There is unprecedented interest in estimating the safety and effectiveness of medicines. The widespread and near-real-time availability of real-world data (RWD) offers opportunities to quickly generate real-world evidence (RWE) to address these needs. Observational studies are vulnerable to many potential biases and translating RWD into high-quality RWE requires careful consideration of the scientific process including identification of fit-for-purpose data and selection of the most appropriate design, measurement, and analysis methods to mitigate potential biases.
The aim of this course is to equip students with the understanding and techniques to generate RWE on safety and effectiveness of medicines and overcome common sources of error, with practical applications using electronic health record data.
During this online course, students will:
- Develop their knowledge of concepts, study designs, and methods in pharmacoepidemiology
- Apply statistical techniques to generate real-world evidence using electronic health record data from the Clinical Practice Research Datalink in Stata (prior experience of Stata not required)
- Understand biases and other sources of error that can occur in studies using real-world data, and identify and apply strategies to avoid them
Who should apply?
Individuals concerned with the safe and effective use of medicines should apply, especially those working in:
- The pharmaceutical industry who are involved in drug development, licensing, or surveillance
- Regulatory bodies who are involved in licensing & surveillance
- Academics interested in evaluating drug safety and effectiveness
- The health service who are involved in drug policy and decision making
The course is designed for individuals with a grounding in epidemiological methods and concepts and/or some prior knowledge of pharmacoepidemiology, especially those who have completed the Certificate in Pharmacoepidemiology & Pharmacovigilance.
Applicants will normally have a science, biomedical or biostatistical background, hold a second class honours degree of a United Kingdom university (or equivalent) in a science, medical, statistical or related subject and will have some post-graduate experience in the area of pharamacoepidemiology, including an understanding of methodological concepts such as bias and confounding. It is not expected that applicants will actually be conducting pharmacoepidemiology studies. Applicants should have a good command of English.
Up to 30 participants will be accepted.
Advice for EU nationals
Students from the EU are very welcome at LSHTM and we would strongly encourage applications from EU nationals to this course.
What topics will you cover?
- Overview of study designs for pharmacoepidemiology
- The practicalities of planning a study, including study design, feasibility counts, power calculations, and study size
- Measurements in pharmacoepidemiology - including outcomes, exposures, confounders, and issues of validation
- Sources of RWD for pharmacoepidemiology and importance of identification of fit-for-purpose data
- Sources of error in pharmacoepidemiological studies, including methods for dealing with bias and confounding, with a particular focus on confounding by indication
- Thinking through causal relationships and regression model building
- Dealing with missing data
- Propensity scores, including high-dimensional propensity scores
- Pharmacoepidemiology in the digital era
- Critical appraisal of published pharmacoepidemiological studies
- Overview of new methods and insights within pharmacoepidemiological research, including:
- Pragmatic trials and trial replication
All teaching will be delivered online and consists of self-study material using a combination of pre-recorded lectures with synchronous interactive live sessions, including Q&A and panel discussions (based on pre-recorded content) and computer-based practical sessions. Computer-based practical sessions will use Stata software (prior experience of Stata not required). Participants will be sent a link to access the course material before the course begins.
The course is tentatively set to run 9:30-16:30 GMT daily, which includes time to watch pre-recorded content. Live sessions (e.g., Q&A, panels, computer practicals) are tentatively set to run daily between 10:30-12:45 GMT and 14:15-16:30 GMT, with a break from 12:45-14:15 GMT. All times are estimates and subject to change. Live Q&A and panel sessions will be recorded and made available to students. Computer practicals will not be recorded.
There is no formal assessment but a Certificate of Attendance will be provided at the conclusion of the course.
Professor Krishnan Bhaskaran (LSHTM)
Professor Ian Douglas (LSHTM)
Dr. Harriet Forbes (Bristol)
Dr. James Galloway (King’s College London)
Dr. John Gregson (LSHTM)
Dr. Susana Perez Gutthann (RTI Health Solutions)
Dr. Christopher Rentsch (LSHTM/Yale)
Professor Liam Smeeth (LSHTM)
Professor Tjeerd van Staa (University of Manchester)
Dr. Helen Strongman (LSHTM)
Dr. John Tazare (LSHTM)
Dr. Kevin Wing (LSHTM)
Clinical Practice Research Database (CPRD) Research Team