Alexandra Maertens, Breanne Kincaid, Eric Bridgeford, Celine Brochot, Arthur de Carvalho E Silva, Jean-Lou C M Dorne, Liesbet Geris, Trine Husøy, Nicole Kleinstreuer, Luiz C M Ladeira, Alistair Middleton, Joe Reynolds, Blanca Rodriguez, Erwin L Roggen, Giulia Russo, Kris Thayer, Thomas Hartung
{"title":"从细胞扰动到概率风险评估。","authors":"Alexandra Maertens, Breanne Kincaid, Eric Bridgeford, Celine Brochot, Arthur de Carvalho E Silva, Jean-Lou C M Dorne, Liesbet Geris, Trine Husøy, Nicole Kleinstreuer, Luiz C M Ladeira, Alistair Middleton, Joe Reynolds, Blanca Rodriguez, Erwin L Roggen, Giulia Russo, Kris Thayer, Thomas Hartung","doi":"10.14573/altex.2501291","DOIUrl":null,"url":null,"abstract":"<p><p>Chemical risk assessment is evolving from traditional deterministic approaches to embrace probabilistic methodologies, where risk of hazard manifestation is understood as a more or less probable event depending on exposure, individual factors, and stochastic processes. This is driven by advancements in human stem cells, complex tissue engineering, high-performance computing, and cheminformatics, and is more recently facilitated by large-scale artificial intelligence models. These innovations enable a more nuanced understanding of chemical hazards, capturing the complexity of biological responses and variability within populations. However, each technology comes with its own uncertainties impacting on the estimation of hazard probabilities. This shift addresses the limitations of point estimates and thresholds that oversimplify hazard assessment, allowing for the integration of kinetic variability and uncertainty metrics into risk models. By leveraging modern technologies and expansive toxicological data, probabilistic approaches offer a comprehensive evaluation of chemical safety. This paper summarizes a workshop held in 2023 and discusses the technological and data-driven enablers, and the challenges faced in their implementation, with particular focus on perturbation of biology as the basis of hazard estimates. The future of toxicological risk assessment lies in the successful integration of these probabilistic models, promising more accurate and holistic hazard evaluations.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"413-434"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"From cellular perturbation to probabilistic risk assessments.\",\"authors\":\"Alexandra Maertens, Breanne Kincaid, Eric Bridgeford, Celine Brochot, Arthur de Carvalho E Silva, Jean-Lou C M Dorne, Liesbet Geris, Trine Husøy, Nicole Kleinstreuer, Luiz C M Ladeira, Alistair Middleton, Joe Reynolds, Blanca Rodriguez, Erwin L Roggen, Giulia Russo, Kris Thayer, Thomas Hartung\",\"doi\":\"10.14573/altex.2501291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Chemical risk assessment is evolving from traditional deterministic approaches to embrace probabilistic methodologies, where risk of hazard manifestation is understood as a more or less probable event depending on exposure, individual factors, and stochastic processes. This is driven by advancements in human stem cells, complex tissue engineering, high-performance computing, and cheminformatics, and is more recently facilitated by large-scale artificial intelligence models. These innovations enable a more nuanced understanding of chemical hazards, capturing the complexity of biological responses and variability within populations. However, each technology comes with its own uncertainties impacting on the estimation of hazard probabilities. This shift addresses the limitations of point estimates and thresholds that oversimplify hazard assessment, allowing for the integration of kinetic variability and uncertainty metrics into risk models. By leveraging modern technologies and expansive toxicological data, probabilistic approaches offer a comprehensive evaluation of chemical safety. This paper summarizes a workshop held in 2023 and discusses the technological and data-driven enablers, and the challenges faced in their implementation, with particular focus on perturbation of biology as the basis of hazard estimates. The future of toxicological risk assessment lies in the successful integration of these probabilistic models, promising more accurate and holistic hazard evaluations.</p>\",\"PeriodicalId\":520550,\"journal\":{\"name\":\"ALTEX\",\"volume\":\" \",\"pages\":\"413-434\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ALTEX\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14573/altex.2501291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/26 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ALTEX","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14573/altex.2501291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/26 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
From cellular perturbation to probabilistic risk assessments.
Chemical risk assessment is evolving from traditional deterministic approaches to embrace probabilistic methodologies, where risk of hazard manifestation is understood as a more or less probable event depending on exposure, individual factors, and stochastic processes. This is driven by advancements in human stem cells, complex tissue engineering, high-performance computing, and cheminformatics, and is more recently facilitated by large-scale artificial intelligence models. These innovations enable a more nuanced understanding of chemical hazards, capturing the complexity of biological responses and variability within populations. However, each technology comes with its own uncertainties impacting on the estimation of hazard probabilities. This shift addresses the limitations of point estimates and thresholds that oversimplify hazard assessment, allowing for the integration of kinetic variability and uncertainty metrics into risk models. By leveraging modern technologies and expansive toxicological data, probabilistic approaches offer a comprehensive evaluation of chemical safety. This paper summarizes a workshop held in 2023 and discusses the technological and data-driven enablers, and the challenges faced in their implementation, with particular focus on perturbation of biology as the basis of hazard estimates. The future of toxicological risk assessment lies in the successful integration of these probabilistic models, promising more accurate and holistic hazard evaluations.