- Cancer is currently the second leading cause of death in the United States and the sixth leading cause of death worldwide. Due to cancer’s variability in type, location, growth rates, and patient physiology, treatment models are based off of previous experimental and clinical work. This variability, however, can lead to inconsistencies in the efficacy of a certain cancer treatments. The project objective was then to develop an overarching model that can be highly tuned to a patient’s individual physiology and cancer type. It was derived from basic pharmacokinetic principles and mass transfer, and tied together using process dynamics to relate a treatment input to a cancer reduction output. The model was simulated using current clinical treatment standards for a common cancer (Non-Small-Cell Lung Carcinoma), and was further optimized against chemotherapy dosing frequency and dosage amount to obtain a more efficient dosing schedule.
- Key Words: Cancer, Pharmacokinetics, Model, Process Dynamics, Optimization