pathways. Prior to joining the EPA in 2015, Dr. Olker received her Ph.D. in Integrated Biosciences and was at the University of Minnesota’s Natural Resources Research Institute for more than 10 years conducting research in aquatic and landscape ecology.
Grace Patlewicz
Dr. Grace Patlewicz is a chemist and toxicologist by training, bringing industrial and regulatory experience from both Europe and the US. Her research focuses on the development and application of Quantitative Structure-Activity Relationships ((Q)SARs), a technique that predicts properties of unknown molecules, and read-across for regulatory purposes, a way to use similar substances to predict the toxicity of other similar chemicals. She has authored journal publications and book chapters on numerous topics related to toxicology, chaired various industry groups and has contributed to the development of technical guidance for (Q)SARs, chemical categories and Adverse Outcome Pathways (AOPs) under Organization for Economic Co-operation, and Development (OECD) work programs.
Katie Paul Friedman
Dr. Katie Paul Friedman is a toxicologist in the Center for Computational Toxicology & Exposure within the U.S. EPA. She works with predictive assay and systems biology models to prioritize chemicals and mixtures for further evaluation, with particular expertise in developmental and endocrine toxicities. One of her goals is to modernize and improve prioritization and risk assessment of environmentally-relevant chemicals. As part of her work, Dr. Paul Friedman coordinates and leads endocrine-related computational toxicology research, analyzes high-throughput screening assay data sets, integrates multiple data sources into systems biology models of toxicological relevance for endocrine function, and develops case studies that illustrate the utility of high-throughput screening data for prioritization and risk assessment tasks.
Katherine Phillips
Dr. Katherine Phillips’ research focuses on collecting and curating data relevant to chemical exposure and using machine learning techniques to fill gaps in this data landscape. These techniques have been useful for investigating the proposal of chemical alternatives, as well as plausibility of chemicals identified in non-targeted analysis.
Risa Sayre
Ms. Risa Sayre is researching spatiotemporal statistics for exposure modeling Center for Computational Toxicology & Exposure at the U.S. EPA. An as ORISE research participant, Dr. Sayre contributed to several projects within EPA’s ExpoCast project involving machine learning (or machine training, as she thinks it should be called) and evaluation of models used to predict toxicology, toxicokinetics, and exposure.
Celia Schacht
Dr. Celia Schacht is an ORISE Postdoctoral Fellow in the Center for Computational Toxicology & Exposure at the U.S. EPA. She earned her M.S. in applied mathematics and Ph.D. in biomathematics where she focused on characterizing uncertainty and variability in aggregate mathematical models and PBPK models. Her work at the U.S. EPA focuses on developing PBTK models in the utilization of high-throughput toxicokinetics including inhalation and mixtures modeling. Other research interests include code development and programming, uncertainty quantification, and dynamical systems.
Nisha Sipes
Dr. Nisha Sipes brings a multidisciplinary background in engineering, cell and molecular biology, and computational toxicology, as well as a driven passion to increase translation of our research for adoption and ultimate use. Her postdoctoral training at the U.S. EPA involved analyzing the ToxCast high-throughput screening assays, developing predictive models of developmental toxicity, and evaluating the ToxCast assays with respect to their ability to predict broader in vivo outcomes utilizing the high-throughput toxicokinetic modeling (HTTK) approaches. In her professional role in the National Toxicology Program Division at the National Institute of Environmental Health Sciences, Dr. Sipes focused on leveraging in silico methods in HTTK modeling approaches to allow for broader applicability of these approaches to Tox21 chemicals, flame retardants, and potential developmental neurotoxicants. Now back at the EPA, Dr. Sipes aims to facilitate the translation of Center for Computational Toxicology & Exposure’s research for use in decisions and to provide scientific and technical expertise to EPA Program Offices, EPA Regions and outside stakeholder groups with an interest in using CCTE research to inform public health and environmental decisions.
