Multiscale Modeling of Lung Disease-Influenced Aerosol Dosimetry

肺部疾病影响的气溶胶剂量测定的多尺度建模

• 批准号: 10436278
• 负责人: CHANTAL DARQUENNE
• 金额: $ 65万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10436278
• 关键词: 3-Dimensional; 4D Imaging; Aerosols; Affect; Air Movements; Air Pollution; Algorithms; Asthma; Biological; Breathing; Caliber; Cause of Death; Chemicals; Chronic Obstructive Pulmonary Disease; Computer Models; Coupled; Coupling; Data; Databases; Deposition; Development; Dimensions; Disease; Dose; Drug Delivery Systems; Dust; Environmental Exposure; Environmental Health; Exposure to; Future; Goals; Health; Heterogeneity; Human; Human Volunteers; Image; Individual; Indoor Air Pollution; Inhalation; Irritants; Link; Liquid substance; Lung; Lung diseases; Measurement; Mechanics; Methods; Modeling; Nose; Occupational; Occupational Exposure; Oral cavity; Outcome; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Property; Published Database; Publishing; Quality of life; Rattus; Research; Research Personnel; Resolution; Respiratory Disease; Respiratory System; Risk; Risk Assessment; Route; Site; Standardization; Therapeutic; Therapeutic Intervention; Three-Dimensional Imaging; Tissues; Work; X-Ray Computed Tomography; base; cigarette smoke; cohort; data submission; dosimetry; environmental toxicology; fine particles; improved; model development; multi-scale modeling; multimodality; novel; novel strategies; particle; pathogen exposure; physical property; predictive modeling; respiratory; ventilation; volunteer

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.

摘要

项目成果

Innovative preclinical models for pulmonary drug delivery research.

• DOI: 10.1080/17425247.2020.1730807
• 发表时间: 2020-04
• 期刊: Expert opinion on drug delivery
• 影响因子: 6.6
• 作者: Ehrmann S;Schmid O;Darquenne C;Rothen-Rutishauser B;Sznitman J;Yang L;Barosova H;Vecellio L;Mitchell J;Heuze-Vourc'h N
• 通讯作者: Heuze-Vourc'h N

Automated bidirectional coupling of multiscale models of aerosol dosimetry: validation with subject-specific deposition data.

• DOI: 10.1016/j.jaerosci.2023.106233
• 发表时间: 2023-07
• 期刊: Journal of aerosol science
• 影响因子: 4.5
• 作者: A. Kuprat;O. Price;B. Asgharian;R.K. Singh;S. Colby;K. Yugulis;R. Corley;C. Darquenne

The Effect of Aging on Aerosol Bolus Deposition in the Healthy Adult Lung: A 19-Year Longitudinal Study.

• DOI: 10.1089/jamp.2019.1566
• 发表时间: 2020-06
• 期刊: Journal of aerosol medicine and pulmonary drug delivery
• 影响因子: 3.4
• 作者: C. Darquenne;G. Prisk

In Silico Quantification of Intersubject Variability on Aerosol Deposition in the Oral Airway.

口腔气道中气溶胶沉积的受试者间变异性的计算机量化。

• DOI: 10.3390/pharmaceutics15010160
• 发表时间: 2023-01-03
• 期刊: Pharmaceutics
• 影响因子: 5.4
• 作者: Borojeni AAT;Gu W;Asgharian B;Price O;Kuprat AP;Singh RK;Colby S;Corley RA;Darquenne C
• 通讯作者: Darquenne C