Polypharmacy in older adults is associated with increased risks of adverse drug events and functional decline. Discharge summaries often contain deprescribing recommendations, but these are frequently overlooked due to documentation complexity. The aim of this study was to develop and validate a two-stage hybrid natural language processing (NLP) system combining rule-based extraction and large language model (LLM)-based classification for automated identification of deprescribing recommendations from discharge summaries. This retrospective cohort study included 850 discharge summaries from patients aged ≥ 65 years with hospitalisation for ≥ 48 h across six public hospitals in New South Wales, Australia. Model 1 (rule-based extraction) identified discharge medications and candidate sentences containing pre-defined deprescribing keywords. Model 2 (LLM-based classification) categorised candidate sentences into five categories, from which a binary outcome (deprescribing recommendation present versus absent) was derived using a pre-specified mapping. Data were split into training (80
Pregnant women are often excluded from clinical trials owing to uncertainty about fetal safety and adverse pregnancy complications. As such, little is known about the effect of medications on pregnancy at the time of marketing. Post-marketing data are therefore important for establishing the safety of treatments in pregnancy, particularly in chronic diseases requiring long-term therapy. Mepolizumab (NUCALA), a first-in-class biologic treatment for patients with severe eosinophilic asthma, was first approved in the United States (US) and European Union (EU) in 2015 as an add-on maintenance treatment for adult and adolescent patients. At the time of marketing, pregnancy safety data for mepolizumab was limited. To address this gap, a Post-Authorization Safety Study (PASS) was conducted—a pregnancy registry to monitor pregnancies exposed to mepolizumab and evaluate the possible teratogenic effect of this medication compared with women treated with other anti-asthmatics and those without asthma. The Mepolizumab Pregnancy Exposure Study (GSK ID: 200870; EU PAS Number: EUPAS13772), a phase IV, prospective, observational exposure registry, was initiated in 2016 by the Organization of Teratology Information Specialists (OTIS) Research Center. Despite extensive recruitment efforts, enrollment into the mepolizumab-exposed cohort remained low during the 5-year enrollment period. In contrast, robust enrollment in the anti-asthmatic comparison cohort was achieved, suggesting both the ability to recruit pregnant women with asthma and the limited use of mepolizumab in pregnancy. The Mepolizumab Pregnancy Exposure Study was ultimately closed in 2024 due to inadequate recruitment. This commentary presents the challenges experienced in the Mepolizumab Pregnancy Exposure Study and describes a pragmatic decision-making framework aimed at mitigating similar issues in future post-marketing pregnancy safety studies, particularly in the context of low treatment exposure in individual population-level data sources. This framework considers important inputs such as prior experience with treatment in the same therapeutic area, background maternal and fetal risks, and potential treatment utilization in the population of interest. A principal recommendation stemming from this framework is the implementation of enhanced worldwide pharmacovigilance, which offers a more robust and structured approach to data collection than standard pharmacovigilance methods, thereby improving information quality and enabling the capture of important variables and confounders, when the exposure rate is low in a population and registry or other database studies cannot reasonably be conducted. However, given the inherent limitations of pharmacovigilance in generating definitive safety conclusions, enhanced data collection methods serve as a pragmatic and necessary tool for ongoing surveillance, to aid in providing information until other types of study designs becoming feasible. Mepolizumab, an injectable treatment for severe eosinophilic asthma, had limited safety information in pregnant women at time of marketing. To address this crucial gap, the Mepolizumab Pregnancy Exposure Study, a Post-Authorization Safety Study was initiated in 2016. This registry aimed to monitor pregnancies exposed to mepolizumab compared with women treated with other anti-asthmatics and those without asthma. Despite significant recruitment efforts, enrollment into the mepolizumab-treated group remained low over the 5-year enrollment period, leading to its closure in 2024. This low recruitment highlighted two things: pregnant women with asthma could successfully be recruited and the limited use of mepolizumab in pregnancy. This article discusses the challenges experienced in the Mepolizumab Pregnancy Exposure Study and describes a practical decision-making framework for post-marketing pregnancy safety studies. This framework considers important factors such as prior experience with similar treatments, background maternal and fetal risks, and potential treatment utilization in the population of interest. For scenarios of low treatment exposure in individual population-level data sources, a key recommendation is enhanced pharmacovigilance as a more robust and structured way of collecting safety information than standard methods. While these methods rarely establish definitive safety conclusions, they are a practical and necessary tool until more robust study designs become feasible.
