In this presentation Dr Brodie Lawson will share how population data is invaluable for understanding variability within and between populations, and importantly, its consequences.
For example, subtle differences in the physiology of individual members of a population can result in medical treatments with an inconsistent effect, and we must understand this in order to develop new drugs or targeted treatment plans. Statistics has a rich history of connecting variable traits to measurements of interest in a meaningful and justifiable manner, say, discovering the impacts of age, health status or medical history. What is less established, however, is how to deal with traits that have not or even cannot be measured ー how does an individual’s relative level of, let’s say, hERG gene expression affect our hypothetical drug treatment?
Armed with some good knowledge of the system of interest, mathematics and computer simulation can provide the answer. Calibrating such simulations to data is its own very well-established topic, but when this data is population data, things become a bit more complicated. We no longer seek some estimate of a bunch of parameters, but instead a description of how these parameters are spread across the population, or at least a sample. This talk demonstrates the key ideas of population calibration, the statistics that underlie it, and the benefits we can get from doing it right.
About the presenter
Dr Brodie Lawson obtained his PhD in applied mathematics, creating computer simulations of cell proliferation and migration. The greatest majority of his postdoctoral career has been associated with ACEMS one way or another, where he has brought together ideas from computational mathematics, Bayesian statistics, computer graphics and manifold geometry in order to better understand the enduring research problem of signalling dysfunction in the heart. He works with the Centre of Data Science as a research postdoc, also serving as an associate investigator for the ARC Centre of Excellence for Mathematical and Statistical Frontiers. His collaborations extend from the United Kingdom (Oxford University), through to Brazil and the Czech Republic. His research into creating virtual populations of heart cells that properly reflect experimental data, along with Centre member Prof. Christopher Drovandi, was published in the #3 ranked interdisciplinary journal worldwide, Science Advances.
|Start Date:||08/04/2021 [add to calendar]|
|Start Time:||2pm (AEST)|
|End Time:||3pm (AEST)|