Professional Training Courses

The purpose of professional training courses is to provide educational opportunities to the membership and guests. The focus is on selecting cutting-edge and general scientific topics of interest. In addition, non-scientific courses that support skills scientists might need to succeed, for example communication or presentation skills, are offered. The courses are taught by experts in the field.

Reserve your spot in a professional training course when you register for the meeting. You can also add a course to your existing registration by visiting the SETAC Store.

Please note, training courses will be presented on site in Pittsburgh and will not be live-streamed or recorded.

Pricing

Sunday Full-Day Courses

8:00–17:00 | 13 November

Instructors: Ellen Mihaich, ER2 and Duke University; Steve Levine, Bayer CropScience; Katie Paul-Friedman, USEPA; Antony Williams, USEPA

In response to concerns that certain environmental chemicals might interfere with the endocrine system of humans and wildlife, regulations have been promulgated around the world targeting the evaluation of these types of effects. The purpose of this short-course is to address key topics related to endocrine system evaluation and regulatory requirements around the world. The course provides basic information on vertebrate endocrine systems, mechanisms of control, and adverse effects. The focus is the estrogen, androgen, and thyroid systems, although new endocrine system targets will be discussed. The requirements of the ECHA/EFSA Guidance document (2018) and the US EPA’s Endocrine Disruptor Screening Program will be presented. As such the course will cover regulatory needs for pesticides, biocides and REACH substances, including the development of definitions and criteria in the EU. Screens and tests used in these programs are discussed, including plans for the evolution of the US EPA program, with the use of high throughput in vitro assays, in silico modeling, and adverse outcome pathways. Use of weight of evidence evaluations in interpreting the data will be covered. Finally, an interactive simulation will be staged where groups of participants can engage in a transparent and quantitative weight of evidence evaluation of data.

Room 316

Instructors: Kelsey Thompson, Harvard University; Joseph Bisesi, University of Florida; Chris Martyniuk, University of Florida

The analysis of microbial communities is challenging due to their biological and bioinformatic complexity. A variety of culture-based and molecular assay are available, the latter of which especially can generate diverse, noisy data with no one clear “best” analysis method. This is especially true for environmental microbiomes, since common analysis methods are often easiest for human-associated microbiota. This course will provide a brief introduction to microbial community analysis techniques appropriate for both host-associated and free-living microbiomes, based on amplicon and metagenomic sequencing. The course will include lectures and discussions around sample collection, extraction, library prep and sequencing, short background lectures and several hands-on tutorials. Processing of data from raw reads through the generation of taxonomic and functional feature tables and the subsequent approaches for data visualization and statistical analysis will be covered. This will include both 16S rRNA gene amplicon sequencing (generalizable to 18S and ITS amplicons) as well as a brief introduction to the analysis of shotgun metagenomics. The course will leverage both the command line environment as well as tutorials in RStudio.

Instructors: Carlie LaLone, USEPA; Sally Mayasich, University of Wisconsin Madison; Marissa Jensen, University of Minnesota Duluth

Data describing the potential adverse effects of chemicals across species is sparse. Therefore, novel strategies are needed to make use of existing data to understand chemical effects across species. An underutilized data source for purposes of species extrapolation is protein sequence and structural information. To capitalize on these data, bioinformatics approaches are being applied to challenges in extrapolating toxicity data/knowledge across the diversity of species. A tool that has been developed to serve this purpose is the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool, that utilizes this data to predict chemical susceptibility across species based on concepts derived from evolutionary biology. The assumption underlying the SeqAPASS tool is that the greater the similarity between the protein target in a sensitive or model organism to other species, the more likely the protein in the other species functions similarly, either binding to a chemical or performing a similar role in a pathway. This knowledge of conservation across species provides a rapid mechanism for understanding how well model organisms serve as surrogates for other untested species and provides a line of evidence for extrapolation of toxicity or pathway data to other species. This course will provide background information on the SeqAPASS tool, describe the scientific underpinnings, strengths, and limitations of the tool and methodology, and demonstrate best practices for use in cross-species extrapolation. The utility of the SeqAPASS tool for addressing challenges related to species extrapolation in toxicology and regulatory decision-making will be discussed. The course will include a step by step demonstration of each component of the SeqAPASS tool using a predefined case study and hands-on training that would allow for independent use of the SeqAPASS tool. Finally, participants will be provided with relevant case studies to work through and practice their hands-on skills developing SeqAPASS output and evaluating it.

