Professional Training Courses

Professional training courses are coordinated by the Education and Short Courses Committee based on feedback from previous participants, input from the SETAC membership community, and discussion with the local program committee for the annual meeting. 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.




Full-day Half-day
Member $319.50 $166.50
Student Member $103.50 $58.50
Nonmember $346.50 $202.50
Nonmember Student $112.50 $67.50
Developing Country/
Recent Grad Member
$103.50 $58.50


Full-day Half-day
Member $355 $185
Student Member $115 $65
Nonmember $385 $225
Nonmember Student $125 $75
Developing Country/
Recent Grad Member
$115 $65

Sunday Morning Half-Day Courses

8:00 a.m.–12:00 p.m. | 3 November

Room: 707
Instructors: Sharon Hook, CSIRO; Doris E. Vidal-Dorsch, VDA LCS; Elin M. Ulrich, USEPA; Adam D. Biales, USEPA

Several OMICS techniques, including genomics, transcriptomics, proteomics and metabolomics, are gaining popularity as a research tool in environmental sciences. However, uncertainty in the design, execution and data interpretation of studies employing these techniques can limit their scientific impact. In addition, a lack of clarity regarding OMICS data use in routine monitoring and in a regulatory context has limited the techniques’ adoption. To accelerate the successful incorporation of these approaches in routineary scientific studies conducted by both scientists and regulators, we are offering the short course titled “Omics for Environmental Scientists, Engineers, and Regulators: An Introduction.” This proposed short course is one of three courses to be offered by the OMICS SETAC Interest Group.

This course will provide an introduction to eDNA metabarcoding, transcriptomics, proteomics, metabolomics, and exposomics, as well as an introduction to the methodologies and bioinformatics required for each. In addition, we will discuss “real world” case studies, how OMICS approaches have been successfully used in these case studies and the impact and implications that these approaches have brought. Furthermore, we will provide guidelines for effective experimental design, as well as proven frameworks for data interpretation. Finally, the group will briefly engage in a discussion on the current work undertaken by the OMICS SETAC Interest Group to move the science forward and the efforts taking place to incorporate OMICS tools into regulation.

Room: 711
Instructors: Lynnae Dudley, EcoMetrix Incorporated; Richard Goulet, CNSC/CCSN

Progressive resource development companies manage environmental risks responsibly and proactively at every stage of the project life cycle. An environmental protection system that incorporates environmental risk assessment (ERA) allows companies to protect the public, mitigate impacts to the environment, and respond to changes in industry practices, regulatory expectations, community interests and advances in science.

This course will provide participants with an understanding of:

  • The basic components of ERA
  • Information ERA provides for decision makers
  • How to use ERA for decision making across all stages of a project
  • How to design environmental monitoring to confirm that ERA predictions are met

This course will describe the evolution of an ERA from the environmental assessment, operation and decommissioning stages, use of multi-criteria decision analysis in identifying mitigation measures and environmental monitoring design. Real life experiences will be shared, focusing on our experiences in the uranium and metal mining and waste management sectors. We will illustrate how consistent and periodic comparison of environmental performance to ERA predictions enables compliance verification, environmental trends analysis, and efficiencies in environmental monitoring and management. The role of environmental models in improving environmental understanding, evidence-based decision making, regulatory approvals and public communication will be discussed.

Room: 703
Instructors: Naomi Stock, Trent University; Karla Newman, Trent University

Toxicological research can strongly benefit from mass spectrometry; at a minimum, the technique can be used to confirm nominal concentrations used in a toxicology experiment. This course will provide an introduction and overview of mass spectrometry techniques, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and inductively coupled plasma–mass spectrometry (ICP-MS). As research scientists in a university mass spectrometry facility, instructors Naomi Stock and Karla Newman will provide valuable hints and tips on how to best prepare samples for mass spectrometry analysis, including simple sample extraction and preservation methods. This course will also examine mass spectrometry techniques that may provide additional information for toxicological experiments, such as MALDI Imaging, untargeted analysis, identification of metabolites or degradation products, nanoparticle characterization and quantification, and the use of stable metal isotope labelling. Other scientists who would like to learn about mass spectrometry are also welcome to attend.

Room: 704
Instructors: Christoph Koffler, thinkstep Inc.

Life cycle assessment (LCA) is an analytical method that aims to quantify potential environmental impacts along the entire life cycle of a product, from extraction or harvest of natural, mineral, or fossil resources through production, distribution, and consumption to final endof- life disposal or reuse/recycling. LCA provides a quantitative evaluation of a wide range of environmental issues to avoid “burden shifting” between different life stages or different environmental concerns. Its primary applications include decision support in the context of design-for-environment programs and policy making as well as providing a science-based basis for environmental claims used for marketing products in business-to-business (B2B) and business-to-consumer (B2C) settings.

