Multiscale Modeling of Lung Disease-Influenced Aerosol Dosimetry

摘要 这项提议的总体目标是开发能够预测沉积的多尺度计算模型 吸入性气雾剂在健康或痛苦的个体呼吸系统的所有区域 慢性阻塞性肺疾病(COPD)等呼吸系统疾病。慢性阻塞性肺病通常与 接触有毒/刺激性气溶胶(如香烟烟雾、职业性粉尘/烟雾、环境PM2.5 空气污染等)并对数百万易感人群的生活质量产生不利影响。与.一起 哮喘，慢性阻塞性肺病是美国第三大主要疾病死亡原因。此外，呼吸系统 已被开发为治疗COPD的局部和系统治疗气雾剂的潜在途径， 哮喘或其他疾病，在这些疾病中，药物可能不像其他给药途径那样有效。因此， 预测气溶胶剂量学模型的发展一直是环境毒理学和环境毒理学的主要焦点 数十年来的医药健康研究。到目前为止，预测吸入性药物沉积的挑战 在疾病条件下的气溶胶在很大程度上没有得到满足。我们建议利用我们已有的先进技术 调查小组和其他人在成像、气溶胶暴露和测量方面取得了进展，以及 开发、实验评估和改进预测地点的多尺度模型的计算模型- 和区域特定的气溶胶在整个呼吸系统的沉积，并研究沉积是如何 受疾病影响。我们建议的模型将通过逐步、模块化的3D集成来开发 从鼻子和嘴巴延伸的计算流体动力学(CFD)气流和气溶胶跟踪模型 到肺的传导通道，每个3D肺通道双向耦合到下部 描述气溶胶传输和气溶胶传输的三维气流、气溶胶传输和组织力学模型 在整个呼吸系统和整个呼吸周期内沉积(目标1)。模特们将 最初是为健康人开发的(目标2)，然后是疾病(目标3)，使用已公布的呼吸道和 组织力学数据，以及在没有人体数据的情况下，从我们的4D成像和气溶胶中提取 健康和疾病大鼠的沉积数据。我们多尺度链接的模块化方法将使用户能够 随着新的进展，替换单个模型组件。将对多尺度模型进行评估 并使用丰富的多模式3D成像和气溶胶沉积测量数据库进行进一步改进 包括健康人群和慢性阻塞性肺病人群的人类志愿者。我们工作的预期结果将是 可用于新模型开发的一套模块化、多比例模型和标准化方法 由研究人员、风险评估员或临床医生预测人类呼吸系统中的气溶胶沉积 在健康和疾病条件下，除了底层的算法和框架外，还可以有效 未来用户定义的、个性化的气雾剂量学模型的链接。

Abstract The overall goal of this proposal is to develop multiscale computational models that can predict the deposition of inhaled aerosols in all regions of the respiratory system of individuals that are either healthy or suffering from respiratory diseases such as COPD (chronic obstructive pulmonary disease). COPD is generally associated with exposure to toxic/irritant aerosols (e.g. cigarette smoke, occupational dusts/fumes, environmental PM2.5 air pollution, etc.) and adversely affects the quality of life for millions of susceptible individuals. Along with asthma, COPD is the third leading disease-based cause of death in the U.S. In addition, the respiratory system has been exploited as a potential route for local and systemic delivery of therapeutic aerosols for COPD, asthma, or other diseases where drugs may not be as effective by other routes of administration. As a result, the development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. To date, the challenge of predicting the deposition of inhaled aerosols under disease conditions has been largely unmet. We propose to utilize advancements our established team of investigators and others have made in imaging, aerosol exposure and measurement, and computational modeling to develop, experimentally evaluate, and refine multiscale models that predict site- and region-specific deposition of aerosols throughout the respiratory system and to study how deposition is influenced by disease. Our proposed models will be developed by a step-wise, modular integration of 3D computational fluid dynamic (CFD) airflow and aerosol tracking models that extend from the nose and mouth to the conducting airways of the lung with each 3D pulmonary airway bi-directionally coupled with lower dimensional airflow, aerosol transport, and tissue mechanics models to describe aerosol transport and deposition over the full respiratory system and throughout the complete breathing cycle (Aim 1). Models will initially be developed for healthy individuals (Aim 2) followed by disease (Aim 3) using published airway and tissue mechanics data and, where data do not exist for humans, extracted from our 4D imaging and aerosol deposition data in healthy and diseased rats. Our modular approach to multiscale linkages will allow users to substitute individual model components as new advances are made. The multiscale models will be evaluated and further refined using a rich database of multi-modal 3D imaging and aerosol deposition measurements in human volunteers that include both healthy and COPD cohorts. The expected outcome of our work will be a suite of modular, multiscale models and standardized approaches for new model development that can be used by researchers, risk assessors, or clinicians to predict aerosol deposition in the respiratory systems of humans under healthy and disease conditions in addition to the underlying algorithms and framework for effective linking of user-defined, personalized aerosol dosimetry models in the future.