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P103: A Robust Data Analysis Tool to Characterize the Safety Profile of Medicines Prescribed to Women While Pregnant or Lactating

Poster Presenter

Sahaja Korlagunta

Director, Pharmacovigilance Scientist
Bristol-Myers Squibb Company
United States

Objectives

A robust pregnancy data analysis tool is needed to enhance routine signal detection of events reported from drug exposures during pregnancy. This is crucial to characterize safety profiles to include data on pre- and post-natal outcomes, allowing evidence-based informed treatment recommendations.

Method

A custom pregnancy/lactation drug report was created to bridge the data gap that exists for this demographic. This report presents adverse events for the medicines with the timing of each exposure as it relates to important milestones during pregnancy and lactation.

Results

This report is currently being used to perform routine signal detection of adverse events reported during pregnancy and to perform pregnancy data analysis to incorporate into Periodic Benefit-Risk Evaluation Reports (PBRERs), where the safety profile includes pregnancy-related risks in "identified/potential risks” or “missing information” categories. This report is also being used to respond to pregnancy-related health authority queries. When responding to a health authority (or writing a cumulative review), having a report with all pregnancy-related data in one place makes the review process more efficient, especially with high case volumes. In addition, all the pregnancy-related information is provided in the form of listings as well as graphical visualizations. The timing and duration of an exposure (relative to gestational age) to a suspect drug and an adverse event is crucial for causality assessment. The custom report calculates the trimester of exposure (using an algorithm with the datapoints of last menstrual period, therapy start date of the drug, therapy stop date, and gestational age at the time of exposure) to assess risk. The intent is to continue to use this report to monitor and develop the safety profile of medicines used by pregnant and lactating women, since use during pregnancy remains as missing information in safety-related documents for the majority of medications.

Conclusion

Pregnant women represent an important segment (3.2% globally each year) of the population, but they are, for ethical reasons, excluded from clinical trials. In addition, study subjects are generally discontinued if they inadvertently become pregnant. Hence, the safety profiles of most medications used during pregnancy remain incomplete and part of “missing information” in safety related documents. However, pregnant patients still need access to medical treatment for chronic conditions, as well as acute conditions that may develop during pregnancy. Thus, safety information is vital for physicians to make prescribing decisions for pregnant women and/or their babies. Given that nearly half of all pregnancies may be unintended, inadvertent exposure to medicines poses a potential risk to the patient and the developing fetus. Therefore, monitoring of adverse events during pregnancy is an important consideration for the characterization of the overall safety profile of a medication. We suggest the following, based on our experience: 1) When planning to implement a new safety database or considering a change, it is important to select a database that comprehensively supports systematic capture of pregnancy reports in appropriate user-defined or standard fields with coded values. Additionally, attention should be given to pregnancy scenarios and related data when migrating to a new safety database to ensure data integrity; and 2) Accurate, complete, and consistent data entry is the backbone of efficient pregnancy data surveillance. This report allows us to efficiently perform pregnancy data analysis to help us better understand the effects of medicines used during pregnancy and lactation. We recommend that pharmaceutical companies develop a robust pregnancy surveillance program via custom report/dashboard for data analysis and update the existing safety profiles of medicines to better inform healthcare professionals and patients. Co-authors: Kerry Somers and Amit Soitkar