Room 319

Instructors: John W. Green, John W Green Ecostatistical Consulting; Jeffrey C. Wolf, Experimental Pathology Laboratories (EPL), Inc

This course covers statistical considerations of experimental design and analysis to evaluate toxicity of chemicals in the environment, focusing on practical issues and using real ecotoxicity studies as examples. Statistically sound techniques acceptable to regulators to analyzing laboratory ecotoxicity experiments meeting current and near-term future guidelines will be identified and explored. Statistical methods in recently adopted OECD Test Guidelines and proposed new guidelines will be introduced. Participants will learn to identify problematic data that requires specialized analysis and receive practical advice and recommendations, including alternatives where appropriate. Within this course classical and generalized linear and nonlinear mixed models (GLMM & GNLMM) with model averaging are developed for BMDx/ECx estimation, as is NOEC determination when regression fails. Differences between NOEC and ECx are assessed for risk assessment and experimental design, and implication of basing one type of analysis on a design intended for the other are illustrated. Continuous, quantal, count, and severity score (histopath) data are examined. Logical flow-charts and discussion of software for NOEC determination and regression model fitting are presented and computer programs and valuable support documents will be discussed. This course is taught by instructors who are active in the OECD Validation Management Group for Ecotoxicity and in the development of several OECD test guidelines and guidance documents.

Sunday Morning Half-Day Courses

8:00–12:00 | 13 November

Instructors: Bonnie Brooks, Washington Department of Ecology; Brady Johnson, Utah Department of Environmental Quality; Chrissy Peterson, EHS Support; Karen Thorbjornsen, APTIM

Soil background concentrations are important to consider when conducting human health and ecological risk assessments. When performing risk assessment at contaminated sites, soil background values are often permitted to be used if the background concentrations exceed risk-based values. The Soil Background and Risk (SBR) Assessment Interstate Technology Regulatory Council (ITRC) guidance document released December 2021 provides a comprehensive defensible framework for establishing and using soil background in risk assessments. This course will provide the student with an understanding of how to establish soil background and use it in risk assessment of contaminated cleanup site based on the new ITRC Soil Background and Risk Assessment Guidance. It will provide the student with the tools necessary to identify when soil background is important to include, how to establish default and site-specific soil background and how to use it in risk assessment. Instructors will elaborate on topics such as soil background definitions, how to choose a soil background site, soil sampling and soil analytical methods. Students will learn about statistical methods and tests including how to handle dataset distributions, nondetects, outliers and different statistical tests that may be useful when comparing soil background to site concentrations. Instructors will also provide insight into what geochemical evaluations and environmental forensics are, and when they can be used to provide an additional line of evidence. After completion of the training course, students will understand what is in the ITRC SBR guidance and where to locate pertinent topics, identify when soil background should be used in risk assessment, know the difference between natural soil background, anthropogenic soil background, default soil background, site-specific soil background, soil background reference area as defined in the guidance.

Room 320

Instructors: Li Li, University of Nevada, Reno; Holly Barrett, University of Toronto; Dingsheng Li, University of Nevada, Reno; Alessandro Sangion, ARC Arnot Research & Consulting

Over the past several decades, dozens of computer models have been developed to support assessments of chemical exposure and risks. However, for many practitioners, chemical assessments are still challenging due to the lack of a mechanistic understanding of the fundamental principles and tools, data gaps and uncertainties, and a reasonable interpretation of estimation results. This introductory course is designed for undergraduate and graduate students, professionals, researchers, new substance notification preparers, and regulators that are interested in model-based chemical risk estimation and assessment. The “theory” section of this course will provide background information on standard procedures of chemical risk assessment, the rationale of chemical risk estimation tools, fundamental principles of selection, evaluation of appropriate chemical and toxicological data for model inputs, as well as the interpretation of model results. In an interactive “practice” section, participants will have hands-on experience with parameterizing and applying computer models to assess the risk of a case study chemical on humans and ecological receptors. Overall, this course will provide insights into the rationale and methods of a model-based chemical risk estimation, equipping participants with an improved understanding of the key concepts in chemical risk assessment.

