Project 3: Dosimetry and Structure-Activity Relationships for Nanomaterial Risk A

项目 3：纳米材料风险 A 的剂量测定和构效关系

• 批准号: 8274449
• 负责人: Justin Gary Teeguarden
• 金额: $ 15.66万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 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/8274449
• 关键词: Adult; Adverse effects; Age; Breathing; Cells; Characteristics; Child; Data; Derivation procedure; Development; Dose; Drug Kinetics; Engineering; Ensure; Generations; Goals; Hazard Assessment; Hazard Models; Health; Human; In Vitro; Inbred BALB C Mice; Individual; Inflammation; Inflammatory; Inflammatory Response; Instruction; Laboratory Finding; Lung; Measures; Mediating; Metric; Modeling; Mus; Outcome; Particle Size; Population; Quantitative Structure-Activity Relationship; Research; Research Personnel; Respiratory System; Respiratory tract structure; Risk; Risk Assessment; Rodent; Route; Scientific Evaluation; Series; Structure; Structure-Activity Relationship; System; Testing; Tissues; Toxic effect; Translating; Translations; base; dosimetry; exposed human population; hazard; improved; in vitro Model; in vivo; macrophage; metal oxide; mouse model; nanomaterials; nanoparticle; novel; novel strategies; particle; pharmacokinetic model; predictive modeling; programs; response; tool

The overarching goal of this project is improved protection of human health through the advancement of risk assessment tools for engineered nanomaterials that allow translation of dose-response data and hazard rankings across in vitro and in vivo systems, between species, and across populations with unique sensitivities. We HYPOTHESIZE that using quantitative structure activity relationship models and novel in vitro and in vivo target tissue dosimetry models, in vitro hazard rankings and no adverse effect levels can be accurately scaled to in vivo for use in risk assessment. This hypothesis will be tested and missing, widely applicable dosimetry tools developed, under the following SPECIFIC AIMS: Construct, calibrate, and apply scalable models of ENP pharmacokinetics and dosimetry to translate dose-response relationships between in vitro and in vivo systems, between species, and between normal and sensitive individuals. 2): Predict in vivo hazard rankings of metal oxide nanoparticles from in vitro data using target tissue dosimetry based quantitative structure activity models and test predictions in a mouse model of pulmonary inflammafion 3): Establish and apply a dosimetry enabled framework for derivation of exposure limits for ENP using in vivo (data rich), and in vitro/quantitative structure activity (data limited) inflammation dose-response data. SIGNIFICANCE: Our contribution to the field of nanomaterial risk assessment will be the development and application of dosimetry models at multiple scales used in concert with mechanistic and dose-response data to develop more accurate predictive models of hazard and toxicity and derive exposure limits for multiple nanoparticles. This contribution is significant because through tools available to the consortium and other researchers and agencies, it will provide the first complete nanomaterial dosimetry platform for extrapolation, and an example of its use for the translafion, and interpretation of in vitro and rodent in vivo nanomaterial data for risk assessment. Thus, critical advances in the risk assessment paradigm for nanomaterials are expected, particulariy in enabling its evolufion towards a paradigm of prediction.

该项目的总体目标是通过改进工程纳米材料的风险评估工具来改善对人类健康的保护，这些工具允许在体外和体内系统、物种之间以及具有独特敏感性的人群之间转换剂量反应数据和危害等级。我们假设，使用定量构效关系模型和新型体外和体内靶组织剂量测定模型，体外危害等级和无不良反应水平可以准确地缩放到体内用于风险评估。这一假设将被测试和失踪，广泛 在以下特定目标下开发的适用剂量测定工具：构建、校准和应用ENP药代动力学和剂量测定的可扩展模型，以转换体外和体内系统之间、物种之间以及正常和敏感个体之间的剂量反应关系。2）、使用基于靶组织剂量测定的定量结构活性模型和肺部炎症小鼠模型中的测试预测，从体外数据预测金属氧化物纳米颗粒的体内危害等级3）： 使用体内（数据丰富）和体外/定量结构活性（数据有限）炎症剂量反应数据，建立并应用剂量测定启用框架，以推导ENP的暴露限值。 重要性：我们对纳米材料风险评估领域的贡献将是在多个尺度上开发和应用剂量学模型，并与机械和剂量反应数据相结合，以开发更准确的危害和毒性预测模型，并推导出多种纳米材料的暴露限值。 纳米粒子这一贡献非常重要，因为通过该联盟和其他研究人员和机构可用的工具，它将提供第一个完整的纳米材料剂量测定平台用于外推，以及其用于体外和啮齿动物体内纳米材料翻译和解释的示例 风险评估数据。因此，预计纳米材料风险评估范例将取得重大进展，特别是使其能够向预测范例发展。