Modeling and quantitative analysis to understand evolution, prognosis, and drug delivery in complex diseases

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dc.contributor.advisorCristini, Vittorio
dc.contributor.advisorKono, Junichiro
dc.creatorPeláez Soní, María José
dc.date.accessioned2024-01-25T15:32:47Z
dc.date.available2024-01-25T15:32:47Z
dc.date.created2023-12
dc.date.issued2023-11-27
dc.date.submittedDecember 2023
dc.date.updated2024-01-25T15:32:47Z
dc.descriptionEMBARGO NOTE: This item is embargoed until 2025-12-01
dc.description.abstractModeling and quantitative analysis stand as indispensable tools in medicine, offering invaluable insights, predictive capabilities, and actionable solutions to address a myriad of healthcare challenges. Their instrumental role in advancing our understanding of disease dynamics has paved the way for enhanced diagnosis, prognosis, and treatment capabilities. This dissertation showcases the pivotal role of modeling methods and quantitative analysis in medicine, presented through three distinct applications that span over advanced drug delivery systems, cancer prognosis and the evolution of chemoresistance. In the first part of this work, a comprehensive mathematical model of transdermal drug delivery via microneedle-based patches, integrated with a pharmacokinetics model, is introduced. Model-based simulations were conducted to pinpoint the key parameters governing systemic delivery, enabling the optimization of patch designs to improve drug pharmacokinetics. In the second part, survival analysis is employed to identify biomechanical and immune biomarkers, enabling the prospective prediction of tumor aggressiveness, invasiveness, treatment outcomes, and survival probability in breast cancer. Lastly, a novel hypothesis is presented, proposing that water exclusion zones within cells may act as insulation barriers, safeguarding the delicate quantum nature of specific biochemical reactions against environmental influences. This hypothesis gains additional support through a review regarding the role that interfacial water plays in several biological processes and a proof of concept example to illustrate the application of quantum mechanics models for understanding the evolution of chemoresistance. Through these multifaceted investigations, this dissertation underscores the vital role that modeling and quantitative analysis plays in investigating the complexities of diseases, promising new horizons in medicine.
dc.embargo.lift2025-12-01
dc.embargo.terms2025-12-01
dc.format.mimetypeapplication/pdf
dc.identifier.citationPeláez Soní, María José . "Modeling and quantitative analysis to understand evolution, prognosis, and drug delivery in complex diseases." (2023). PhD diss., Rice University. https://hdl.handle.net/1911/115426
dc.identifier.urihttps://hdl.handle.net/1911/115426
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.subjectMathematical modeling, quantitative analysis, dissolution, biomarker, entanglement, superposition, coherence
dc.titleModeling and quantitative analysis to understand evolution, prognosis, and drug delivery in complex diseases
dc.typeThesis
dc.type.materialText
thesis.degree.departmentApplied Physics
thesis.degree.disciplineApplied Physics
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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