S10-02化学品安全评估的综合方法：建立单一的SSbD健康模型

IF 2.9 3区医学 Q2 TOXICOLOGY

Toxicology letters Pub Date : 2025-09-01 DOI:10.1016/j.toxlet.2025.07.072

D. Greco

{"title":"S10-02化学品安全评估的综合方法：建立单一的SSbD健康模型","authors":"D. Greco","doi":"10.1016/j.toxlet.2025.07.072","DOIUrl":null,"url":null,"abstract":"<div><div>Toxicology is going through profound changes as the focus of investigation is shifting from the observation of apical phenomena to mechanistic aspects of the exposure. Toxicogenomics aims at clarifying the mechanism of action (MOA) of chemicals by using omics assays. The Adverse Outcome Pathways (AOP) concept is also emerging to contextualise toxicogenomics-derived MOA.</div><div>At the Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE) of Tampere University, we use advanced modelling of large amounts of data to anchor molecular assays to AOPs. We also combine big data science, artificial intelligence (AI), network science, toxicogenomics, molecular assays and cell technology to analyse a comprehensive knowledge graph comprising tens of millions of data points with the aim to develop AOP-derived New Methodology Approaches (NAMs). The goal is to build multi-scale models to clarify the mechanism of action of exposures from molecular to planetary scales.</div><div>In this talk, I will discuss how integrated data-driven approaches can be used to unify the currently fragmented comprehension of the chemical-biological interactions, while guiding the development of safe and sustainable by design (SSbD) and effective by design (EbD) chemicals, drugs, and materials.</div></div>","PeriodicalId":23206,"journal":{"name":"Toxicology letters","volume":"411 ","pages":"Page S23"},"PeriodicalIF":2.9000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"S10-02 Integrated approaches for chemical safety assessment: towards one health models for SSbD\",\"authors\":\"D. Greco\",\"doi\":\"10.1016/j.toxlet.2025.07.072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Toxicology is going through profound changes as the focus of investigation is shifting from the observation of apical phenomena to mechanistic aspects of the exposure. Toxicogenomics aims at clarifying the mechanism of action (MOA) of chemicals by using omics assays. The Adverse Outcome Pathways (AOP) concept is also emerging to contextualise toxicogenomics-derived MOA.</div><div>At the Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE) of Tampere University, we use advanced modelling of large amounts of data to anchor molecular assays to AOPs. We also combine big data science, artificial intelligence (AI), network science, toxicogenomics, molecular assays and cell technology to analyse a comprehensive knowledge graph comprising tens of millions of data points with the aim to develop AOP-derived New Methodology Approaches (NAMs). The goal is to build multi-scale models to clarify the mechanism of action of exposures from molecular to planetary scales.</div><div>In this talk, I will discuss how integrated data-driven approaches can be used to unify the currently fragmented comprehension of the chemical-biological interactions, while guiding the development of safe and sustainable by design (SSbD) and effective by design (EbD) chemicals, drugs, and materials.</div></div>\",\"PeriodicalId\":23206,\"journal\":{\"name\":\"Toxicology letters\",\"volume\":\"411 \",\"pages\":\"Page S23\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Toxicology letters\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378427425016558\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Toxicology letters","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378427425016558","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

毒理学正在经历深刻的变化，因为研究的重点正在从观察暴露的顶点现象转向机理方面。毒物基因组学旨在通过组学分析阐明化学物质的作用机制。不良后果途径（AOP）的概念也出现在毒物基因组学衍生的MOA的背景下。在坦佩雷大学的芬兰综合方法开发和验证中心（FHAIVE），我们使用大量数据的先进建模来将分子分析固定在AOPs上。我们还将大数据科学、人工智能（AI）、网络科学、毒物基因组学、分子分析和细胞技术结合起来，分析包含数千万个数据点的综合知识图谱，旨在开发aop衍生的新方法论方法（NAMs）。目标是建立多尺度模型，以阐明从分子到行星尺度暴露的作用机制。在这次演讲中，我将讨论如何使用集成的数据驱动方法来统一目前对化学-生物相互作用的碎片化理解，同时指导安全可持续设计（SSbD）和有效设计（EbD）化学品，药物和材料的发展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

S10-02 Integrated approaches for chemical safety assessment: towards one health models for SSbD

Toxicology is going through profound changes as the focus of investigation is shifting from the observation of apical phenomena to mechanistic aspects of the exposure. Toxicogenomics aims at clarifying the mechanism of action (MOA) of chemicals by using omics assays. The Adverse Outcome Pathways (AOP) concept is also emerging to contextualise toxicogenomics-derived MOA.

At the Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE) of Tampere University, we use advanced modelling of large amounts of data to anchor molecular assays to AOPs. We also combine big data science, artificial intelligence (AI), network science, toxicogenomics, molecular assays and cell technology to analyse a comprehensive knowledge graph comprising tens of millions of data points with the aim to develop AOP-derived New Methodology Approaches (NAMs). The goal is to build multi-scale models to clarify the mechanism of action of exposures from molecular to planetary scales.

In this talk, I will discuss how integrated data-driven approaches can be used to unify the currently fragmented comprehension of the chemical-biological interactions, while guiding the development of safe and sustainable by design (SSbD) and effective by design (EbD) chemicals, drugs, and materials.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