The course will convey the general principles and relevant definitions of the LCA methodology as defined in the ISO 14040 series of standards and exemplify them through frequent reference to real-world case studies covering a wide array of industry sectors and product categories. The overall goal of the course is to provide the skills necessary to scope, manage, and scrutinize LCA studies in the business, consulting, or government sectors.

Sunday Afternoon Half-Day Courses

1:00 p.m.–5:00 p.m. | 3 November

Room: TBD
Instructors: Laure Patouillard, CIRAIG, Polytecnhique Montréal; Cécile Bulle, CIRAIG, ESG UQAM

Most of the impact categories accounted for in life cycle impact assessment (LCIA) are regional or local impacts. However, the majority of LCIA methodologies currently offer generic characterization factors (CFs), not allowing to account for the spatial variability of impacts except for their geographical converage (e.g. Europe for ReCiPe). Novel LCIA methodologies LC-IMPACT and IMPACT World+ (IW+) provide spatially explicit CFs for various impact categories. IW+ addresses the need for a regionalized LCIA method covering the entire world, addressing uncertainty related to spatial variability and implementing state-of-the-art characterization modelling approaches. This methodology proposes three distinct complementary viewpoints to present an life cycle assessment (LCA) profile: midpoint impacts, damages on areas of protection and damages on areas of concerns.

This training course aims to provide an overview of regionalization in LCIA and deconstruct the myths of being too sophisticated and hardly applicable in the LCA practice. Illustrated with IW+, participants will learn how to enhance the interpretation capability in LCA through regionalization. The course is structured with a theoretical part exposing the basic concepts of LCIA and regionalization and a practical part based on a case study through an LCA software.

Room: 707
Instructors: Anže Županič, National Institute of Biology; Živa Ramšak, National Institute of Biology; Adam Biales, USEPA; Weichun Huang, USEPA

Advancements in technology have enabled us to measure the abundance of biomolecules present in biological systems in a high-throughput fashion. For instance, transcriptomics utilizes array technology and next-generation sequencing to measure the abundance of RNA transcripts, while metabolomics utilizes mass spectrometry to measure different types of small molecules, such as sugars, acids and lipids. In environmental toxicology, the standard experimental design is to identify individual biomolecules that change after perturbation of a biological system using chemical or physical stress. As a result, one obtains lists of genes, epigenetic regions, proteins or metabolites that are either differentially expressed or changed between experimental conditions. To be able to better interpret these results, one needs to put them into the context of existing biological knowledge or combine them with other experimental data.

In this short course, we will present a set of state-of-the-art methodologies that can be used for analysis, interpretation of omics datasets and their integration. The course will focus on transcriptomics datasets obtained by RNA-seq and epigenetic datasets obtained by reduced representation bisulfite sequencing (RRBS). For transcriptomic datasets, we will first quickly summarize the main characteristics of the datasets and explain the standard analysis methods: pathway enrichment analysis which moves the analysis from individual genes to higher level biomolecular pathways and data clustering which can be useful, for example, for chemical classification. We will continue with correlation network analysis, which can provide information on genes that serve similar functions, and integration of omics with toxicity pathways, which can be used for hazard assessment. For RRBS data, we will mainly focus on its experimental design, data analysis methods, visualization and integrated interpretation with RNA-seq expression data. For each method, we will present what type of data (experimental design) you require for the method to work optimally, what applications it is useful for and what open-source and proprietary tools are available for their execution. Since many of the described methods are network based, the course will include a short demonstration of the network analysis software Cytoscape, which will be used to explore the prepared precalculated examples.

Room: 703
Instructors: Jessica D’eon, University of Toronto; Shira Joudan, University of Toronto; Sivani Baskaran, University of Toronto; Rachel Hems, University of Toronto

All environmental research includes some chemistry, however many self-identified non-chemists perceive the subject to be an insurmountable obstacle. Here we present an environmental chemistry primer aimed at non-experts from biology and engineering that will provide participants with an appreciation for the role of chemistry in their environmental research.

The first half of the course will cover chemical partitioning and relevant chemical transformations. The discussion of chemical partitioning will include bioavailability, bioaccumulation, chemical exposure, and environmental distribution. The discussion of chemical transformations will include typical chemical reactions in the atmosphere, water, and biological systems.

