Department Environmental Toxicology

European Partnership for the Assessment of Risks from Chemicals (PARC)

Eawag and the Ecotox Centre host several projects within the EU PARC consortium. (Created with BioRender)

Chemical risk assessment is meant to ensure the safety of chemicals for both human health and the environment. However, the rising number of highly diverse chemicals on the market, for which toxicological and exposure data is not always available, challenge the current regulatory system. Here, new toxicological methods can help streamlining the process of filling these data gaps. Likewise, improving the dialogue between science, policymakers, and the public can lead to rapid prioritization of new chemicals in terms of research and regulatory needs. This then feeds into the agile adaptation of the regulatory process, ensuring higher safety for the public while simultaneously reducing the need for currently required animal tests, thus saving both resources and animal lives.

The Partnership for the Assessment of Risks from Chemicals (PARC)[SC1]  is a Horizon Europe project funded by the European Union. It is aimed at revising and improving the chemical risk assessment process to suit the possibilities and needs of the 21st century. This effort is brought forward through research and innovation that are closely linked to society. By including over 200 partners from 29 countries, spanning diverse disciplines, PARC puts a particularly strong focus on interdisciplinary collaboration across research fields and stakeholders. PARC activities support the EU Green Deal zero pollution goal as well as the EU Chemicals Strategy for Sustainability.

At Eawag and the Ecotox Centre, PARC is represented through several projects, covering a diverse array of aspects:

WP4 Monitoring and Exposure

Under PARC WP4 Monitoring and Exposure, whose overall goal is “to monitor chemicals guided by regulatory challenges both in humans and in the environment, observing different sources, chemical fates and exposure pathways”:

  • Contribution to the project design of targeted monitoring activities (WP 4.2.3) and prioritization of chemicals and activities based on existing knowledge (WP 4.2.1, 4.2.2)

Team

Prof. Dr. Juliane Hollender Senior scientist / Group leader Tel. +41 58 765 5493 Send Mail
Dr. Etienne Vermeirssen Tel. +41 58 765 5295 Send Mail
  • Suspect screening of metabolites of industrial compounds and pharmaceuticals in the aquatic environment by compilation of appropriate suspect lists including usage of pathway-prediction systems and application to various sample types within the project “Wastewater based epidemiology for community-wide human exposure assessment” (WP 4.3.3)

Team

Prof. Dr. Juliane Hollender Senior scientist / Group leader Tel. +41 58 765 5493 Send Mail
Dr. Kasia Arturi Scientist Tel. +41 58 765 6816 Send Mail
Corina Meyer PhD student Tel. +41 58 765 6799 Send Mail

WP5 Hazard Assessment

Under PARC WP5 Hazard Assessment, the overall focus is “on hazard assessment for human and environmental health on three different directions: fill data gaps, develop and/or improve methodologies for hazard assessment to progress toward next generation risk assessment (NGRA)”, all projects under WP5.2.:

  • The project on machine learning where available data will be surveyed using available databases and data cleaned for further processing. Focus will be on acute toxicity data across taxa on the one hand and on mode-of-action specific assay information on the other.

Team

Prof. Dr. Kristin Schirmer Head of department Tel. +41 58 765 5266 Send Mail
Dr. Christoph Schuer Postdoctoral Scientist Tel. +41 58 765 5684 Send Mail
  • The project on a microfluidic device with immobilized synthetic phototrophic biofilms, where the optimal conditions for a reproducible biofilm formation will be identified. This will be achieved by testing different inoculation conditions as well as the various flow velocities in the microfluidic device.

Team

Prof. Dr. Kristin Schirmer Head of department Tel. +41 58 765 5266 Send Mail
Emera Forni Scientific Assistant Tel. +41 58 765 5271 Send Mail
Bettina Wagner Lab Technician Tel. +41 58 765 5342 Send Mail
  • The project on zebrafish behavioral effects of neurotoxicants will focus on the consolidation of the pipeline for concomitant assessment of behavioral alterations and the underlying structural and molecular changes occurring in the nervous system of larval zebrafish upon exposure to neurotoxic substances as well as during the depuration period.

Team

Dr. Ksenia Groh Group Leader Tel. +41 58 765 5182 Send Mail
Dr. Colette vom Berg Deputy head of department Tel. +41 58 765 5535 Send Mail
Melissa von Wyl Scientific Assistant Tel. +41 58 765 5586 Send Mail
Severin Ammann Lab Technician Tel. +41 58 765 6407 Send Mail
René Schönenberger Lab Technician Tel. +41 58 765 5105 Send Mail

WP6 Innovation in Regulatory Risk Assessment

Under PARC WP6 Innovation in Regulatory Risk Assessment, the main goal is “to drive innovation in regulatory risk assessment by strengthening its scientific basis, with implementation of NGRA as ultimate goal”:

  • Contribution to a review of risk assessment methodology, through a case study led by FOEN and Eawag, which will analyze the differences and similarities in environmental risk assessment of pesticides performed under different prospective and retrospective regulations, aiming to advance the one substance one assessment goal (WP 6.3). This project will make use of extensive experience with risk assessment for pesticides in Switzerland and in Europe, built by the project team during the last decade.

