Meghan C. Ferrall-Fairbanks, Ph.D.
Assistant Professor, Biomedical Engineering
Researchers have recognized that a one-size-fits-all approach is not effective at treating cancer and that tumor heterogeneity plays an important role in patient response. Tumor heterogeneity can result from a variety of different viewpoints within a tumor including genetics, epigenetics, transcriptomics, and proteomics. Furthermore, we have a limited ability to stratify patients into high versus low-risk groups based on these different types of heterogeneity. To address this, we explore ways to quantifying tumor heterogeneity, or diversity, and how that diversity changes over time in an evolving tumor population using mathematical modeling. Mathematical models of prostate cancer population dynamics have been proven to be successful at delaying disease progression and we are leveraging similar tools to apply to ovarian cancer, where 1 in 6 women diagnosed with ovarian cancer die within 3 months of learning they have the disease. The goal of our research is to understand the evolution of resistance to treatment and engineer better strategies to better control ovarian cancer growth.
Meghan Ferrall-Fairbanks, Ph.D., is a biomedical engineer at the University of Florida. Her research focuses on leveraging mathematics, systems biology, and tumor ecology to optimize cancer treatment.
Core Standards
MA.912.F.1
Understand, compare and analyze properties of functions
MA.912.F.2
Identify and describe the effects of transformations on functions. Create new functions given transformations
MA.912.DP.5
Determine methods of data collection and make inferences from collected data
MA.912.C.2
Develop an understanding for and determine derivatives
MA.912.C.3
Apply derivatives to solve problems
SC.912.L15
Diversity and Evolution of Living Organisms
SC.912.CS-CS.1
Modeling and simulations
SC.912.CS-CP.1
Data analysis
SC.912.L.16.8
Explain the relationship between mutation, cell cycle, and uncontrolled cell growth potentially resulting in cancer.