My research uses mathematical models and computer simulations to understand and predict the behaviour of biological systems. I am particularly interested in studying disease processes and potential therapies or cures. The experiments and clinical trials used to study many diseases are very costly and time-consuming and the data we get are usually quite limited, so it's often difficult to get a clear picture of which biological processes are important in causing a disease. This also makes it difficult to study different treatment regimens. By the time a drug makes it to a clinical trial, usually only a couple of different dose/timing regimens are tested in humans; not because they were found to be the optimal regimens after a thorough examination of all the possibilities, but typically based on the educated guess of the researchers heading the trial. An accurate computer model of the disease can not only help us understand the underlying dynamics of the disease but will be extremely helpful in assessing potential treatments. Computers can simulate thousands of different dose/timing regimens and will help doctors choose optimal regimens to test in patients.
Influenza is a viral infection that affects millions of people every
year. Most often, the illness is not serious and resolves on its own,
but it has the potential to cause widespread illness and death during a
pandemic. I use mathematical models of the infection process to study
the causes of severe influenza, the emergence of drug resistance, the
role of the immune response in clearing the infection, and antiviral
treatment. The long-term goal of this research is to develop an
accurate model of the infection in humans which can then be used to
test a wide variety of drug treatment protocols and to simulate drug or
vaccine treatment in high risk patients, reducing the risk to these
In a healthy heart an electrical pulse from the sino-atrial node causes a single electrical wave to propagate uniformly across the heart. This wave initiates the contraction that pumps the blood through your body. In a heart experiencing an arrhythmia, the electrical pulse generates waves that spread non-uniformly or break up into multiple waves. This causes different parts of the heart to contract at different times making it difficult for the heart to pump blood efficiently. I use mathematical models to try to understand how a heart becomes arrhythmic so that we can predict which patients should be given medication to prevent arrhythmias. I also use models to assess the effect of different anti-arrhythmic drugs on electrical activity in the heart.