Project 4

项目4摘要 项目4旨在开发一种体外到体内的翻译测试策略，以评估组织间和组织间 对复杂环境暴露的反应的个体变异性。这一目标是总体目标的关键部分 德克萨斯农工大学超级基金研究中心对人类健康的描述和管理策略 与暴露于环境紧急动员的危险物质有关的风险 开发可供急救人员、受影响社区和政府使用的工具 参与现场管理和清理的机构。在过去的融资期间，我们不仅开发了多个- 高含量/高通量复杂环境暴露的组织“生物交叉阅读”方法 使用人诱导多能干细胞(IPSC)的检测，但也证明了其在定量 通过一些案例研究评估复杂环境暴露的危险 在社区、国家和国际范围内。这些研究表明，新的方法方法(NAMS) 可用于评估现实生活中暴露的风险。我们的中心假设仍然是一个分层的 基于风险的安全评估策略，利用人体器官型体外培养，结合种群- 基于反向毒物动力学，可以用来准确地描述联合暴露于 环境紧急情况下的危险物质。首先，我们将开发一个以人口为基础的人类 表征组织间和个体间对复杂环境反应的变异性的体外方法 曝光。我们将检验这一假设，即基于人类群体的体外模型可以改进风险预测。 并描述组织间和个体间变异的分子基础和程度。第二, 我们将开发一种高通量的反向毒物动力学(RTK)建模方法，用于复杂的接触 实现环境样品的体外-体内外推(IVIVE)。因为IVIVE对于 在人类健康的背景下，对体外NAMS数据的解释，我们假设新的暴露 分析和新的芯片上器官模型可以提供浓度和组合暴露依赖的RTK IVE所需的参数，最终能够更准确地预测体内效应。第三，作为艺术的 中心的灾难研究响应(DR2)方法，我们将演示人类多方面的应用。 组织和人口范围的高通量体外模型对灾难的响应研究。我们将向您展示 在过去的资助期发展的“生物阅读”方法可以通过测试 假设体外毒性数据可以用来定量预测和表征对健康的危害 环境样本。我们将与所有项目合作，使用他们的样本或合作进行分析、 分子和生物医学工程方法和技术。我们将与所有核心合作进行数据分析 和管理、地理空间分析以及将我们的研究翻译到受影响的社区和其他 利益相关者。该项目的数据和方法在应对灾害方面将具有至关重要的作用。

Project 4 ABSTRACT Project 4 aims to develop a translational in vitro-to-in vivo testing strategy for evaluating the inter-tissue and inter- individual variability in responses to complex environmental exposures. This goal is a critical part of the overall strategy of the Texas A&M University Superfund Research Center to characterize and manage the human health risks associated with exposure to environmental emergency-mobilized hazardous substances through the development of tools that can be used by first responders, the impacted communities, and the government bodies involved in site management and cleanup. In the past funding period, we not only developed a multi- tissue “biological read-across” approach for complex environmental exposures in high-content/high-throughput assays using human induced pluripotent stem cells (iPSC), but also demonstrated its utility for quantitative estimation of hazard of complex environmental exposures through a number of case studies that spanned community, national and international scales. These studies show how new approach methodologies (NAMs) can be applied for assessment of risks from real-life exposures. Our central hypothesis remains that a tiered risk-based strategy for safety evaluation utilizing human organotypic in vitro cultures, combined with population- based reverse toxicokinetics, can be used to accurately characterize the risks posed by combined exposures to hazardous substances during environmental emergencies. First, we will develop a population-based human in vitro approach to characterize inter-tissue and inter-individual variability in responses to complex environmental exposures. We will test the hypothesis that human population-based in vitro models can refine hazard predictions and characterize the molecular underpinnings and extent of inter-tissue and inter-individual variability. Second, we will develop a high-throughput reverse toxicokinetics (RTK) modeling approach for complex exposures to enable in vitro-to-in vivo extrapolation (IVIVE) of environmental samples. Because IVIVE is critical for interpretation of in vitro NAMs data in the context of human health, we hypothesize that novel exposomic analyses and new organ-on-a-chip models can provide concentration- and combined exposure-dependent RTK parameters needed for IVIVE, ultimately enabling more accurate predictions of effects in vivo. Third, as art of Center’s Disaster Research Response (DR2) approach, we will demonstrate the application of human multi- tissue and population-wide high-throughput in vitro models to disaster research response. We will show how the “biological read-across” method developed in the past funding period can be applied to DR2 by testing the hypothesis that in vitro toxicity data can be used to quantitatively predict and characterize health hazard of environmental samples. We will partner with all Projects to use their samples or collaborate on analytical, molecular and biomedical engineering methods and techniques. We will work with all Cores for data analysis and management, geospatial analysis, and translation of our research to the impacted communities and other stakeholders. The data and methods from this project will be of critical importance in responses to disasters.