Periodic Reporting for period 2 - ONTOX (Ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment)
Período documentado: 2022-11-01 hasta 2024-04-30
The overall goal of ONTOX is to deliver a generic strategy to create innovative New Approach Methodologies (NAMs) to predict systemic repeated dose toxicity effects of chemicals that, upon combination with tailored exposure assessment, will enable human risk assessment. For proof-of-concept purposes, focus will be put on 3 organs, each with 2 specific types of adversity, namely the liver (steatosis and cholestasis), the kidneys (tubular necrosis and crystallopathy) and the developing brain (neural tube closure and cognitive function defects). This will result in 6 NAMs in total. Chemicals from different application domains will be considered, including from, but not limited to, the pharmaceutical, cosmetics, food and biocide sectors. The 6 NAMs will each consist of a computational system based on advanced Artificial Intelligence (AI), and will be primarily fed by available biological, toxicological, chemical and kinetic data. These data will be consecutively integrated in physiological maps, quantitative Adverse Outcome Pathway (qAOP) networks and ontology frameworks. Data gaps, as identified by the AI system, will be filled by targeted in vitro (cell culture) and in silico (computational) testing. The impact of ONTOX is, however, de facto much broader, as the underlying ontology-driven and AI-based strategy can as such be applied to any type of chemical and systemic repeated dose toxicity effect. ONTOX will thus provide a fully functional and sustainable solution for advancing human risk assessment of chemicals leading to better protection of European citizens without the use of animals.
Highlights of the second reporting period include:
WP1 updated all physiological maps to obey FAIR principles and performed transcriptomics analysis on acquired human brain and spinal cord samples.
WP2 constructed a database , consisting of 432 patients with drug-induced cholestasis for the cholestasis project, enabling the identification of three distinct subphenotypes of cholestatic drugs.
WP3 developed novel computational models (QSAR and fragment-based) and a new automated docking server, DockTox.
WP4 completed an analysis of the high-throughput PBK platform and simulated the in vitro distribution of over 100 DNT chemicals.
WP5 created ChemHarmony, which allowed for accurate prediction for 4,200 properties across 120+ million chemicals. Automated import of extracted scientific literature feeds into physiological maps and a probabilistic hazard assessment.
WP6 identified the most relevant exposure methods and models for chemical exposure and expanded the ONTOX Stakeholder network.
WP7 published updated adverse outcome pathway networks on chemical-induced liver steatosis and cholestasis and set up in vitro test batteries.
WP8 published a nephrotoxicity AOP network and established a novel in vitro model for kidney tubular crystallopathy.
WP9 characterized the biological applicability domain of the in vitro models used for the DNT assessment of chemicals and delivered computational model of mammalian neural tube closure to predict defects.
WP10 coordinated the ONTOX research and non-research aspects, co-coordinated the ASPIS cluster (ONTOX, PrecisionTox, RISKHUNT3R) and supported the establishment of the ASPIS Academy.
WP11 created an ONTOX collection in BioStudies containing 36 accessions (physiological maps, AOPs, ToxTemps and transcriptomics data).
WP12 provided audiovisual and written content for disseminating the project’s accomplishments, supported the organization of ONTOX consortium meetings and with stakeholders.
WP13 released version 1 of the ONTOX Hub and performed an analysis of the global chemical safety and risk assessment market.
WP14 amplified ONTOX scientific advancements by utilizing established channels such as the website and social media, ONTOX TV and newsletters.
WP1 updated all physiological maps to obey FAIR principles and performed transcriptomics analysis on acquired human brain and spinal cord samples.
WP2 constructed a database , consisting of 432 patients with drug-induced cholestasis for the cholestasis project, enabling the identification of three distinct subphenotypes of cholestatic drugs.
WP3 developed novel computational models (QSAR and fragment-based) and a new automated docking server, DockTox.
WP4 completed an analysis of the high-throughput PBK platform and simulated the in vitro distribution of over 100 DNT chemicals.
WP5 created ChemHarmony, which allowed for accurate prediction for 4,200 properties across 120+ million chemicals. Automated import of extracted scientific literature feeds into physiological maps and a probabilistic hazard assessment.
WP6 identified the most relevant exposure methods and models for chemical exposure and expanded the ONTOX Stakeholder network.
WP7 published updated adverse outcome pathway networks on chemical-induced liver steatosis and cholestasis and set up in vitro test batteries.
WP8 published a nephrotoxicity AOP network and established a novel in vitro model for kidney tubular crystallopathy.
