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Project 2: Enhancement of Biokinetics using Physiologically-Based Models for Internalized Radionuclides

Project 2: Enhancement of Biokinetics using Physiologically-Based Models for Internalized Radionuclides
项目 2:使用基于生理学的内化放射性核素模型增强生物动力学
批准号:
10589877
负责人:
Shaheen Azim Dewji
金额:
$37.03万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-03-10 至 2027-02-28

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中文摘要
翻译
项目2:摘要 放射性或核(RN)事件导致大规模人群暴露后,放射性核素生物动力学模型 可用于测定各种不同环境中内化放射性核素随时间变化的活度浓度。 在分诊期间根据需要对身体的组织和器官进行剂量评估。RN事件可以包括 从放射性弥散装置、简易核装置或核反应堆释放的放射性核素 意外事件国际辐射防护委员会(ICRP)的生物动力学模型是 当前被实现为确定性的(即,单一“参考”)主要开发的基于隔室的模型 用于职业辐射防护。我们假设,新的生物动力学模型与现实的RN 代表暴露人群的源项参数和代谢变异性可用于可靠地 预测放射性核素在不同生物组织水平的生物分布和反应。总目标 项目2的主要目的是将放射性核素摄入量和全身生物平衡的生理模型与 关键模型参数的随机概率分布。构建现实主义的核心挑战 代表暴露非参考人群的生物动力学模型缺乏对基本 生理过程,从定义现实的源术语从RN事件和翻译到机械 定义吸入摄入动力学、血液摄取和排泄的参数。拟议的扩大 生物动力学建模将首次允许体内测定和预测新的去甲肾上腺素的功效 在代表性人群的急性RN摄取后,创新的基本要素 在项目2中,包括:(1)开发针对真实RN源的生物动力学模型;(2)进行 ICRP 133人体呼吸道模型真实RN源项和生物动力学随机分析 行为;(3)暴露人群吸入剂量系数的制定(年龄/性别/形态测量- 具体)从现实的曝光源条款;(4)计算流体和粒子动力学的建设 使用真实源项和测量的基于CFPD的粒子摄入生理口肺模型 肺中颗粒分布的数据;(5)使用基于生理学的机器学习 药代动力学模型,以确定时间依赖性的摄取,保留,排泄和重建 放射性核素,以评估效能的decidation对策剂;(6)发展一个在 与用于摄入重建的随机生物计量学相关的体内放射分类身体扫描系统, 监测脱钙治疗。拟议的工作将支持项目1软件提供非 参考吸入剂量系数,以及用于分诊的检测器效率全身响应函数。 项目1和3的数据将用于创建基于网格的CFPD吸入动力学模型。项目4 将利用动物数据来提出脱钙效果的动物-人比例模型 代理人,包括年龄和性别变量,如果可能。
英文摘要
PROJECT 2: ABSTRACT Following mass population exposures from radiological or nuclear (RN) events, radionuclide biokinetic models can be used to determine the time-dependent activity concentrations of internalized radionuclides in various tissues and organs of the body as needed for dose assessment during triage. RN events may include radionuclide releases from a radiological dispersion device, an improvised nuclear device, or a nuclear reactor accident event. Biokinetic models from the International Commission on Radiological Protection (ICRP) are currently implemented as deterministic (i.e., single “reference”) compartment-based models developed primarily for occupational radiation protection purposes. We hypothesize that new biokinetic models with realistic RN source term parameters and metabolic variability representative of an exposed population can be used to reliably predict radionuclide biodistribution and responses at different levels of biological organization. The overall goal of Project 2 is to integrate physiologically-based models of radionuclide intake and systemic biokinetics with stochastic probability distributions of key model parameters. The core challenge in constructing realistic biokinetic models representative of an exposed non-reference population is the lack of consideration of basic physiological processes, from defining realistic source terms from RN events and translation to mechanistic parameters that define inhalation intake kinetics, uptake into blood, and excretion. The proposed expansion in biokinetic modeling will for the first time allow in-vivo assay and prediction of the efficacy of novel decorporation agents in humans following an acute RN uptake for a representative population. Primary elements of innovation in Project 2 include: (1) Development of biokinetic models specific to realistic RN sources; (2) Conducting stochastic analysis of ICRP 133 Human Respiratory Tract Model for realistic RN source term and biokinetic behavior; (3) Development of inhalation dose coefficients for exposed population (age/sex/morphometry- specific) from realistic exposure source terms; (4) Construction of computational fluid and particle dynamics (CFPD)-based physiological mouth-lung model of particle intake using realistic source terms and measurement data of particulate distribution in the lungs; (5) Employment of machine learning with physiologically-based pharmacokinetic models to determine the time-dependent uptake, retention, excretion, and reconstruction of radionuclides to evaluate the efficacy of decorporation countermeasure agents; and (6) Development of an in- vivo radiological triage body scanning system correlated with stochastic biokinetics for intake reconstruction and monitoring of decorporation therapy. The proposed work will support Project 1 software in providing non- reference inhalation dose coefficients, as well as detector efficiency whole body response functions for triage. Project 1 and 3 data will be leveraged to a create mesh-based CFPD model of inhalation kinetics. Project 4 animal data will be leveraged to propose animal-to-human scaling models of the efficacy of the decorporation agent, inclusive of age and sex variables where posible.
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Project 2: Enhancement of Biokinetics using Physiologically-Based Models for Internalized Radionuclides
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