Team

Dr. Marion Junghans Ecotox Centre Tel. +41 58 765 5401 Send Mail
Dr. Alexandra Kroll Tel. +41 58 765 5487 Send Mail
Dr. Carmen Casado-Martinez Tel. +41 58 765 5747 Send Mail
  • Case study to contribute to the current discussion on mixture allocation factors  (MAF) for the prospective risk assessment of chemicals. Different MAF types are applied on fresh water monitoring datasets to find statistical evidence for a MAF that minimizes mixture effects of single substances and to discuss the limitations of each MAF type in the context of real monitoring data. s (WP 6.4.1)

Team

Dr. Marion Junghans Ecotox Centre Tel. +41 58 765 5401 Send Mail
Fabian Balk Researcher Tel. +41 58 765 6478 Send Mail
  • In this case study, the current mixture risk assessment for water bodies used by certain swiss cantons (Junghans et al., 2013, Aqua & Gas, 93(5), 54-61) will be expanded with endpoints relevant to the european water framework directive (WFD), the methodology compared to conventional mixture risk assessments and assessed for consideration as amendment for the WFD (WP 6.4.1)

Team

Dr. Marion Junghans Ecotox Centre Tel. +41 58 765 5401 Send Mail
Fabian Balk Researcher Tel. +41 58 765 6478 Send Mail
  • In WP 6.4.4, models for landscape-based environmental risk assessment are being developed. Different case studies provide data to inform model design. Eawag/OZ leads a case study on linking pesticide use to monitoring data: Based on chemical monitoring data (water, sediment, fish) and biotest data for five agricultural sites, we want to calculate exposure-activity ratios that will then be compared with biological monitoring data. The main aims are (1) to understand the predictive power of the EAR approach at the selected sites and (2) to check for established adverse outcome pathways (AOPs) being evidenced by the data for further investigation.

Team

Dr. Alexandra Kroll Tel. +41 58 765 5487 Send Mail
Dr. Carmen Casado-Martinez Tel. +41 58 765 5747 Send Mail

Publikationen

Machine learning-based prediction of fish acute mortality: implementation, interpretation, and regulatory relevance

Regulation of chemicals requires knowledge of their toxicological effects on a large number of species, which has traditionally been acquired through in vivo testing. The recent effort to find alternatives based on machine learning, however, has not focused on guaranteeing transparency, comparability and reproducibility, which makes it difficult to assess advantages and disadvantages of these methods. Also, comparable baseline performances are needed. In this study, we trained regression models on the ADORE “t-F2F” challenge proposed in [Schür et al., Nature Scientific data, 2023] to predict acute mortality, measured as LC50 (lethal concentration 50), of organic compounds on fishes. We trained LASSO, random forest (RF), XGBoost, Gaussian process (GP) regression models, and found a series of aspects that are stable across models: (i) using mass or molar concentrations does not affect performances; (ii) the performances are only weakly dependent on the molecular representations of the chemicals, but (iii) strongly on how the data is split. Overall, the tree-based models RF and XGBoost performed best and we were able to predict the log10-transformed LC50 with a root mean square error of 0.90, which corresponds to an order of magnitude on the original LC50 scale. On a local level, on the other hand, the models are not able to consistently predict the toxicity of individual chemicals accurately enough. Predictions for single chemicals are mostly influenced by a few chemical properties while taxonomic traits are not captured sufficiently by the models. We discuss technical and conceptual improvements for these challenges to enhance the suitability of in silico methods to environmental hazard assessment. Accordingly, this work showcases state-of-the-art models and contributes to the ongoing discussion on regulatory integration.
Gasser, L.; Schür, C.; Perez-Cruz, F.; Schirmer, K.; Baity-Jesi, M. (2024) Machine learning-based prediction of fish acute mortality: implementation, interpretation, and regulatory relevance, Environmental Science: Advances, doi:10.1039/d4va00072b, Institutional Repository