Treatment-resistant depression (TRD) is associated with elevated suicide risk, but real-world evidence on whether esketamine reduces suicide attempts and intentional self-harm remains limited. The aim was to estimate whether current esketamine exposure was associated with a higher or lower risk of recorded nonfatal, medically attended suicide attempt or intentional self-harm among adults with TRD using a large, real-world administrative claims database. We conducted a retrospective cohort study using a nationwide, multipayer administrative claims database from January 2015 through June 2025. Among 1,574,657 adults eligible for matching, patients initiating esketamine after TRD were matched to up to three controls using risk-set propensity score matching. A marginal structural model combined a baseline esketamine treatment probability weight accrued from TRD to index with longitudinal inverse probability of treatment weights. Follow-up continued through month 18. The final cohort of complete 3:1 matched sets included 23,140 patients, comprising 5785 treated patients and 17,355 controls, who contributed 295,137 patient-months. Current esketamine exposure was not associated with a statistically distinguishable difference in recorded nonfatal, medically attended suicide attempt or intentional self-harm. The hazard ratio (HR) was 1.017, the 95
Drug safety remains central to patient benefit, as maximizing the value of beneficial therapies requires recognition, appropriate characterization, and effective mitigation of treatment-related adverse drug reactions (ADRs). These challenges, particularly with the advent of artificial intelligence (AI) tools, have increased interest in predictive safety as a lifecycle scientific capability that seeks to anticipate plausible harm in a timely fashion and translate evolving evidence into more informed decisions across acquisitions, clinical development, and postmarketing use. In this article, predictive safety is used primarily to mean product-level and population- or subgroup-level anticipation of plausible treatment-related harm, rather than an autonomous patient-level clinical decision-making approach. Recent advances in AI, human genetics, mechanistic modeling, translational biomarkers, and real-world data have strengthened the scientific basis for this approach. However, predictive safety should never be viewed as a promise to eliminate ADRs or as a substitute for clinical judgment. Its value would be in improving prospective ADR characterization, supporting portfolio prioritization, and enabling timely and more targeted mitigation. In some settings, notably prospective genotype-based screening before exposure, it might prevent the reaction from occurring. This article argues for the development of a governed AI-supported predictive safety ecosystem. It outlines the reasons predictive safety is needed and the context in which it is most likely to add value. It also discusses principal implementation risks, including fragmented data, unstable phenotypes, model drift, transportability failure, and misuse of probabilistic outputs, together with practical mitigation strategies and leading indicators for early governance response.
Adverse events (AEs) reported with medicines and vaccines form the foundation of pharmacovigilance (PV), enabling the detection, assessment, and prevention of drug-related risks. Initial AE reports often lack relevant clinical detail, limiting their utility. Follow-up is used to obtain additional information but is resource-intensive. Spontaneous reporting systems receive large volumes of reports and follow-up yields additional information in only a proportion of cases. Given these volumes and variable yield, it is important to define when follow-up is most likely to add value and when it is likely to be low-yield or futile. This study aimed to identify scenarios where follow-up on AEs meaningfully improves the understanding of medicine and vaccine safety, and to delineate circumstances when it may be less beneficial or futile. A Delphi based methodology was used to systematically gather expert consensus on scenarios in which follow-up of AE reports enhances the understanding of medicine and vaccine safety. Data saturation was achieved after ten interviews. Panel members identified three primary scenarios in which follow-up adds value in PV: supporting causality assessment, strengthening signal detection and monitoring, and informing risk management and public health actions. They saw questionable or no value in follow up of well-characterised labelled events, cases in which the reporter cannot be contacted or did not consent to further contact, and settings where additional data were unlikely to alter benefit-risk. This study characterises expert perspectives on when follow-up activities are most likely to provide actionable value. Our results indicate that follow-up improves understanding when it resolves clinical uncertainty, but is inefficient when pursued without regard to impact, supporting a shift to proportionate, purpose-driven follow-up strategies for consistent and efficient use of resources including criteria for prioritisation and de-prioritisation.
Phloroglucinol is a spasmolytic drug widely prescribed in France for gastrointestinal or pelvic pain, and frequently used during pregnancy despite limited evidence regarding its safety. We aimed to evaluate the association between first-trimester phloroglucinol exposure and the risk of major congenital malformations (MCMs) in a nationwide cohort. Using data from the French EPI-MERES cohort based on the national health data system (SNDS), we identified all pregnancies ending after 22 weeks between 2010 and 2022, excluding women with phloroglucinol use in the year before pregnancy. We compared the risks of 68 MCM subtypes according to exposure during gestational weeks 3–12. Adjusted odds ratios (aORs) were estimated using logistic regression controlling for maternal sociodemographic, medical and pregnancy characteristics. Interpretation relied on effect size (aOR > 1.30) and consistency across sensitivity analyses. Among 6,233,539 pregnancies, 1,024,369 (16.4
