| The course runs from 20 to 24 October 2025. |
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. However, observational studies using RWD are vulnerable to many potential sources of bias. 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.
This intensive, online short course addresses the growing demand for professionals trained in developing and critiquing RWE. The diverse backgrounds and expertise of our lecturers ensure a strong balance of theoretical insight and practical applications.
The aim of this course is to equip students with the understanding and techniques to generate high-quality RWE on the safety and effectiveness of medicines , while addressing common sources of error in studies using RWD.
During this course, students will:
- Develop their understanding of concepts, study designs, and methods in pharmacoepidemiology.
- Apply statistical techniques to generate RWE using electronic health record data.
- Identify and address biases and other sources of error that can occur in studies using RWD.
What topics are covered?
- Overview of study designs, including self-controlled designs.
- The practicalities of planning a study, including reproducible codelist building.
- Measurements in pharmacoepidemiology - including outcomes, exposures, confounders, and issues of validation.
- Sources of RWD around the world and the concept of fit-for-purpose data.
- Introduction to data-enabled trials.
- Sources of error in pharmacoepidemiological studies, including methods for dealing with bias and confounding, with a particular focus on confounding by indication.
- Causal inference and regression model building.
- Propensity scores, including high-dimensional propensity scores.
- Quantitative bias analysis.
- Dealing with missing data.
- Open science, reproducibility, and trusted research environments.
- Tools for distributed network pharmacoepidemiological studies.
- Critical appraisal of published studies.
- Emerging topics, including:
- Target trial emulation framework.
- Pharmacoepidemiology in the digital era.
- Pharmacoequity.
- Confounding specific to vaccine RWE.
Course delivery
All teaching will be delivered online and consists of:
- Self-study materials (e.g., pre-recorded lectures).
- Synchronous live sessions (e.g., Q&A, group discussions, computer-based practical sessions).
Computer-based practical sessions will use Stata software. Prior experience of Stata is not required; however, some statistical programming experience is strongly encouraged.
The course is tentatively set to run 9:30-16:30 UK time daily, with morning and afternoon sessions spread over five days. This includes time to work through the self-study materials. Synchronous live sessions provide students the opportunity to apply and discuss concepts introduced in the self-study materials.
While attending all live sessions is not mandatory, students who attend will get the most out of the course. Most lectures are pre-recorded and made available on the course website one week prior to each block. Live sessions (except for practicals) will be recorded and made available to students within 24 hours. Practicals will not be recorded; however, solution sets to all practicals are made available immediately following each practical to allow students to work through the materials asynchronously. Students can access an online forum on the course website to post questions about any of the course materials to the course tutors during the course.
Teaching faculty
This course is developed and delivered by a diverse team of world-leading researchers and educators at LSHTM, a global centre of excellence in public health, epidemiology, and health data science. A key feature of this course is its co-development with the Clinical Practice Research Database (CPRD) Research Team at the UK’s Medicines and Healthcare products Regulatory Agency (MHRA). Students will also benefit from the insights of senior guest lecturers working at the forefront of pharmacoepidemiology and real-world evidence at academic and non-academic institutions around the world. These diverse perspectives ensure the course content is scientifically rigorous and relevant to real-world practice.
Assessment
There is no formal assessment. However, students who attend a majority of the live sessions and engage with the self-study materials may request a Certificate of Attendance.
Additional information
£1,630 full fee
£1,000 for students or charity status
£570 for residents of LMICs (eligible countries)
When applying for discounted fees, please include proof of student or LMIC status instead of your CV. LMIC status can be confirmed with a passport and proof of current residence. Charity status refers to individuals who are currently affiliated with a charity.
This course is ideal for professionals concerned with the safe and effective use of medicines, especially those working in:
- The pharmaceutical industry (e.g., drug development, licensing, surveillance).
- Regulatory authorities (e.g., medicines licensing, monitoring).
- Academic and research settings (e.g., drug effectiveness and safety evaluation).
- Health services (e.g., drug policy, decision-making).
Prerequisites for this course include:
- A second-class honours degree from the UK (or international equivalent) in a science, medical, statistical, or related subject.
- Some post-graduate experience in pharmacoepidemiology or a related field.
- A grounding in epidemiological methods and/or prior knowledge of pharmacoepidemiology (e.g., completion or related experience with materials covered in Block 3 of the Professional Certificate in Pharmacoepidemiology & Pharmacovigilance).
The course includes computer practicals conducted in Stata. Prior experience of Stata is not required; however, some statistical programming experience is strongly encouraged.
Applicants should have a good command of English.
Up to 50 participants will be accepted.
Applications for 2025 are now open and can be made via our online application form.
In your application, please:
- Describe your prior knowledge of or experience with epidemiological concepts (e.g., bias, confounding).
- Describe any experience with statistical programming (e.g., R, Stata, SAS).
- Explain your motivation for taking this course and how it fits into your professional development.
The application deadline is Wednesday 29 September 2025, 23:59 UK time. We strongly advise that you apply early as courses may close earlier than the stated deadline if they become full.
Please read LSHTM's Admissions policies prior to submitting your application.
LSHTM may cancel courses two weeks before the first day of the course if numbers prove insufficient. In those circumstances, course fees will be refunded.