Building the Digital Twin and Virtual Clinical Trials
Maintenance of Immunological Memory
Optimizing Therapeutic Administration
Machine Learning + Mechanistic Modeling
Sampling and Calibrating Complex Models
Modeling whole-host tuberculosis response
As the major current effort of my thesis work, I am building a whole-host model of Mycobacterium tuberculosis infection. As a first step in this effort, we have developed a lungs-only model of infection which tracks the formation, dissemination, clustering, and sterilization of multiple granulomas across time. Each granuloma is governed by a series of ordinary differential equations and both single granuloma and whole-lung outcomes are calibrated against non-human primate experimental data.
Response to H56 vaccine in monkeys and humans
We integrated non-human primate (NHP) and human clinical trial data with mathematical modeling approaches to improve our understanding of NHP and human response to the TB vaccine, H56. We use a mathematical model to describe T-cell priming, proliferation, and differentiation in lymph nodes and blood, and calibrate the model to NHP and human blood data. Using the model, we demonstrate the impact of BCG timing on H56 vaccination response.
Limited T cell exhaustion in TB granulomas
Recent studies have shown a surprisingly low quantity of cytokine-producing T cells in NHP granulomas. One hypothesis of limited function is T cell exhaustion. In this work — a truly collaborative effort between two labs (experimental and computational) — we calibrate and inform an agent-based model of granuloma formation. Together, the results of the modeling and the experimental work suggest that T cell exhaustion alone is not responsible for the low quantity of M. tuberculosis-responsive T cells observed within TB granulomas and that the lack of exhaustion is likely an intrinsic property of granuloma structure.
A dynamic balance of pro- and anti- inflammatory molecules
We provide evidence from both experimental and mathematical & computational studies to support the concept of a dynamic balance operating during chronic infection scenarios. We focus mainly on tuberculosis, but also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host‐directed therapies.
Modeling retinal rod coupling
During my research experience for undergraduates (REU) at the University of Michigan Mathematics Department with Dr. Daniel Forger and Dr. Adam Stinchcombe, I developed a mathematical model to represent a rod photoreceptor population, compare model frameworks, and draw conclusions about gap junction coupling on eyesight.
Representing a road network using graph theory
Performed between my freshman and sophomore years of college, this work, led by Dr. Debra Czarneski as part of the Bryan Summer Research experience at Simpson College, opened the world of research to me and was published in an undergraduate journal. Briefly, we used simple graph theory techniques to identify weak points in connectivity across a small road network.