Professor Ian Douglas

London School of Hygiene and Tropical Medicine

 Prof Douglas is an epidemiologist, currently funded by GlaxoSmithKline. He initially studied physiology and completed a PhD in Manchester. Since then, he has spent several years at the UK Medicines & Healthcare Products Regulatory Agency and in the pharmaceutical industry investigating adverse effects of drugs - both in clinical trials and post-marketing. He completed the MSc in epidemiology at LSHTM in 2005.

Prof Douglas is interested in pharmacoepidemiology, and in particular, how large primary care databases can be used to investigate the effects of drugs - both harmful and beneficial. He is exploring methodologies to minimize some of the biases inherent in the research of drug effects, and his main current areas of interest include case-only approaches to study design, the use of non-interventional data to estimate intended treatment effects, quantitative bias analysis, and the application of high dimensional propensity scores in electronic health data.

Basic Pharmacoepidemiology, Intermediate Pharmacoepidemiology; further ways to deal with confounding

Basic Pharmacoepidemiology: This course will introduce participants to the fundamentals of pharmacoepidemiology, including; Measures of disease and measures of association, key study designs in pharmacoepidemiology, bias and confounding. Each topic will be covered by a 45 minute talk, followed by a 30 minute practical where participants will be able to put into practice the concepts they are learning. It is aimed at people who are familiar with, or have an interest in the drugs industry, drug safety, drug regulation, or the study of medicine/vaccine safety. No prior expertise in epidemiology is required.

 Intermediate Pharmacoepidemiology: further ways to deal with confounding: This course will introduce participants to two methods for dealing with confounding which are frequently used in pharmacoepidemiology. First we will cover propensity scores; what they are, how they are used, the assumptions involved in using them and how they compare with other methods for dealing with confounding. Following a 1 hour talk, participants will explore the concepts we have covered in small groups. Second we will cover case only study designs and introduce the self-controlled case series and case cross-over designs to participants. We will explore both methods, their underlying assumptions, and some examples of their application. Following a 1 hour talk, participants will have an opportunity to gain practical experience in thinking through self-controlled design features in small group discussions. We will assume all participants in this course are already familiar with core concepts in epidemiology including cohort and case control designs, bias and confounding and multivariable adjustment for confounding.