The second half of the course will include chemical property prediction for chemical reactivity, partitioning, and bioaccumulation potential. Participants will learn how and when to use predictions, and the limitations behind them. Case studies will be used to demonstrate how molecular structure drives environmental fate. Pre-course surveys will be used to tailor this content to participant interest.

This course was originally developed as part of a Green Chemistry initiative in 2018 by graduate students in the Department of Chemistry at University of Toronto. All four instructors will present the material and actively engage with participants. The take home message of this course is that chemistry is fun!

Room: 711
Instructors: Jeremy L. Conkle, Texas A&M University Corpus Christi; Samantha Athey, University of Toronto; Bonnie Hamilton, University of Toronto; Nigel Lascelles, Texas A&M University Corpus Christi

The growth of microplastics research by scientists from a wide range of backgrounds has lead to many creative and effective methods. However, much of this early work as well as some recent publications lack proper quality assurance and quality control (QA/QC) best management practices (BMPs) (including controls, blanks, method validation and contamination mitigation) leading to uncertainty in conclusions. For researchers just entering this field, the level of planning and consideration for QA/QC is not always obvious, which can lead to serious issues that significantly narrow, or sometimes invalidate their results. This short course is designed for beginners through intermediate researchers and will introduce students to QA/QC BMPs, method validation techniques and data reporting strategies to consider when developing and conducting more robust microplastics studies from researchers who have developed strategies for addressing these challenges.

During this course, attendees can expect to:

  • Learn BMPs for micro- and nano-plastic sample collection in different environmental media
  • Gain hands-on experience in clean sample preparation practices
  • Discuss the importance of method validation and recovery reporting
  • Learn BMPs for sample analysis (focus on different sample analysis techniques) and data reporting

Sunday Full-Day Courses

8:00 a.m.–5:00 p.m. | 3 November

Room: 705
Lead Instructor: Christian Ritz, University of Copenhagen; Signe M. Jensen, University of Copenhagen

The open source statistical environment R ( is an extremely powerful and versatile statistical environment. Moreover, the advent of RStudio ( has dramatically changed how R may interface with other languages and systems such as HTML and Microsoft Word (using R Markdown). Currently, many advanced statistical methods and visualization approaches are only implemented in R. This is in particular true when it comes to dose-response analysis.

Specifically, the course will show how to analyze continuous, quantal, count, and event-time dose-response data. Both analysis of single dose-response curves and more complex hierarchical dose-response data will be shown. We will use both joint models and metaanalytic approaches for dealing with multiple curves. Moreover benchmark dose estimation will be demonstrated.

In this short course, the primary focus will be on providing practical experience with using R for analyzing a wide range of dose-response data. The course material will be a mixture of lectures and hands-on case studies.

The course is intended for PhD students, researchers, and scientists in ecotoxicology and environmental sciences. An elementary understanding of statistical concepts such as regression models is a prerequisite. Participants are encouraged to bring their own laptop.

Room: 706
Lead Instructor: John W. Green, John W Green Ecostatistical Consulting; Jeffrey Wolf, Experimental Pathology Laboratories (EPL®), Inc

This course covers statistical considerations of experimental design and analysis to evaluate toxicity of chemicals in the environment. Hypothesis testing to determine a NOEC and regression modeling to determine an ECx are developed in detail. Discussion includes the uses of both approaches in risk assessment, differences in experimental design, and implication of basing one type of analysis on a design intended for the other. The instructors work closely with OECD & USEPA, are active members of the OECD Validation Management Group for Ecotoxicity and other multi-displanary teams and were instrumental in developing several OECD Test Guidelines, guidance documents, and methodology. Continuous, quantal, count, and severity score (histopath) data and both classical and generalized linear mixed models (GLMM) are explored. The instructors drew on decades of practical experience designing and analyzing ecotoxicity experiments, performing risk assessments, and dealing with regulatory issues in developing this class. Underlying principles are discussed, but the focus is on practical issues. All topics are illustrated by real laboratory ecotoxicity data examples describing relevant points and techniques. Logical flow-charts and discussion of software for NOEC determination and regression model fitting are presented. A related text book provides more detail and computer programs for all methods presented.

Room: 709
Lead Instructor: Richard Erickson, USGS; Nathan Pollesch, USEPA; Egina Malaj, University of Saskatchewan

R is a free, open source statical programming language that is increasingly used in environmental toxicology and chemistry. This course will provide a gentle introduction to R. The course assumes no prior experience with R. Participants will learn how to read data into R, perform basic data manipulation, create plots, and learn basic statistical methods in R. Participants are encouraged to bring their laptop with R preinstalled so they may use R during the course.