WP9 characterized the biological applicability domain of the in vitro models used for the DNT assessment of chemicals and delivered computational model of mammalian neural tube closure to predict defects.
WP10 coordinated the ONTOX research and non-research aspects, co-coordinated the ASPIS cluster (ONTOX, PrecisionTox, RISKHUNT3R) and supported the establishment of the ASPIS Academy.
WP11 created an ONTOX collection in BioStudies containing 36 accessions (physiological maps, AOPs, ToxTemps and transcriptomics data).
WP12 provided audiovisual and written content for disseminating the project’s accomplishments, supported the organization of ONTOX consortium meetings and with stakeholders.
WP13 released version 1 of the ONTOX Hub and performed an analysis of the global chemical safety and risk assessment market.
WP14 amplified ONTOX scientific advancements by utilizing established channels such as the website and social media, ONTOX TV and newsletters.
Original and innovative aspects of ONTOX presented against the current state-of-the-art include:
1. State-of-the-art: focus on individual critical aspects of systemic repeated dose toxicity and full risk assessment for development of NAMs mainly in separate projects.
Innovation in ONTOX: ontology-driven and AI-based integration of all critical aspects of systemic repeated dose toxicity (biology, toxicology, chemistry and kinetics) and risk assessment (hazard identification, hazard characterisation and exposure assessment) in a single
collaborative project and resulting in 1 NAM per type of adversity.
2. State-of-the-art: frequent insufficient data for the development of AI systems to predict chemical hazard.
Innovation in ONTOX: generation of an advanced AI system for reliable chemical hazard identification fed by data-rich ontologies and read-across structure-activity relationships, which allows inclusion of heterogeneous big data.
3. State-of-the-art: traditional bottom-up approach for hazard identification in animals using high doses of chemicals starting from the apical toxicological outcome at the organism level.
Innovation in ONTOX: top-down approach for hazard identification and next generation risk assessment in human-based NAMs using physiologically relevant doses starting from basic biology at the molecular level.
4. State-of-the-art: 1-to-1 replacement of animal studies for toxicity testing with single non-animal methods.
Innovation in ONTOX: replacement of animal studies for toxicity testing by batteries of in vitro assays and in silico tools encompassing the full biological spectrum and reflecting the in vivo complexity of adverse effects.
The ambition of ONTOX is to strengthen Europe’s world-leading position regarding the development, exploitation, regulation and application of NAMs for human risk assessment of chemicals by empowering:
1. Scientific excellence: to move beyond the state-of-the-art by delivering an unprecedented set of NAMs.
2. Industrial innovation: to generate new value creation opportunities and market potential.
3. Regulatory pioneering: to introduce a paradigm shift in the validation and use of non-animal methods.
4. Societal prioritisation: to increase human chemical safety while fully replacing the use of animals.
1. State-of-the-art: focus on individual critical aspects of systemic repeated dose toxicity and full risk assessment for development of NAMs mainly in separate projects.
Innovation in ONTOX: ontology-driven and AI-based integration of all critical aspects of systemic repeated dose toxicity (biology, toxicology, chemistry and kinetics) and risk assessment (hazard identification, hazard characterisation and exposure assessment) in a single
collaborative project and resulting in 1 NAM per type of adversity.
2. State-of-the-art: frequent insufficient data for the development of AI systems to predict chemical hazard.
Innovation in ONTOX: generation of an advanced AI system for reliable chemical hazard identification fed by data-rich ontologies and read-across structure-activity relationships, which allows inclusion of heterogeneous big data.
3. State-of-the-art: traditional bottom-up approach for hazard identification in animals using high doses of chemicals starting from the apical toxicological outcome at the organism level.
Innovation in ONTOX: top-down approach for hazard identification and next generation risk assessment in human-based NAMs using physiologically relevant doses starting from basic biology at the molecular level.
4. State-of-the-art: 1-to-1 replacement of animal studies for toxicity testing with single non-animal methods.
Innovation in ONTOX: replacement of animal studies for toxicity testing by batteries of in vitro assays and in silico tools encompassing the full biological spectrum and reflecting the in vivo complexity of adverse effects.
The ambition of ONTOX is to strengthen Europe’s world-leading position regarding the development, exploitation, regulation and application of NAMs for human risk assessment of chemicals by empowering:
1. Scientific excellence: to move beyond the state-of-the-art by delivering an unprecedented set of NAMs.
2. Industrial innovation: to generate new value creation opportunities and market potential.
3. Regulatory pioneering: to introduce a paradigm shift in the validation and use of non-animal methods.
4. Societal prioritisation: to increase human chemical safety while fully replacing the use of animals.