Beyond adverse outcome pathways: making toxicity predictions from event networks, SAR models, data and knowledge

Abstract

Adverse outcome pathways have shown themselves to be useful ways of understanding and expressing knowledge about sequences of events that lead to adverse outcomes (AOs) such as toxicity. In this paper we use the building blocks of adverse outcome pathways—namely key events (KEs) and key event relationships—to construct networks which can be used to make predictions of the likelihood of AOs. The networks of KEs are augmented by data from and knowledge about assays as well as by structure activity relationship predictions linking chemical classes to the observation of KEs. These inputs are combined within a reasoning framework to produce an information-rich display of the relevant knowledge and data and predictions of AOs both in the abstract case and for individual chemicals. Illustrative examples are given for skin sensitization, reprotoxicity and non-genotoxic carcinogenicity.

Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework

“…Dr. Chris Barber, CEO of Lhasa limited and Dr. Crina Heghes, Principal Global Alliance Manager at Lhasa, introduced the tool, Kaptis ( https://www.lhasalimited.org/products/kaptis.htm ). This AOP-based tool can support toxicological hazard and risk assessment as a way to accelerate analysis, decision-making, save money and time traditionally spent on long-term studies ( Ball et al 2021 ). The value of the tool was demonstrated using well-developed AOPs to skin sensitization and cleft palate.…”

“…org/products/kaptis.htm). This AOP-based tool can support toxicological hazard and risk assessment as a way to accelerate analysis, decision-making, save money and time traditionally spent on long-term studies (Ball et al 2021). The value of the tool was demonstrated using well-developed AOPs to skin sensitization and cleft palate.…”

Predicting the Skin Sensitization Potential of Small Molecules with Machine Learning Models Trained on Biologically Meaningful Descriptors

“…For example, the RASAR models [ 53 ] are RF models that predict nine health hazard endpoints (including the skin sensitization potential) based on the distances of a compound of interest to its nearest active and inactive neighbors in reference data sets for 19 toxicological outcomes. Another computational approach utilizes a reasoning framework to build an information-rich network based on assay knowledge, assay data, and predicted bioactivities [ 54 ]. The visualization of this network can provide guidance to researchers for the assessment of the safety profile of small molecules.…”

Application of Benchmark Dose Analysis to in vitro Genotoxicity Data for Compound Risk Characterisation

“…The HESI GTTC proposed AOPs are intended to provide the basis for organising key biological events associated with genotoxic outcomes (Sasaki et al, 2020) as well as outlining the tests that can be used to identify and measure the occurrence of key events in biological test systems. The scientists at Lhasa describe how an AOP network can advance compound risk assessment (Ball et al, 2021) by imagining some use cases that could emerge an indirect measure of stalled DNA replication forks (Hendriks et al, 2015;Sasaki et al, 2020). The Derek Nexus Topo-II Poison AOP network that has been developed in this results chapter can be included in Lhasa's Kaptis software platform (https://www.lhasalimited.org/products/kaptis.htm) that is intended to combine AOP knowledge in a meaningful way to be used in risk assessment (Ball et al, 2021).…”

“…The scientists at Lhasa describe how an AOP network can advance compound risk assessment (Ball et al, 2021) by imagining some use cases that could emerge an indirect measure of stalled DNA replication forks (Hendriks et al, 2015;Sasaki et al, 2020). The Derek Nexus Topo-II Poison AOP network that has been developed in this results chapter can be included in Lhasa's Kaptis software platform (https://www.lhasalimited.org/products/kaptis.htm) that is intended to combine AOP knowledge in a meaningful way to be used in risk assessment (Ball et al, 2021).…”