2025 Annual Report
Annual Report
We’re Hiring: Join the ECETOC Team as a Trainee!
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We’re Hiring: Join the ECETOC Team as a Trainee!

Are you passionate about science, regulatory toxicology, and making a real-world impact at the intersection of industry, academia, and policy? ECETOC is excited to announce that we’re looking for a...
ECETOC publishes a framework for the risk assessment of plastic additives
Press Release

ECETOC publishes a framework for the risk assessment of plastic additives

Part 1 sets out the fundamental elements, from problem formulation to risk characterisation.Brussels, 22 July 2026. The ECETOC Plastic Additives Task Force has published the first of two peer...
HSSD Tool

HSSD Tool

This software was developed by a consortium of partners to facilitate the uptake of novel approaches to estimate aquatic threshold concentrations (e.g. the concentration at which 5% of the species are exposed above their EC50, HC5).
The Human Exposure Assessment Tools Database (heatDB)

The Human Exposure Assessment Tools Database (heatDB)

heatdb is a public directory of exposure data sources as well as available tools for exposure
NanoApp

NanoApp

ECETOC’s NanoApp is a tool designed to define the boundaries of sets of similar nanoforms and to generate a justification for the REACH registration.
Targeted Risk Assessment (TRA)

Targeted Risk Assessment (TRA)

The Targeted Risk Assessment (TRA) estimates exposures to workers, consumers and the environment that arise during a series of events.
TRA Task Force – Worker branch

TRA Task Force – Worker branch

Why? The Worker TRA Task Force has been active since 2019, delivering projects that advance the scientific basis of the Worker Targeted Risk Assessment (TRA) tool. Its overarching objective is to e...
Immunotoxicity assessment: Addressing Challenges and Advancing Methodologies [Workshop → Task Force]​

Immunotoxicity assessment: Addressing Challenges and Advancing Methodologies [Workshop → Task Force]​

Why?Regulatory assessment of immunotoxic properties of chemicals is a complex and challenging task​ Limited regulatory guidance exists​ Lack of industry and regulatory knowledge​...
Chronic fish case studies towards an IATA

Chronic fish case studies towards an IATA

Why?Hazard and safety assessments for the pelagic compartment often rely on in vivo studies using a single fish species, raising ethical concerns and uncertainty in terms of extrapolation....
Event
18.10.2022 - 19.10.2022

Workshop on Quantitative Response-Response Relationships (qAOPs)

This event is by invitation only.
For more information, please contact info@ecetoc.org

Workshop background

Adverse Outcome Pathways (AOPs) provide a framework for curating and organising toxicological & ecotoxicological knowledge with associated measurements of key events and the dose & temporal concordance of relationships between these events. AOPs have been the topic of many conferences and workshops since the concept was first proposed in 2010. To date these qualitative AOPs have made little impact in regulatory toxicology beyond simple chemical reactivity-driven endpoints. However, quantitative AOPs are likely to be significantly more impactful in next generation risk assessments using new approach methods without the need to conduct animal studies. There is, though little guidance on best practices for quantitative AOP generation.

There are several published tiered frameworks for conducting next generation risk assessments using human-focused in vitro experimentation and in silico modelling of both biological effects and pharmacokinetics to provide estimates of human bioactive doses. A minimally toxic in vitro exposure is derived from this perturbation of human biological effects using a panel of in vitro assays. This is then converted into a human effective dose estimate using in silico physiologically based pharmacokinetic models, which can also be parameterized by in vitro assays. This combination thus provides an estimate of a point of departure for human effects that can be used as an endpoint in a risk assessment and derivation of a health-based guidance value. This is often presented, using the premise that biological responses occur at lower doses than adverse responses, as a protective conservative first tier and is performed without regard for whether the biological perturbation is large enough to cause, or even can cause, an adverse outcome.

If there isn’t sufficient margin of exposure to ensure safety, even after risk management to reduce exposures, higher tier refinements are recommended to identify adverse points of departure. However, performing such higher tier risk assessments critically depends on having knowledge of the pathway between exposure and adverse outcome to ensure this pathway is adequately modelled within the in vitro and in silico approaches. The development of a quantitative Adverse Outcome Pathways (AOPs) from these data could bridge this gap.

However, there are several issues with using the existing AOP framework as the underpinning to a higher tier risk assessment:

  • Existing AOPs provide incomplete coverage of all potential toxicities, and our knowledge of all toxic mechanisms is also incomplete. Therefore, in these circumstances it isn’t clear how to address prediction of adversity using only in vitro and in silico methods.
  • Current and emerging regulatory concerns (such as for developmental neurotoxicity) often require us to predict effects in humans where there are no established in vivo model systems, but panels of potentially mechanistically relevant human in vitro assays have or are being developed. However, the relationship of these in vitro assays to human effects is not clear.
  • Perhaps most importantly, existing AOPs are not quantitative. The Molecular Initiating Event (MIE) is the foundational event, but for most MIEs the quantitative threshold triggering the downstream key biological events leading to adversity are unknown. Equally, the ability to describe a quantitative AOP from MIE to subsequent key biological events using only in vitro and in silico approaches is unproven.

Workshop objectives

  • To bring together different stakeholders to build on the knowledge gained from existing experience of qAOP generation.
  • To make recommendations that will enable the design, interpretation and application of Quantitative Response-Response Relationships based on qualitative/descriptive AOPs that are trusted to provide confidence in use in decision making.
  • Emphasis will be placed on the development of open standards to support the FAIRification of qAOP.

Workshop presentations

  1. WS introduction_Ben van Ravenzwaay
  2. Considerations for increasing quantitative AOP (qAOP)regulatory uptake_Magda Sachana (OECD)
  3. An evolving view of QAOP and considerations for application_Dan Villeneuve (US EPA)
  4. Supporting Regulatory Application of AOPs_Bette Meek (Univeristy of Ottawa)
  5. Quantitative systems modeling of qAOP and its data integration - ONTOX perspective_Huan Yang (esqLABS)
  6. Identifying molecular biomarkers of a chemical hazard using new approach methodologies_Albert Zhou (University of Birmingham)
  7. Acute-to-chronic extrapolation in vitro. Implications for the development of KERs_Peter Macko (EC JRC)
  8. Quantitative adverse outcome pathway (qAOP) models for toxicity prediction_Nicoleta Spïnu (Liverpool John Moores University)
  9. A Machine-Readable AOP Evidence Data Model: Enhanced data input and retrieval from the AOPwiki_Jason O'Brien ( Environment and Climate Change Canada)
  10. Case study 1: The state of the art in AgChem – an example using HPPD inhibitors_Steven Webb (Syngenta)
  11. Case study 3: Identifying thyroid hormone disruptors by establishing qAOPs integrating cross-species extrapolations and thresholds_Stephanie Melching-Kollmuss (BASF)
  12. Recap of Day 1 and introduction to the breakout groups_Richard Currie (Syngenta)
  13. Breakout Group 2_Summary
  14. Breakout Group 3_Summary
  15. Breakout Group 4_Summary
  16. Toxicological Sciences (SOT) - Journal article: "How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology", Wittwehr et al., 2017