Search

Both because of the shortcomings of existing risk assessment methodologies, as well as newly available tools to predict hazard and risk with machine learning approaches, there has been an emerging emphasis on probabilistic risk assessment. Increasingly sophisticated artificial intelligence (AI) models can be applied to a plethora of exposure and hazard data to obtain not only predictions for particular endpoints but also to estimate the uncertainty of the risk assessment outcome. This provides the basis for a shift from deterministic to more probabilistic approaches but comes at the cost of an increased complexity of the process as it requires more resources and human expertise. There are still challenges to overcome before a probabilistic paradigm is fully embraced by regulators. Based on an earlier white paper (Maertens et al., 2022), a workshop discussed the prospects, challenges, and path forward for implementing such AI-based probabilistic hazard assessment. Moving forward, we will see the transition from categorized into probabilistic and dose-dependent hazard outcomes, the application of internal thresholds of toxicological concern for data-poor substances, the acknowledgement of user-friendly open-source software, a rise in the expertise of toxicologists required to understand and interpret artificial intelligence models, and the honest communication of uncertainty in risk assessment to the public. [ABSTRACT FROM AUTHOR]

The Virtual Human Platform for Safety Assessment (VHP4Safety) project aims to build a Virtual Human Platform (VHP) to protect human health and revolutionize the safety assessment of chemicals and pharmaceuticals by transitioning from animal-based to human-based approaches. The goal of this article is to introduce the project and its interdisciplinary approach to co-creation with multiple academic, regulatory, industrial and societal partners covering the entire safety assessment knowledge chain. Three research lines drive the project: 1) building the VHP; 2) feeding the VHP with human data; and 3) implementing the VHP. The project focusses on three case studies that incorporate human relevant scenarios not included in current animal-based safety assessment strategies. The VHP is built on tools and services, including pharmacokinetic and computational models, and integrates several data sources within each case study, including data on human physiology, epidemiology, toxicokinetic and -dynamic parameters, as well as data on chemical characteristics and exposures. In addition, the VHP integrates new data generated within the project using new approach methodologies representing key events within adverse outcome pathways. Implementation of the VHP is investigated using an innovation systems approach, engaging stakeholders and organizing training and education. Central to the VHP4Safety project is our co-creative approach, which facilitated by biannual designathons and hackathons that foster active involvement of all project participants from over 30 partner organizations. By integrating technological innovations with transparency and stakeholder collaboration, the VHP4Safety project will help shape the transition to the next generation safety assessment in which animal testing becomes redundant.