Advanced Toxicological Risk Assessment by Implementation of Ontologies Operationalized in Computational Models

Abstract

Given tremendous progress in biology, toxicology, and chemistry knowledge in recent decades, the time is right for serious consideration of options to move away from animal experimentation in chemical hazard and risk assessment. Individual alternative and animal-free assays as a replacement of individual animal studies have met with understandable reluctance in the scientific and regulatory arenas. An integrated conceptual approach based on mechanistic information built from all available information on biology, chemistry, and mechanisms of toxicity, might allow sufficient coverage of the biological system to provide the basis for reliable animal-free chemical hazard and risk assessment for man. We describe construction of an ontology, which can be considered a network of adverse outcome pathways, including feedback loops representing homeostasis. Basic elements in the ontology are subjects (such as enzymes, receptors, and cell types) and their quantitative relationships (response-response relationships), together forming a multidimensional network of biological interactions. This network can be modeled in silico, providing an integrated system toxicology computational model with which toxicity predictions can be made at the level of adverse outcomes in the intact individual. The model will indicate critical rate-determining steps in the network that can be monitored in a battery of dedicated in vitro assays, providing a testing strategy to collect data feeding into the systems model. Connecting this integrated dynamic model with exposure models allows quantitative hazard and risk assessment for man, avoiding animal experiments.

Identifying the landscape of developmental toxicity new approach methodologies

“…This question also arose from discussions stimulated by review and querying of the dashboard. In addition to empirical studies (Jarque et al, 2020 ), research highly relevant to this question is focused on constructing a developmental ontology to describe the pathways and processes critical to embryonic development in a manner that would permit analyzing and linking chemically induced responses in specific pathways and physiological processes to adverse outcomes (Heusinkveld et al, 2021 ; Staal, Pennings, Hessel, & Piersma, 2017 ).…”

Pluripotent stem cell assays: Modalities and applications for predictive developmental toxicity

“…Combinations of assays can also be designed from a more mechanistic perspective, defining the developmental landscape that needs to be covered and subsequently filling that landscape with the necessary models (e.g. virtual embryo, ontologies) ( Kavlock and Dix, 2010; Hutson et al, 2017 , Staal et al, 2017 , Hessel et al, 2018 , Scialli et al, 2018 ). The latter requires sufficient knowledge of developmental biology, ideally leading to an in silico systems biology model covering all necessary developmental elements.…”

Workshop on the validation and regulatory acceptance of innovative 3R approaches in regulatory toxicology – Evolution versus revolution

“…Instead, complex quantitative network modelling is probably necessary for adequate toxicity prediction (Staal et al, 2017). The example of endocrine feedback homeostasis was given as an essential mechanism of sustaining life, and in that context toxicity can be described as an effect that over rides homeostatic control.…”