The COVID-19 treatment trials that ‘learn as they go’

Thursday, 23 April 2020

In the event of an outbreak of an infectious disease, such as the current COVID-19 pandemic, we often know very little, yet are required to act very fast. In this article, Dr Robert Mahar and Dr David Price from the Centre for Epidemiology and Biostatistics, along with A/Prof Steven Tong from the Doherty Institute for Infection and Immunity, explain how innovative approaches to clinical trials for COVID-19 treatments can enable us to quickly hone in on the most promising treatments, saving time and potentially saving lives.

Read the full original article.

Dr David Price

Dr David Price

Post-doctoral Biostatistician
Centre for Epidemiology and Biostatistics
Melbourne School of Population and Global Health, The University of Melbourne

David received his PhD from the University of Adelaide in 2015. His main research interest is on the model-based, information-theoretic approach to optimal design of experiments, with a particular focus on models of infectious diseases. He is also working on developing models of within-host bacterial infection dynamics, inference methods suited to these systems, and developing an R package to implement these tools. David is also providing collaborative statistical support and training to researchers at the Doherty Institute.

Robert Mahar

Dr Robert Mahar

Post-doctoral Biostatistician

Robert Mahar received a PhD in Biostatistics at the University of Melbourne in 2019, following completion of a Master of Biostatistics at the University of Queensland in 2014. He is a statistician with a research focus on applied causal inference and epidemiology, Bayesian methods, and novel clinical trial design, with a particular emphasis on applications in cancer.