Combined Exposures and Mixtures Research Program

组合暴露和混合物研究计划

• 批准号: 10696799
• 负责人: Cynthia Rider
• 金额: $ 153.76万
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10696799
• 关键词: Address; Animal Model; Animals; Area; Biological Assay; Botanicals; Chemicals; Collaborations; Complex Mixtures; Data; Data Analyses; Decision Making; Discipline; Dose; Drug Kinetics; Epidemiology; Evaluation; Exposure to; Extramural Activities; Flame Retardants; Foundations; Fractionation; Future; Goals; HIV; Human; Individual; Intramural Research; Joints; Methods; Modeling; National Institute of Environmental Health Sciences; Pathway interactions; Pharmacologic Substance; Poly-fluoroalkyl substances; Process; Research; Research Design; Research Training; Resources; Risk; Risk Assessment; Structure; Systems Biology; Testing; Therapeutic; Time; Toxic effect; Toxicology; Translating; Uncertainty; Vulnerable Populations; Work; adverse outcome; base; environmental justice; exposed human population; hazard; improved; in vitro Assay; in vivo; innovation; meetings; method development; phthalates; programs; psychosocial; response; statistics; stressor; tool; working group

Our work on defined mixtures strengthens our ability to predict the effects of mixtures on the basis of their individual constituents. It will also contribute to decreasing the uncertainty involved in component-based risk assessment by conducting hypothesis-driven research on the current assumptions (e.g., dose addition for estimating cumulative effects of like-acting chemicals, lack of interactions among chemicals within a class). Our work on defined mixtures approaches leverages the toxicological data that already exist for single chemicals to estimate effects of mixtures. It is anticipated that the lessons learned, and statistical tools developed during these projects, will be useful in projects under other strategic focus areas that involve environmental mixtures (e.g., per- and polyfluoroalkyl substances, phthalates, and flame retardants) as well as combination pharmaceuticals (e.g., human immunodeficiency virus (HIV) therapeutics). Future work will further build on this foundation by addressing combinations of chemical and nonchemical stressors. DNTP is currently applying the concept of sufficient similarity of complex mixtures to its test article selection process for botanicals; further development of methods to evaluate sufficient similarity will also be a critical contribution in interpreting data generated from other complex mixture projects. For example, sufficient similarity approaches allow for better definition of when we can extrapolate findings from a tested substance to related substances with variable composition, whereas bioassay guided fractionation and polypharmacokinetics can allow for identification of the bioactive constituent(s). These projects will improve our ability to translate animal study findings from complex mixture exposures to better understand their human relevance. The use of Adverse Outcome Pathway (AOP) networks to provide a framework for mechanistic data and generate testable hypotheses regarding the joint action of combined exposures represents the leading edge of mixtures research. The DNTP is currently developing projects to evaluate the AOP network approach. In addition, we are exploring combinations of chemical and nonchemical stressors to better recapitulate real-world human exposures. Innovative methods for simulating nonchemical stressors in model organisms will advance testing capabilities at DNTP and allow us to begin addressing important environmental justice issues related to unequal environmental and psychosocial burdens in vulnerable populations. DNTP has the resources required to evaluate both individual components and whole mixtures using cutting-edge chemical characterization tools, in vitro assays, and in vivo studies. We have mixtures research experts within DNTP and at the National Institute of Environmental Health Sciences (NIEHS) (Division of Intramural Research and Division of Extramural Research and Training) in complementary disciplines (e.g., statistics, epidemiology) who share ideas and develop collaborations through quarterly meetings of the trans-NIEHS Combined Exposures/Mixtures Working Group. We regularly engage with our federal partners and other stakeholders to design studies that address current mixtures of concern, provide data useful in the risk assessment of mixtures, and refine predictive methods for mixtures evaluation.

我们在定义的混合物上的工作增强了我们根据其各个成分来预测混合物影响的能力。它还将通过对当前假设进行假设驱动的研究（例如，估算诸如作用化学物质的累积效应，班级中的化学物质之间缺乏相互作用的累积效应）进行假设驱动的研究来减少基于组件的风险评估的不确定性。我们在定义的混合物上的工作利用了单个化学物质已经存在的毒理学数据来估计混合物的影响。可以预见的是，这些项目期间所学习的经验教训和统计工具将在其他战略重点领域的项目中很有用，这些项目涉及环境混合物（例如，per-和多氟烷基物质，phthalates和phthalates和flame blebardates和flame bleasartes）以及组合药物（例如，人类免疫缺陷式病毒率（Hiv）。未来的工作将通过解决化学和非化学压力源的组合来进一步以此为基础。 DNTP目前正在将复杂混合物足够相似性的概念应用于植物学的测试文章选择过程。进一步开发评估足够相似性的方法也将是解释其他复杂混合项目产生的数据的重要贡献。例如，足够的相似性方法可以更好地定义我们何时可以将发现的发现从测试物质推断为具有可变组成的相关物质，而生物测定的指导分级分级和多疗法可以识别生物活性成分。这些项目将提高我们将动物研究结果从复杂混合物暴露的转化能力，以更好地了解其人类的相关性。 使用不良结果途径（AOP）网络为机械数据提供框架，并就合并暴露的联合作用产生可检验的假设，代表了混合研究的前沿。 DNTP目前正在开发用于评估AOP网络方法的项目。此外，我们正在探索化学和非化学应激源的组合，以更好地概括现实世界中的人类暴露。模拟生物体中模拟非化学压力源的创新方法将提高DNTP的测试能力，并使我们能够开始解决与脆弱人群中与不平等环境和社会心理负担有关的重要环境正义问题。 DNTP具有使用尖端的化学特征工具，体外测定和体内研究所需的资源来评估单个组件和整个混合物。我们在DNTP和美国国家环境健康科学研究所（NIEHS）（NIEHS）（NIEHS）的混合物研究专家（辅助学科（例如统计，流行病学，流行病学）的校内研究和分工），他们通过跨Niehs的季度会议进行了合作，他们共享思想，并通过跨Niehs的季度会议进行合作。我们定期与联邦合作伙伴和其他利益相关者互动，以设计解决当前关注的混合物，提供对混合物风险评估的数据，以及提高混合评估的预测方法的数据。