Instructor: Hendrik Rathjens, Stone Environmental

The Automated Probabilistic Co-Occurrence Assessment Tool (APCOAT) is freely available software published in 2022 that allows users to rapidly generate probabilistic pesticide usage footprints and species distribution models, and reports on the degree of spatial overlap between them. In this short course, we cover the theory and methods involved in producing pesticide usage and species distributions models, and walk students through running each modeling component using APCOAT. Participants are required to bring their own laptops with the software previously downloaded and installed from https://stone-env.com/APCOAT. The software and associated data are approximately 3GB, and copies will be distributed on USB drives. Knowledge of simple statistical concepts is assumed; advanced knowledge is not expected. With APCOAT, pesticide usage footprints are derived from six probabilistic crop footprints (alfalfa, corn, cotton, rice, soybeans, wheat) multiplied by Percent Crop Treated (PCT) rasters derived from annual pesticide usage time series. APCOAT users may either provide their own annual pesticide usage data time series or query the 315 pesticides included in the USGS ePest dataset and compiled in APCOAT databases. Species distribution models are generated using species location records, biogeographic predictor variable rasters, and the open-source Maxent software, the most widely used algorithm for modeling species’ distributions. Attendees will gain an understanding of the methods used for creating probabilistic pesticide usage footprint rasters and learn to produce pesticide usage footprint rasters at varied spatial resolutions. Attendees will learn to rapidly calculate, report, and interpret the degree of probabilistic spatial overlap (co-occurrence) between pesticide usage sites and species locations.

Sunday Afternoon Half-Day Courses

13:00–17:00 | 13 November

Room 303

Instructors: Ryan Heisler, American Cleaning Institute; Raghu Vamshi, WaterBrone Environmental Inc.

Formulated household and personal care products have become omnipresent in our lives, with our reliance on many of these products for long-term health, comfort, and safety. These products have also garnered the attention of regulators and researchers because of their widespread use and disposal. The chemical safety of formulated consumer products is a high priority for product manufacturers and ingredient suppliers who seek to ensure a clean and healthy future. One accepted method used to ensure the environmental safety of formulated products is applying risk assessments based on chemical hazards and their potential exposure. Potential exposure estimations include environmental (ecological) exposures through releases to aquatic environments, air, or soil. This short course aims to detail the methods used by product manufacturers and regulators to assess environmental exposures associated with formulated consumer products such as home and personal care products to understand related risks of their disposal, post-use, into the aquatic environments, i.e., U.S. surface waters. The focus will be on the fundamentals of risk assessment, emphasizing tiered aquatic environmental exposure assessment. Applications will include both lower (Tier I) and higher tier (Tier II) probabilistic modeling of environmental exposures in aquatic environments across regional and national geographies. Emphasis will be placed on Tier 2 assessment using the iSTREEM® model, a publicly available web-based GIS model. The course will review case studies of iSTREEM® application for common ingredients found in formulated home and personal care products to demonstrate aquatic environmental exposure and risk screening.

Room 320

Instructors: Corinna Singleman, Queens College, CUNY; Laura Langan, University of Baylor

Science communication is key to retaining support of the community and nation, both moral and monetary. Communicating science to scientists is vastly different from communicating science to the public. This short course explores the different communication avenues a scientist has available to them in communicating their science and provides practical steps in creating science writing for the public. During the short course, participants will transform their scientific writings into science writing that is accessible to non-scientist readers. Participants will bring a research or white paper with them, translate that into a press release, which they will learn how to edit appropriately for a general audience. That press release will be shortened into a sound bite and finally the sound bite will be converted into a social media post for their preferred platform (Facebook, IG, Twitter, etc). The course will end with a discussion on how the COVID pandemic has challenged science communicators, highlighting examples of good and bad science communication over the last year.

Instructor: Lawrence Malizzi, Ramboll

The Environmental Unit (EU) is established within hours of a spill under the Incident Command System (ICS) and is responsible for all environmental issues during the response. This course aims to educate participants on roles and uses of science in the EU. One of the primary roles of the EU is to minimize inadvertent injury from the spill product and response activities to natural and cultural resources. Sampling of air, water, soils, and sediment may be conducted to delineate the extent of impacts from the spill product. Waste is also analyzed for characterization and disposal purposes. These tasks require competent scientists with backgrounds in risk assessment, toxicology, environmental science, and geoscience to conduct scientific studies to assess impacts to the environment. Additional EU responsibilities include identifying resources at risk, managing the Shoreline Cleanup Assessment Technique (SCAT) program, and coordinating internal and external environmental stakeholder concerns as they pertain to response activities. The EU does not perform injury assessment to support the Natural Resource Damage Assessment (NRDA) process, but those data collected by the EU may support the NRD settlement. This is a discussion-based, 4-hour workshop taught by experienced spill response consultants who have worked on numerous spills.