Improving the evidence on safety and efficacy for medication use in pregnancy
Annual Adrian Root Lecture with Professor Deborah Lawlor
Join Professor Deborah Lawlor in honouring the life and passion for electronic health record data research of our much missed colleague Adrian Root.
We are delighted to welcome Professor Deborah Lawlor, CBE, FMedSci, to deliver this year’s LSHTM Annual Adrian Root Lecture, titled ‘Improving the evidence on safety and efficacy for medication use in pregnancy’. Professor Lawlor is internationally recognised for her work on perinatal and women’s health, causal inference, and the use of large-scale data to answer pressing clinical and public health questions.
There is understandable reluctance to undertake randomized controlled trials in pregnant women. This means that women and clinicians often do not know what to do when a woman starts pregnancy on existing medication for conditions such as autoimmune diseases, mental health conditions and epilepsy which are common in women of reproductive age. It also means that developing new medications that could prevent or treat adverse pregnancy and perinatal health is rare.
Professor Deborah Lawlor will argue that we must make best use of observational data and epidemiological methods that do not require experimenting on pregnant women.
Attendees will gain insight into how triangulating evidence from different study designs that each have different key sources of bias can be used to identify causal effects, and to the continually increasing international large data sources that could support triangulation to improve evidence on the safety of and efficacy of medications in pregnancy.
Speaker
Professor Deborah Lawlor
Professor Debbie A. Lawlor is Professor of Epidemiology, MRC Investigator and BHF Chair at the Bristol Medical School (Population Health Sciences), University of Bristol, and leads work in the MRC Integrative Epidemiology. Her research spans life course, reproductive, perinatal and cardio metabolic epidemiology, leveraging genetic, environmental and social data to understand disease causation and prevention. In 2024 she was awarded the Richard Doll Prize in Epidemiology by the International Epidemiological Association.
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