Rusty Thomas
Dr. Rusty Thomas is the Director of the Center for Computational Toxicology & Exposure within the U.S. EPA. His area of expertise is in the application of high-throughput and high data content approaches to chemical toxicity testing. He has a broad, multidisciplinary background and experience but his formal academic training was in chemistry, radiation health physics, and toxicology. He received postdoctoral training in molecular biology and genomics. Following his academic training, Dr. Thomas performed bioinformatics and genomics research in the biotechnology sector and gained experience in high-throughput screening and in vitro assay development in the biopharma sector. Prior to coming to the U.S. EPA, Dr. Thomas worked as an investigator and the director of the Institute for Chemical Safety Sciences at The Hamner Institutes for Health Sciences.
Scarlett VanDyke
Scarlett VanDyke works with the Outreach Stakeholder Engagement and Training team in the Center for Computational Toxicology & Exposure (CCTE) within the U.S. EPA. Scarlett helps communicate CCTE’s research to EPA’s Program Office Partners, Regional representatives, industry professionals, academia, and the general public. Scarlett assists with NAMs training opportunities, such as virtual trainings for the CompTox Chemicals Dashboard and the ECOTOX Knowledgebase.
Dan Villeneuve
Dr. Dan Villeneuve is an aquatic ecotoxicologist in the Center for Computational Toxicology & Exposure within the U.S. EPA. He conducts research with a focus on use of alternatives to traditional in vivo guideline toxicity tests to assess the ecological safety of chemicals. Dr. Villeneuve is heavily engaged in the development and use of the adverse outcome pathway (AOP) framework as a tool for facilitating the use of new approach methodologies in chemical safety assessments and risk-based decision-making. He conducts both laboratory and field research aimed at the development and practical use of biological effects assays for assessing potential adverse effects of organic chemicals. Dr. Villeneuve is also engaged in development and evaluation of high throughput, transcriptomics-based, aquatic toxicity assays for chemical screening and prioritization.
Taylor Wall
Mr. Taylor Wall collaborates on various data curation projects within the Data Extraction & Quality Evaluation Branch (DEQEB). Areas of focus include chemical exposure and toxicology with notable projects including development of the Multimedia Monitoring Database (MMDB) under Dr. Kristin Isaacs and development of automated workflows for the Concentration versus Time Database (CvTdb) under Dr. John Wambaugh. He is also the product lead for the development of the Data Accuracy Tool (DAT), which is designed to be a browser-based application for standardizing dataset quality control (QC) and managing data provenance of any dataset. His graduate research focused on the experiences of lay counselors providing a novel family therapy to improve child mental health in Eldoret, Kenya.
John Wambaugh
Dr. John Wambaugh finds solutions that capture the essence of complex problems. He co-leads the EPA's ExpoCast project (Exposure Forecasting), the aim of which is to identify the chemicals to which people are the most exposed. Working with the ToxCast team, ExpoCast develops high throughput tools to prioritize among commercial chemicals based on risk posed to public health. These tools include exposure assessment, toxicokinetics, and toxicity testing. They use math modeling, machine learning, and statistics to better understand existing data. They also design new experiments to fill data gaps. ExpoCast research helps to identify chemical public health risks while reducing animal testing.
Tony Williams
As a Title 42 Principal Investigator, Dr. Williams is focused on the application of cheminformatics to support multiple projects in the center. These include the development of the DSSTox database that underpins the CompTox Chemicals Dashboard, structure standardization approaches to support QSAR modeling, and the development of informatics systems to support non-targeted analysis mass spectrometry. Dr Williams conceived the Comptox Chemicals Dashboard (https://comptox.epa.gov) and was the product owner for six years and eleven releases. He is responsible for managing the development of a number of informatics prototypes to support the mission of the U.S. EPA. Dr. Williams applies his analytical science skills in developing informatics approaches to support mass spectrometry based non-targeted analysis.