Exploring BPA alternatives - environmental levels and toxicity review

Bisphenol A alternatives are manufactured as potentially less harmful substitutes of bisphenol A (BPA) that offer similar functionality. These alternatives are already in the market, entering the environment and thus raising ecological concerns. However, it can be expected that levels of BPA alternatives will dominate in the future, they are limited information on their environmental safety. The EU PARC project highlights BPA alternatives as priority chemicals and consolidates information on BPA alternatives, with a focus on environmental relevance and on the identification of the research gaps. The review highlighted aspects and future perspectives. In brief, an extension of environmental monitoring is crucial, extending it to cover BPA alternatives to track their levels and facilitate the timely implementation of mitigation measures. The biological activity has been studied for BPA alternatives, but in a non-systematic way and prioritized a limited number of chemicals. For several BPA alternatives, the data has already provided substantial evidence regarding their potential harm to the environment. We stress the importance of conducting more comprehensive assessments that go beyond the traditional reproductive studies and focus on overlooked relevant endpoints. Future research should also consider mixture effects, realistic environmental concentrations, and the long-term consequences on biota and ecosystems.
Adamovsky, O.; Groh, K. J.; Białk-Bielińska, A.; Escher, B. I.; Beaudouin, R.; Mora Lagares, L.; Tollefsen, K. E.; Fenske, M.; Mulkiewicz, E.; Creusot, N.; Sosnowska, A.; Loureiro, S.; Beyer, J.; Repetto, G.; Štern, A.; Lopes, I.; Monteiro, M.; Zikova-Kloas, A.; Eleršek, T.; Vračko, M.; Zdybel, S.; Puzyn, T.; Koczur, W.; Ebsen Morthorst, J.; Holbech, H.; Carlsson, G.; Örn, S.; Herrero, Ó.; Siddique, A.; Liess, M.; Braun, G.; Srebny, V.; Žegura, B.; Hinfray, N.; Brion, F.; Knapen, D.; Vandeputte, E.; Stinckens, E.; Vergauwen, L.; Behrendt, L.; João Silva, M.; Blaha, L.; Kyriakopoulou, K. (2024) Exploring BPA alternatives - environmental levels and toxicity review, Environment International, 189, 108728 (29 pp.), doi:10.1016/j.envint.2024.108728, Institutional Repository

Green Swans countering chemical pollution

If a problem has exponential features, its solution asks for counter-exponential approaches. Chemical pollution appears to be such a problem. Analyses of chemical hazards to human health, biodiversity, and ecosystem services and estimates of the cost of inaction suggest the potential for adverse impacts, and analyses of trends in the chemical economy appear exponential in kind. Here, we argue that we need and can develop an exponential and application-focused mindset in thinking about solutions.
Posthuma, L.; Bloor, M.; Campos, B.; Groh, K.; Leopold, A.; Sanderson, H.; Schreiber, H.; Schür, C.; Thomas, P. (2024) Green Swans countering chemical pollution, Integrated Environmental Assessment and Management, 20(3), 888-891, doi:10.1002/ieam.4915, Institutional Repository

A benchmark dataset for machine learning in ecotoxicology

The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, which we consider a barrier of entry for this kind of research. Additionally, model performances can only be compared across studies when the same dataset, cleaning, and splittings were used. Therefore, we provide ADORE, an extensive and well-described dataset on acute aquatic toxicity in three relevant taxonomic groups (fish, crustaceans, and algae). The core dataset describes ecotoxicological experiments and is expanded with phylogenetic and species-specific data on the species as well as chemical properties and molecular representations. Apart from challenging other researchers to try and achieve the best model performances across the whole dataset, we propose specific relevant challenges on subsets of the data and include datasets and splittings corresponding to each of these challenge as well as in-depth characterization and discussion of train-test splitting approaches.
Schür, C.; Gasser, L.; Perez-Cruz, F.; Schirmer, K.; Baity-Jesi, M. (2023) A benchmark dataset for machine learning in ecotoxicology, Scientific Data, 10(1), 718 (20 pp.), doi:10.1038/s41597-023-02612-2, Institutional Repository

Kontakt

WP 4 Monitoring and Exposure

WP 4 Monitoring and Exposure
Prof. Dr. Juliane Hollender Senior scientist / Group leader Tel. +41 58 765 5493 Send Mail
WP 4 Monitoring and Exposure

WP5 Hazard Assessment

Dr. Colette vom Berg Deputy head of department Tel. +41 58 765 5535 Send Mail

WP6 Innovation in Regulatory Risk Assessment

Dr. Marion Junghans Ecotox Centre Tel. +41 58 765 5401 Send Mail

Involved Eawag research departments

Umwelttoxikologie
Umweltchemie
Ökotoxzentrum
Systemanalyse, Integrated Assessment und Modellierung

In collaboration with

Swiss Data Science Center

Funding

Europäische Union
Staatssekretariat für Bildung, Forschung und Innovation (SBFI)
Eawag