Abstract
As the basis for managing the risks of chemical exposure, the Chemical Risk Assessment (CRA) process can impact a substantial part of the economy, the health of hundreds of millions of people, and the condition of the environment. However, the number of properly assessed chemicals falls short of societal needs due to a lack of experts for evaluation, interference of third party interests, and the sheer volume of potentially relevant information on the chemicals from disparate sources.In order to explore ways in which computational methods may help overcome this discrepancy between the number of chemical risk assessments required on the one hand and the number and adequateness of assessments actually being conducted on the other, the European Commission's Joint Research Centre organised a workshop on Artificial Intelligence for Chemical Risk Assessment (AI4CRA).The workshop identified a number of areas where Artificial Intelligence could potentially increase the number and quality of regulatory risk management decisions based on CRA, involving process simulation, supporting evaluation, identifying problems, facilitating collaboration, finding experts, evidence gathering, systematic review, knowledge discovery, and building cognitive models. Although these are interconnected, they are organised and discussed under two main themes: scientific-technical process and social aspects and the decision making process.
Highlights
Chemical Risk Assessment (CRA) is a discipline at the science-policy interface that informs far reaching decisions about the placing of chemical compounds onto the market, thereby having a significant impact on a multi-billion industry, the health of hundreds of millions of people and the condition of the environment
The workshop identified a number of areas where Artificial Intelligence could potentially increase the number and quality of regulatory risk management decisions based on CRA, involving process simulation, supporting evaluation, identifying problems, facilitating collaboration, finding experts, evidence gathering, systematic review, knowledge discovery, and building cognitive models
As a scientific body supporting the development of chemical risk assessment methodologies in the European Union, the European Commission's Joint Research Centre (JRC) has launched and coordinated an initiative to explore the applicability of Artificial Intelligence (AI) to CRA as a means of supporting and improving regulatory decisions, and increasing public trust in the way the decisions are reached
Summary
Chemical Risk Assessment (CRA) is a discipline at the science-policy interface that informs far reaching decisions about the placing of chemical compounds onto the market, thereby having a significant impact on a multi-billion industry, the health of hundreds of millions of people and the condition of the environment. The four elements of CRA, i.e. hazard identification, hazard characterisation, exposure assessment and risk characterisation (Fig. 1), depend on the integration of different types of information from different sources, and increasingly with an unmanageable volume of information, including regulatory dossiers, study reports and scientific literature. As a scientific body supporting the development of chemical risk assessment methodologies in the European Union, the European Commission's Joint Research Centre (JRC) has launched and coordinated an initiative to explore the applicability of Artificial Intelligence (AI) to CRA as a means of supporting and improving regulatory decisions, and increasing public trust in the way the decisions are reached. Collaboration for the Automation of Systematic Reviews (ICASR) [3,23,24], which suggests a critical mass in interest in applying AI to assessments across environmental and biomedical disciplines. Establishing collaboration with ICASR to exploit a common focus will be a priority
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