On Sunday 13 May 2018, a variety of training courses are offered prior to the opening of the meeting. Course registration is open to members and guests. Note that you do not need to register for the full meeting to attend a training course.
We strongly encourage early registration in order to avoid disappointment, as i) the number of registrations for some courses is limited and ii) the final decision on whether the training course will be programmed at the meeting will depend on the number of registrations received on 20 March 2018. If you have not registered by that date, we might need to cancel the course you are interested in, due to lack of registrations.
Continuous development of your career.
Up-to-date courses thought by experts in the field.
Unique composition of instructors from all SETAC sectors (business, government and academia).
What Participants Say
Fantastic course! Instructors knew all about the theory & execution of the material, and provided excellent reference for future use.
Well done! Relevant and current content. All speakers strong in experince and all presentations well prepared.
Sad that too less authority people joined. Courses like this are ideal to drive exchange between different stakeholders.
Sunday, 13 May | 8:00 a.m. – 5:00 p.m.
Instructors: Ellen Mihaich (Environmental and Regulatory Resources), James Wheeler (Dow AgroSciences), David Dreier (University of Florida) and Christopher Green (UK DEFRA)
Room: Meeting Room 3
In response to concerns that certain environmental chemicals might interfere with the endocrine system of humans and wildlife, regulations have been promulgated in various regulatory bodies around the world targeting the evaluation of these types of effects.
The purpose of this training course is to address key topics related to endocrine system evaluation and regulatory requirements around the world. The course will provide basic information on the vertebrate endocrine system, mechanisms of control, and adverse effects.
The focus will be the estrogen, androgen, and thyroid systems, although new endocrine system targets will be discussed. The requirements of the US EPA’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. Specific screens and tests used in these programmes will be reviewed, including plans for the evolution of the US EPA programme, such as EDSP21 and the 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.View the course objectives and outline
Instructors: John W. Green (DuPont) and Henrik Holbech (University of Southern Denmark)
Room: Meeting Room 8
This course covers statistical considerations of experimental design and analysis used to evaluate toxicity of chemicals in the environment. Both hypothesis testing to determine a NOEC and regression modeling to determine an ECx or benchmark dose are developed in detail. Discussion includes advantages and disadvantages of both approaches, their use in risk assessment, differences in experimental design, and the implication of basing one type of analysis on a design intended for another. The instructors work closely with OECD & USEPA, are active members of the OECD Validation Management Group for Ecotoxicity and several other multi-displanary teams and were instrumental in developing several OECD Test Guidelines, guidance documents, and methodology. Continuous, quantal, and severity score (histopath) data and both normal and Poisson models are explored. The instructors have decades of practical experience designing and analyzing ecotoxicity experiments, performing risk assessments, and dealing with related regulatory issues and drew on that experience in developing this class. Underlying principles will be discussed, but the focus will be on practical issues. All topics include illustration by real laboratory ecotoxicity data examples illustrating the relevant points and techniques. Logical flow-charts and discussion of software for NOEC determination and for regression model fitting will be presented.View the course objectives and outline.
This training course is designed for scientists of any career stage wanting to improve their live presentation skills. During the course we focus on three issues: “you”—being aware of the impression you make in front of a live audience, and using that impression in your favor (i.e. for getting your message across most effectively), “your audience”—understanding the audience’s perspective, its needs and response to your presentation style, and “you & your audience”—how to best interact with a live audience to help spread your message. We use training techniques from improvisational theatre and also include some role play/theatrical elements, but the purpose of the workshop is not to “be funny”. We assist you in shaping your message in such a way that the relevance of your work becomes clear in the context of societal needs. This one-day workshop will sharpen your awareness and help you develop your presentation skills—in a friendly and fun atmosphere.
This course has a maximum of 10 participants!View the course objectives and outline.
Instructors: Mark Miles (Bayer), Jacoba Wassenberg (Ctgb), Edward Pilling (Dow AgroSciences), Ivo Roessink (WUR Alterra), Nicole Hanewald (BASF), Marco Candolfi (Eurofins), Silvio Knaebe (Eurofins)
Room: Meeting Room 1
Regulatory texts on Plant Protection Products (pesticides) require an assessment of the impact of these products on the pollinating species and these texts have been recently updated in Europe and North America in order to take into account the most recent scientific input. In the meantime, expert groups are active in updating the set of testing methods to be used in a revised regulatory context.
This course aims at guiding risk assessors as well as scientists through the updated set of methods and more particularly:
- Providing elements of bee biology as a basis for understanding testing methods set-up, advantages and limitations;
- Providing state of the art of actual testing methods and their developments, linked to OECD, ICP-PR and EPPO activities;
- Discussing the derivation of endpoints that allow a reliable description of products ecotoxicological profile to bees for use in robust risk assessments;
- Role of the testing methods in context of the bigger challenges underlying the protection of pollinators.
The open source statistical environment R is an extremely powerful and versatile statistical environment. In recent years there has been an amazing development in terms of added capabilities and extra functionality, making it the preferred data analytic toolbox of many statisticians and researchers in many applied sciences. Moreover, it encourages collaborative and reproducible research. RStudio has dramatically changed how R may interface with other languages and systems such as HTML and MS Word.
Currently, many advanced or recent statistical and visualisation approaches and techniques are implemented much more generally or even only available in R. This is, in particular, true when it comes to statistical approaches used in ecotoxicology, e.g., dose-response analysis.
In this course, the primary focus will be on giving the participants practical experience with using R for analysing ecotoxicological data. Relevant recent statistical methodological advances and concepts will be touched upon. The course material will be a mixture of lectures and hands-on case studies with toxicological data, from recent publications. Participants are encouraged to bring their own data.
Specifically, analysis of variance and linear regression will be briefly revisited before introducing nonlinear regression and more general dose-response analysis, logistic and Poisson regression models, and linear, logistic and nonlinear mixed-effects models. More advanced concepts such as sandwich variance estimators, single-step multiplicity adjustment,