Integrated Mathematical Oncology Faculty
Alexander RA Anderson, PhD - Interm Major Director
The Anderson Lab is focused on integrating mathematical and computational modeling approaches with experimental and clinical data to better understand cancer growth and development and translate this understanding into novel therapies.
Noemi Andor, PhD
We develop and integrate algorithms to quantify the clonal composition of a tumor from different perspectives, including its genome, transcriptome or morphology. The goal is using these clone characteristics to inform how a tumor’s environment can be altered to favor certain tumor subclones over others. A first instance of this translates into testing the potential of a clone’s genomic instability as biomarker of its sensitivity to DNA damaging drugs.
Renee Brady-Nicholls, PhD
My research is primarily focused on improving patient care using accessible, minimally-invasive biomarkers through the integration of mathematical modeling, with a special interest in improving outcomes for underrepresented minorities. To accomplish this, we develop predictive mathematical models of these biomarker dynamics to propose patient-tailored treatment strategies that maximize patient response and quality of life.
David Basanta Gutierrez, PhD
To understand the evolutionary dynamics of cancer using integrative approaches so that one day we will be able to exert some control on cancer progression. My work will focus on mathematical and computational models of cancer evolution.
Joel Brown, PhD
We apply theoretical evolutionary biology models, together with computational, bioinformatics and statistical approaches to cancer cell biology. I use a combination of mathematical and experimental approaches to understand how organisms interact with and shape their environments.
Kasia Rejniak, PhD
My lab's research is focused on understanding how the heterogeneous and dynamically changing tumor microenvironment can be harnessed to design more effective treatment protocols. In close collaboration with experimentalists and clinicians, we develop mathematical models of in silico organoids and micro-pharmacology based on tumor-specific histology and quantitative image analyses to predict tumor response to combined (chemo-, immuno- and targeted) therapies and to optimize their schedules.
Jeffrey West, PhD
The goal of my research group is to aid in targeting treatment resistance by constructing mathematical models of 1) tumor evolution and heterogeneity and 2) evolutionary-minded treatment strategies, employing techniques such as agent-based modeling, dose-response convexity analysis (second-order effects), and evolutionary game theory. These methods are broadly applicable to many cancer types, but recent publications have focused on applications to breast and prostate cancer.
Integrated Mathematical Oncology PhD