Data-Driven Modeling of Lung Deposition of Aerosol Medication Delivered by Metered Dose Inhalers

Simple item page
dc.contributor.advisorSabharwal, Ashutosh
dc.contributor.committeeMemberGrande-Allen, Jane
dc.creatorBiswas, Rajoshi
dc.date.accessioned2019-05-17T15:43:05Z
dc.date.available2019-08-01T05:01:08Z
dc.date.created2018-08
dc.date.issued2018-07-12
dc.date.submittedAugust 2018
dc.date.updated2019-05-17T15:43:05Z
dc.description.abstractChronic pulmonary diseases such as Asthma and COPD (Chronic Obstructive Pulmonary Disease) affect over 510 million worldwide. The most common form of treatment for the management of the diseases is a Metered Dose Inhaler (MDI). Numerous large-scale studies have demonstrated that 70-90% of patients misuse their MDIs leading to wasted medication and poor health outcomes. Due to the nature of inhaled therapy and delayed impact of MDI misuse on health outcomes, patients are unaware of their MDI use technique as well as the resulting lung deposition. In this thesis, I have developed and validated a predictive model of lung deposition corresponding to any MDI technique in three phases. Phase I: I conducted the first pilot study that quantitatively measured MDI technique from 23 physician-diagnosed asthma and COPD adult patients in an outpatient clinic setting. Our results showed that all patients made at least one technique error and 74% made at least three; our quantitative method of measurement recorded 60% more errors than the current gold standard method (using observation alone). Further, I derived an MDI technique model using a parameterized model with a trapezoidal approximation to inspiration curves and includes actuation timing and instantaneous flow-based parameterization. Phase II: To derive lung deposition for any MDI technique (ground truth estimation), I constructed and validated the first in vitro experimental testbed designed to emulate both inspiration and actuation mechanisms of any MDI use in a lab setting. Using this testbed, I determined the significance of inspiration and actuation parameters on in vitro lung deposition of aerosols delivered by Ventolin MDIs. Our results demonstrated that actuation parameters affected lung deposition more significantly (23% difference in lung deposition) than inspiratory flow parameters (<5%). Phase III: With a training dataset of MDI techniques and corresponding in vitro lung deposition, I determined that the model specification for a linear mixed effects model of lung deposition of aerosol from Ventolin MDIs was a function of quadratic inspiration and actuation parameters. I validated the model against in vitro lung deposition measured for the MDI techniques (non-trapezoidal) recorded from patients and had a testing RMSE of 2.3% lung deposition. Hence, we demonstrated the methodology and validation for developing a data-driven model of lung deposition of aerosol medication delivered by any MDI, based on patient representative inhaler use techniques.
dc.embargo.terms2019-08-01
dc.format.mimetypeapplication/pdf
dc.identifier.citationBiswas, Rajoshi. "Data-Driven Modeling of Lung Deposition of Aerosol Medication Delivered by Metered Dose Inhalers." (2018) Diss., Rice University. <a href="https://hdl.handle.net/1911/105804">https://hdl.handle.net/1911/105804</a>.
dc.identifier.urihttps://hdl.handle.net/1911/105804
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectAsthma
dc.subjectCOPD
dc.subjectMetered Dose Inhaler
dc.subjectModeling
dc.subjectAerosol
dc.subjectLinear Mixed Effects Model
dc.subjectInhaler technique
dc.subjectLung deposition
dc.titleData-Driven Modeling of Lung Deposition of Aerosol Medication Delivered by Metered Dose Inhalers
dc.typeThesis
dc.type.materialText
thesis.degree.departmentElectrical and Computer Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
BISWAS-DOCUMENT-2018.pdf
Size:
23.36 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
PROQUEST_LICENSE.txt
Size:
5.84 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
LICENSE.txt
Size:
2.61 KB
Format:
Plain Text
Description:
Download
Collections
Rice University Electronic Theses and Dissertations