Medication history-wide association studies for pharmacovigilance of pregnant patients.

Background: Systematic exclusion of pregnant people from interventional clinical trials has created a public health emergency for millions of patients through a dearth of robust safety data for common drugs.

Methods: We harnessed an enterprise collection of 2.8 M electronic health records (EHRs) from routine care, leveraging data linkages between mothers and their babies to detect drug safety signals in this population at full scale. Our mixed-methods signal detection approach stimulates new hypotheses for post-marketing surveillance agnostically of both drugs and diseases-by identifying 1,054 drugs historically prescribed to pregnant patients; developing a quantitative, medication history-wide association study; and integrating a qualitative evidence synthesis platform using expert clinician review for integration of biomedical specificity-to test the effects of maternal exposure to diverse drugs on the incidence of neurodevelopmental defects in their children.

Results: We replicated known teratogenic risks and existing knowledge on drug structure-related teratogenicity; we also highlight 5 common drug classes for which we believe this work warrants updated assessment of their safety.

Conclusion: Here, we present roots of an agile framework to guide enhanced medication regulations, as well as the ontological and analytical limitations that currently restrict the integration of real-world data into drug safety management during pregnancy. This research is not a replacement for inclusion of pregnant people in prospective clinical studies, but it presents a tractable team science approach to evaluating the utility of EHRs for new regulatory review programs-towards improving the delicate equipoise of accuracy and ethics in assessing drug safety in pregnancy.