Medical Applications and Epidemiology

Using mathematics to fight cancer

Speaker: 
Ami Radunskaya
Date: 
Mon, Aug 13, 2018
Location: 
PIMS, University of British Columbia
Conference: 
Diversity in Mathematics
Abstract: 

What can mathematics tell us about the treatment of cancer? In this talk I will present some of work that I have done in the modeling of tumor growth and treatment over the last fifteen years.

Cancer is a myriad of individual diseases, with the common feature that an individual's own cells have become malignant. Thus, the treatment of cancer poses great challenges, since an attack must be mounted against cells that are nearly identical to normal cells. Mathematical models that describe tumor growth in tissue, the immune response, and the administration of different therapies can suggest treatment strategies that optimize treatment efficacy and minimize negative side-effects.

However, the inherent complexity of the immune system and the spatial heterogeneity of human tissue gives rise to mathematical models that pose unique challenges for the mathematician. In this talk I will give a few examples of how doctors, immunologists, and mathematicians can work together to understand the development of the disease and to design effective treatments.

This talk is part of the PIMS Diversity in Mathematics Summer School and is intended for a general audience: no knowledge of biology or advanced mathematics will be assumed.

Biography

A California native, Professor Radunskaya received her Ph.D. in Mathematics from Stanford University. She has been a faculty member in the Math Department Pomona College since 1994.

In her research, she specializes in ergodic theory, dynamical systems, and applications to various "real-world" problems. Some current research projects involve mathematical models of cancer immunotherapy, developing strategies for targeted drug delivery to the brain, and studying stochastic perturbations of dynamical systems.

Prior to her academic career, Professor Radunskaya worked extensively as a cellist and composer. Her music, described as "techno-clectic", combines traditional forms with improvisation, acoustic sounds with electronic, computer-generated, and found sounds, and abstract structures with narrative visual and sonic elements.

Contrary to popular belief, Professor Radunskaya thinks that anyone can succeed in mathematics, and she has committed herself to increasing the participation of women and underrepresented groups in the mathematical sciences.

She is currently the President of the Association for Women in Mathematics, and co-directs the EDGE (Enhancing Diversity in Graduate Education) program, which won a "Mathematics Program that Makes a Difference" award from the American Mathematics Society in 2007, and a Presidential Award for Excellence in Science, Mathematics and Engineering Mentoring (PAESMEM) in 2015.

Professor Radunskaya was recently been elected as a Fellow of the American Math Society, and she is the recipient of several awards, including a WIG teaching award in 2012, and the 2017 AAAS Mentor award.

Managing Patients with Chronic Conditions

Speaker: 
Mariel Lavieri
Date: 
Thu, Feb 23, 2017
Location: 
University of Calgary, Downtown Campus
Conference: 
Lunchbox Lecture Series
Abstract: 
Chronic disease management often involves sequential decisions that have long-term implications. Those decisions are based on high dimensional information, which pose a problem for traditional modeling paradigms. In some key instances, the disease dynamics might not be known, but instead are learned as new information becomes available. As a first step, we will describe some of the ongoing research modeling medical decisions of patients with chronic conditions. Key to the models developed is the incorporation of the individual patient's disease dynamics into the parameterization of the models of the disease state evolution. Model conception and validation is described, as well as the role of multidisciplinary collaborations in ensuring practical impact of this work.

Virtual Lung Project at UNC: What's Math Got To Do With It?

Speaker: 
Gregory Forest
Date: 
Fri, Mar 18, 2011
Location: 
PIMS, University of British Columbia
Abstract: 
A group of scientists at the University of North Carolina, from theorists to clinicians, have coalesced over the past decade on an effort called the Virtual Lung Project. There is a parallel VLP at the Pacific Northwest Laboratory, focused on environmental health, but I will focus on our effort. We come from mathematics, chemistry, computer science, physics, lung biology, biophysics and medicine. The goal is to engineer lung health through combined experimental-theoretical-computational tools to measure, assess, and predict lung function and dysfunction. Now one might ask, with all due respect to Tina Turner: what's math got to do with it? My lecture is devoted to many responses, including some progress yet more open problems.

Modeling the Dynamics of Infectious Diseases

Author: 
Bryan Grenfell
Date: 
Mon, Sep 1, 2003
Location: 
University of Alberta, Edmonton, Canada
Conference: 
PIMS Distinguished Chair Lectures
Abstract: 
Infectious diseases continue to have a major impact on individuals, populations, and the economy, even though some of them have been eradicated (e.g. small pox). Unlike many other ecological systems, many infectious diseases are well documented by spatio-temporal data sets of occurrence and impact. In addition, in particular for childhood diseases, the dynamics of the disease in a single individual are fairly well understood and fairly simple. As such, infectious diseases are a great field for mathematical modeling, and for connecting these models to data. In this article, we concentrate on three issues, namely (1) comparative childhood disease dynamics and vaccination, (2) spatio-temporal disease dynamics, and (3) evolution in diseases with multiple strains. The mathematical techniques used in the analysis of disease models contain bifurcation theory for ODEs, wavelet analysis, stochastic simulations and various forms of data fitting.
Notes: 
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