Author ORCID Identifier
https://orcid.org/0000-0002-7678-6527
Defense Date
2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Systems Modeling and Analysis
First Advisor
Dr. Rebecca Segal
Abstract
In the last 50 years, pain in Sickle Cell Disease (SCD) has become more widely studied thanks to advancements in technology and awareness. Clinical studies, population surveys, pharmaceutical trials, and computational models have been created and conducted to elucidate the mechanisms, treatments, and prediction of Sickle Cell disease pain episodes. Computational models have become quite useful in unraveling disease pathology with the rise in data collection accessibility and advanced computational power. In particular, dynamic mathematical models have been used to investigate Sickle Cell disease pathology and treatment. In this work we conduct a literature review of mathematical models used in SCD research and present two modeling approaches for understanding pain behavior and treatment in SCD - one behavioral approach and one biological approach.
The third chapter examines and elaborates on the connection between sleep quality and pain in SCD using a differential equations (ODE) model. The ODE model uses patient mobile health (mHealth) data to compute a simulated pain profile that is compared to raw patient data for predictive value and analysis. The results show that the sleep - pain relationship becomes more significant with increasing incidence of pain, which is correlated with patient age, supporting the theory that SCD's progression into a chronic pain state occurs in adolescence.
The fourth chapter switches from a behavioral model of pain in SCD to a biological model to investigate the underlying mechanisms of the painful vaso-occlusive crises - the hallmark occurrence of SCD and cause of the recurrent pain episodes. The recurrence of vaso-occlusive crisis has been revealed to be exacerbated by the chronic inflammatory processes associated with SCD pathophysiology so we have formulated an ODE model of the temporal dynamics of inflammation and adhesion in Sickle Cell disease. The ODE model uses hematological blood data to estimate cell concentrations and their impact on the likelihood of secondary VOC (sVOC). Model formulation allows for the investigation of potential mechanistic pathways to treat or prevent VOC duration and frequency. Our results identify key parameters in the VOC process and provide some mechanistic explanation for the changes in patient state during crisis.
Through these models, we highlight the power of mathematical biology to change the lives of patients in medicine, through little to no cost to the patient or family. As more data is collected and becomes available, models like these can be used to investigate these complex processes more thoroughly with minimal cost and injury to patients.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
5-9-2024