Spontaneous reporting is one of the most effective methods to detect new and rare suspected adverse drug reactions (ADRs) [1] and its utilisation in signal detection has been optimised over time [1, 2]. Data from spontaneous reports have been used to evaluate the safety of medicine exposure during pregnancy in the absence of reliable data from clinical trials, but underreporting, data quality issues and the lack of relevant information are major drawbacks of spontaneous reporting systems [3]. Observational studies and disproportionality methods have therefore been used for hypothesis testing and signal generation regarding the impact of medicines on pregnancy outcomes or embryo-foetal development [4]. However, given the methodological difficulties, such as the background rate of specific individual birth defects, the variability in reporting practices and the complexity of pregnancy-related symptoms, signal detection in this population remains challenging [5].

Medicine use in pregnancy is the norm—not the exception. According to a study conducted in France, medicines are prescribed in up to 90% of all pregnant women [6]. Nonetheless, available information on the impact of medicines used during pregnancy is considerably falling behind the information available for other vulnerable populations [7], such as children, elderly and patients with renal and hepatic impairment. Given that pregnant women may become ill, and people with a disease may become pregnant, it is important to generate and interpret data regarding the impact of medicine use in pregnancy, recognising that treating maternal disease, more often than not, benefits both mother and child [8, 9].

In 2001, EudraVigilance (EV) was created as a system for managing and analysing information on suspected adverse reactions to medicines which have been authorised or are being studied in clinical trials in the European Economic Area (EEA), and it has become one of the largest pharmacovigilance databases in the world [10]. As of 31 December 2023, EV included over 15.9 million unique suspected ADR case reports [11] submitted by EU national competent authorities (NCAs), marketing authorisation holders (MAHs) and sponsors in line with the EU legal requirement [12,13,14] and the accompanying guidelines [15]. Despite the several functionalities available in EV to support pharmacovigilance activities, a dedicated data field, to indicate whether the cases are associated with medicine exposure in pregnancy and to help streamline the reporting, is not yet available in the current ICH E2B(R3) format [16] for electronic transmission of individual case safety reports (ICSRs). Because signal detection is carried out routinely on the entire EV database, signals associated with pregnancy may be diluted and therefore may not surface. Considering that spontaneous reporting systems were developed largely as a consequence of thalidomide, it was decided to explore the possibility of identifying in EV a subset of cases reporting ADRs in pregnancy, with a view to developing signal detection methods specifically for this population.

In EV, reported ADRs are coded using terms from the Medical Dictionary for Regulatory Activities (MedDRA®Footnote 1) [17], which is hierarchical and includes five different levels: System Organ Class (SOC); High Level Group Term (HLGT); High Level Term (HLT); Preferred Term (PT) and Lowest Level Term (LLT). To support pharmacovigilance activities, PTs related to defined medical conditions or safety topics of regulatory interest are grouped in Standard MedDRA Queries (SMQs). Standard MedDRA Queries facilitate retrieval of cases as a first step when investigating safety issues related to medicines and may combine very specific terms (narrow scope) and less specific terms (broad scope). Such grouping is consistent with the description of the overall clinical manifestation associated with a particular adverse event and drug exposure. The SMQ Pregnancy and Neonatal Topics (PNT) [18] (Fig. 1) was developed to make it more compatible with regulatory goals related to pregnancy and neonatal topics [19] and it is normally used to identify pregnancy cases in pharmacovigilance reporting systems [20, 21]; however, the data retrieved using this approach result in a broader range of ADRs. Examples include: (1) lack of therapeutic efficacy of contraceptive terms co-reported with terms related to drug exposure during pregnancy; (2) cases of ADR in the mother following use of abortifacients; (3) situations not related to in utero exposure (i.e., paediatric exposure); (4) reporting malpractice and coding quality issues where pregnancy terms are used incorrectly.

Hierarchy structure of pregnancy and neonatal topics (SMQ). The above photographic content is protected by MedDRA’s copyright and extracted from chapter 2.83 "Pregnancy and neonatal topics (SMQ)" in the Introductory Guide for Standardised MedDRA Queries (SMQs) Version 27.0,  2024 [18]. A minor modification to the original table was made to include the SMQ levels available in MedDRA. MedDRA Medical Dictionary for Regulatory Activities, SMQ Standardised MedDRA Query

As part of a larger initiative [8] to strengthen the evidence base regarding medicine use in pregnancy, this manuscript reports on a novel approach to identify a subset of cases in EV that are most likely to be associated with medicine exposure in pregnancy, with the aim to improve signal detection for this population.

The first objective of this study was to assess the utility of the SMQ PNT (broad) in identifying ADRs associated with exposure during pregnancy. The second objective focused on leveraging the insights gained from this evaluation to develop a rule-based algorithm that more reliably identifies cases that are truly representative of an ADR occurring during pregnancy. For example: ADRs with an impact on the baby (e.g., growth retardation in utero, congenital malformation), ADRs with an impact on the mother (e.g., pre-eclampsia) or both (e.g., miscarriage).