Research Projects

This project aims to incorporate computational blood flow modeling with experimental research on magnetic particle dynamics, transport, and rheology to develop a magnetically guided drug delivery system for cancer and hyperthermia treatments. To improve targeted delivery, lower toxicity, and enable precision tools for minimally invasive applications, microfluidic technologies provide insight into how particle dynamics such as aggregation and deposition take place in biological systems, which may result in unfavorable outcomes or treatment failure. The core areas of research of this project include: 1. Experimental Study of Magnetic Particle Dynamics: The motion of drug-coated magnetic particles at the micron and nanoscale will be monitored under both steady and oscillating magnetic fields using a specially designed setup integrated with magnetic coils. To ensure precise control over particle trajectories, parameters like field strength, frequency, and particle characteristics (size, shape, and magnetization) will be optimized. 2. Advanced Image Processing and High-Speed Imaging for Particle Tracking: To precisely measure critical parameters, such as rotational speed, linear displacement, and aggregation behavior of the drug-coated magnetic particles, and to record time-resolved trajectories under high-frequency oscillating magnetic fields, mimicking vascular flow and targeted drug delivery applications. 3. Rheology and Characterization of Drug-Coated Particles: Anticancer drug-coated synthetic magnetic particles will be characterized by means of SEM, TEM, XRD, VSM, and rheometry. The flowability and responsiveness of particle suspensions under magnetic fields will be investigated in order to comprehend their rheological behavior, which is crucial for effective delivery through blood vessels. 4. Analysis Under Pathological Conditions: To conduct experimental and computational studies under realistic pathological conditions, clinical data and literature will be reviewed. To ensure accuracy, hemodynamic models that include cardiovascular disease factors will be developed for subjects of various ages, both male and female. 5. Computational Hemodynamic Modeling: CFD-based simulations are used to simulate real-time particle navigation as blood flows through a healthy and stenosed arterial geometry, including a tumor-afflicted area. The model will optimize delivery protocols for specific patient scenarios by taking into account the blood viscosity, elasticity of the artery wall, vessel diameter, and external magnetic sources. 6. AI and Machine Learning (AI/ML): To create predictive tools and resolve inverse issues by combining AI/ML with clinical data, and validations of the results will allow precise experiments and simulations of intricate biomedical processes. The ultimate objective is to use minimally invasive targeted drug localization to widen the door to safer, customized, and more effective therapies.