Developing Computational Models to Understand and Predict Adverse Human Health Effects Associated with Exposure to Environmental Chemicals
Developing Computational Models to Understand and Predict Adverse Human Health Effects Associated with Exposure to Environmental Chemicals
批准号:
10714054
负责人:
Anders Wallqvist
金额:
$106.0万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
未结题
起止时间:
至
关键词:
AccountingAcuteAddressAdoptionAffectAgreementBiochemical PathwayBiologicalBiological ModelsBiologyCardiovascular systemChronicComputer ModelsDevelopmentDiseaseEnvironmentEvaluationExposure toHealthHumanIndividualLinkMathematicsMetabolicMissionModelingMolecularNational Institute of Environmental Health SciencesOutcomePersonsPopulationPredispositionPreventiveResearchRodentScienceSystemToxicologyTranslatingbasebiological systemsbody systemdata modelingenvironmental chemicalevidence basegenome-widehazardimprovedinnovationmathematical modelmulti-scale modelingreproductiveresearch and developmentresponsesafety assessmentsextooltool development
中文摘要
NIEHS的使命是发现环境如何影响人们,以促进更健康的生活。转化毒理学部(DTT)通过开发和应用创新的、与人类相关的工具和策略来表征暴露于环境化学品所带来的危害,从而引领毒理学的转型,从而为这一使命做出贡献。DTT最近确定了三个总体目标,作为其战略调整的一部分:i)通过有意应用转化毒理学管道(TTP),加速成为更具预测性,精确性和预防性的科学; ii)提供基于证据的方法来识别和理解当代和常见疾病的潜在环境因素;提高我们进行和交流基于物质的危害评估的能力,使之更具转化性、创新性和反应性。DTT已经确定开发和利用生物系统的多尺度计算模型的能力是一个关键需求。 多尺度建模使用数学和计算来在多于一个尺度上定量地表示和模拟系统,同时在功能上链接跨这些尺度的数学模型,这些尺度包括原子、分子、细胞、器官、系统(例如,心血管、生殖等),个体和(子)群体。
该项目的目的是进一步研究和开发DTT可用于其转化毒理学管道(TTP)的工具,以更好地预测急性和慢性暴露于环境化学品及其混合物对人类健康造成的潜在不利影响。 根据这一机构间协议,研究计划将评估先进计算方法的应用,这些方法整合并模拟了人类和啮齿动物生物学多个尺度的数据,开始解决必须克服的三个关键挑战,以实现真正预测人类健康结果的安全评估范式的采用:将性别作为生物学变量;准确地将毒理学发现转换为生物学尺度和物种之间的结果;表征个体间的生物学变异性和易感性
英文摘要
The mission of NIEHS is to discover how the environment affects people in order to promote healthier lives. The Division of Translational Toxicology (DTT) contributes to that mission by leading the transformation of toxicology through the development and application of innovative, human-relevant tools and strategies to characterize hazards presented by exposure to environmental chemicals. Three overarching objectives recently identified by DTT as part of its strategic realignment are to: i) accelerate progress toward becoming a more predictive, precise, and preventive science through the deliberate application of a Translational Toxicology Pipeline (TTP); ii) provide an evidence-based approach to identifying and understanding potential environmental contributors to contemporary and common diseases; and iii) improve our ability to conduct and communicate substance-based hazard evaluations that are more translational, innovative, and responsive. DTT has identified the ability to develop and utilize multi-scale computational models of biological systems as a critical need. Multiscale modeling uses mathematics and computation to quantitatively represent and simulate a system at more than one scale while functionally linking the mathematical models across these scales, which include atomic, molecular, cellular, organ, system (e.g., cardiovascular, reproductive, etc..), individual, and (sub)populations.
The purpose of this project is to further the research and development of tools that DTT can use in its Translational Toxicology Pipeline (TTP) to better predict potential adverse human health effects caused by acute and chronic exposure to environmental chemicals and mixtures thereof. The research plan under this interagency agreement will assess the application of advanced computational approaches that integrate and model data across multiple scales of human and rodent biology to begin addressing three key challenges that must be overcome to enable the adoption of safety assessment paradigms that are truly predictive of human health outcomes: Accounting for sex as a biological variable; accurately translating toxicological findings across biological scales and between species; characterizing inter-individual biological variability and susceptibility
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Developing Computational Models to Understand and Predict Adverse Human Health Effects Associated with Exposure to Environmental Chemicals
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批准号:10913274
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项目类别:
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资助金额:$106.0万
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财政年份:--
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负责人:Anders Wallqvist
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依托单位:
海外基金