Room: TBD
Lead Instructor: Michelle Embry, HESI; Jon-Arnot, ARC Arnot Research and Consulting; Kellie Fay, USEPA; Alessandro Sangion, University of Toronto, Scarborough

Thousands of chemicals are being screened for their Persistence, Bioaccumulation and Toxicity (PBT), and various lines of evidence (LOEs) are available to assess bioaccumulation. In vivo laboratory-based lines of evidence include the bioconcentration factor (BCF) and biomagnification factor (BMF). In vitro biotransformation rate data (S9, hepatocytes) can also be applied for bioaccumulation assessment using in vitro- in vivo extrapolation (IVIVE) methods. Field-based LOEs include the BMF, bioaccumulation factor (BAF), and the Trophic Magnification Factor (TMF). In silico LOEs include quantitative structure-activity relationships (QSARs) for the BCF and the biotransformation rate constant (kB) and mass balance bioaccumulation (toxicokinetic) models. The Bioaccumulation Assessment Tool (BAT) integrates relevant measured and modelled data in a user-friendly, organizational framework and computational tool to provide a weight of evidence (WOE) approach for B assessment. This course will overview some new methodologies and approaches to incorporate estimates of biotransformation (in vitro fish biotransformation assays and QSAR model predictions), and provide instruction on how these and other LOEs for bioaccumulation assessment can be integrated into the BAT.

This course is an advanced course, aimed at registrants and evaluators familiar with bioaccumulation assessment and chemical evaluation/assessment.

Room: TBD
Lead Instructor: Jay Overmyer, Syngenta Crop Protection; Dan Schmehl, Bayer CropScience; Reed Johnson, Ohio State University; Max Feken, Syngenta Crop Protection; Nicole McKenzie, Health Canada; Michael Wagman, Environmental Protection Agency

Insect pollinators play a vital role in ecosystem health and are essential to ensuring food security. With apparent declines of both managed and wild pollinator populations in recent years, regulatory scientists have been challenged to develop and implement better ways to identify and assess risks in order to protect pollinator populations now and in the future. Pesticide Risk Assessment for Pollinators was the topic of a SETAC Pellston Workshop® convened in Pensacola, FL in 2012 and a regulatory guidance document issued in 2014 jointly by the USEPA, Canada Pest Management Regulatory Agency, and California Department of Pesticide Regulation. This course will cover the components of this tiered risk assessment process, including problem formulations for various chemical use scenarios, effects studies, exposure measurement and risk evaluation procedures proposed for each step. A copy of the SETAC Pellston Workshop® report, Pesticide Risk Assessment for Pollinators, will be included in the course materials.

Room: TBD
Lead Instructor: Christopher Salice, Townson University; Scott Weir, Queens University of Charlotte

This course is designed to introduce registrants who are unfamiliar with amphibian and reptilian biology into the special considerations needed when performing ecotoxicological studies and ecological risk assessments with these species. The course will be divided into a morning amphibian session and an afternoon reptilian session. The course will cover the essential elements of ecological risk assessment focused on amphibian and reptilian receptors. Some specific topics include adjustments to oral exposure models, consideration of dermal exposure models, as well as important methodological considerations when performing toxicity tests with these unique and interesting organisms. Students will have opportunities to perform hands-on activities to investigate exposure models and to adjust parameters and evaluate the effects on risk estimates. We expect students to leave the course with a better understanding of herpetofaunal biology, ecotoxicity data needs and modeling considerations for future ecotoxicity testing and risk assessments with amphibians and reptiles.

Room: 712
Lead Instructor: Ellen Mihaich, Environmental and Regulatory Resources; Steve Levine, Bayer CropScience; Antony Williams, USEPA; Katie Paul-Friedman, USEPA

In response to concerns that certain environmental chemicals might interfere with the endocrine system of humans and wildlife, regulations have been promulgated in regulatory bodies 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 USEPA’s Endocrine Disruptor Screening Program, as well as those for REACH and other regulatory initiatives around the world, including the development of definitions and criteria in the EU, will be reviewed. Screens and tests used in these programs are presented, including plans for the evolution of the USEPA program, with the use of high throughput in vitro assays, in silico modeling, and development of adverse outcome pathways. Use of weight of evidence evaluations in interpreting the data will be covered. Finally, an interactive simulation will be staged where small groups of participants can engage in a transparent and quantitative weight of evidence evaluation of data.