Pharmacovigilance is essential to ensuring patient safety by enabling timely identification of adverse reactions in increasingly complex and voluminous data. Routine quantitative signal detection methods generate statistical alerts for product-event pairs based on predefined criteria; however, most alerts do not warrant further investigation, creating inefficiencies and significant time demands for pharmacovigilance teams. Manual triage of these alerts is often resource-intensive, prone to variability, and challenging to audit, highlighting the need for more reliable, transparent and efficient triage strategies. This study aimed to design, develop and prospectively evaluate an explainable Machine Learning for Intelligent Triage (MLIT) tool to assist pharmacovigilance teams in reviewing statistical alerts for vaccine and drug portfolios. The objective was to enhance signal detection performance without increasing the risk of missing signals, improving operational efficiency and maintaining decision traceability and regulatory compliance. Alert and individual case safety report data were retrieved from the company’s safety and signal management databases. Feature selection was guided by prior experience with a published case completeness tool, called Clinical Utility Score for Prioritisation (CUSP), and expert input. Of several ML methods explored, eXtreme Gradient Boosting (XGBoost) emerged as the optimal algorithm, with models trained and tested using a 75/25 split dataset. Iterative model refinement was conducted using Shapley Additive Explanations analyses to ensure explainability and alignment with safety reviewers’ decision-making processes. Refined models underwent prospective validation in two four-month prospective validation studies, covering over 20 products across vaccine and drug portfolios. The prospective validations assessed concordance between model predictions and reviewers’ decision under real-world conditions, as well as estimated time savings. The vaccine model demonstrated robust predictive performance, achieving a weighted-average F1 score of 0.81 and an accuracy of 0.79. In the prospective validation phase, 92
The AS01E-adjuvanted respiratory syncytial virus prefusion F protein vaccine (adjuvanted RSVPreF3) received its first marketing authorization in May 2023 for the prevention of respiratory syncytial virus lower respiratory tract disease in individuals aged ≥ 60 years. We conducted a review of post-marketing safety surveillance data following adjuvanted RSVPreF3 administration. Spontaneous adverse events (AEs) that were reported worldwide since the first approval (3 May, 2023) to 2 May, 2025 in the GSK global safety database were analyzed. Up to 2 May, 2025, 13.4 million doses of adjuvanted RSVPreF3 were distributed globally. A total of 2861 spontaneous reports, including 7012 AEs (serious: 11.0
Sustained exposure to oral corticosteroids (OCS) increases the risk of upper gastrointestinal bleeding (UGIB). It is uncertain whether short-term OCS treatment of asthma exacerbations increases this risk. This study aims to estimate the risk of acute UGIB after transient OCS use in patients with mild-to-moderate asthma. We used a case-crossover design within a cohort of patients with mild-to-moderate asthma, aged 18–40 years during 2000–2023, from the UK’s Clinical Practice Research Datalink. Subjects who experienced a first severe UGIB formed the case series. Short-term OCS was defined by a prescription for ≤ 14 days, with a 30-day residual effect period. For each case, the UGIB event date and 6 control dates, selected at 45-day intervals in the prior year, were considered exposed if the prescription spanned the date. The odds ratio (OR) of UGIB was estimated using conditional logistic regression, adjusted for time-varying use of asthma inhalers and medications related to bleeding risks. Findings The cohort involved 655,217 patients with mild-to-moderate asthma, with 743 experiencing a first UGIB who received 1160 OCS prescriptions in the past year. The crude and adjusted ORs of UGIB after OCS use versus non-use was 1.12 (95
Anti-spike monoclonal antibodies (mAbs) for early treatment of COVID-19 represented a significant improvement in the pharmacological management of the SARS-COV-2 pandemic, especially in early phases, but the continuous emergence of novel virus variants of concern (VoC) required a rapid and continuous benefit-risk assessment. To identify possible unexplored safety signals of anti-SARS-CoV-2 mAbs through disproportionality analysis using VigiBase, the World Health Organization (WHO) global pharmacovigilance database. We conducted a disproportionality analysis of VigiBase (February 2020–December 2023). All de-duplicated individual case safety reports (ICSRs) for bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, regdanvimab, sotrovimab, and tixagevimab/cilgavimab were retrieved. Descriptive analyses of ICSRs and distribution of suspected adverse drug reactions across VoC-defined periods (Alpha, Delta, Omicron) were performed. Disproportionality analysis was conducted and reported in accordance with the READUS-PV guideline. Reporting odds ratios (RORs) with 95
Pharmaceuticals in aquatic environments are a growing environmental concern. Because of their widespread use and poor removal by conventional wastewater treatment, benzodiazepines are frequently detected in treated effluents. To synthesise global evidence on the occurrence and distribution of benzodiazepines and their metabolites across the urban water cycle. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in performing this systematic review. Bibliographic databases PubMed (including PubMed Central and Medline), Embase and Scopus were searched, from the inception date to July 26th, 2024, using query terms related to benzodiazepines (BDZs) and water pollution. Titles, abstracts and full text of the articles were independently evaluated by six review authors. Of 1973 records identified, 119 studies published between 2001 and 2024 met the inclusion criteria. Most research (N = 102) was conducted in European countries, followed by Asia (N = 29), America (N = 16), Africa (N = 5) and Australia (N = 2). Reported BDZ concentrations varied widely across the included studies, ranging from below analytical detection limits to several thousand ng/L, depending on the specific compound, sampling strategy, analytical technique, and environmental matrix. Most of the included studies searched BDZs in surface water (N = 61), followed by wastewater treatment plants (WWTP) effluents (N = 47) and WWTP influents (N = 40). Diazepam (N = 64 studies), oxazepam (N = 58 studies), lorazepam (N = 45 studies), temazepam (N = 31 studies) and alprazolam (N = 29 studies) were the most frequently detected compounds. Global data highlight the need for standardised monitoring frameworks, targeted sources mitigation, and advanced water treatment technologies capable of efficiently removing chemically stable pharmaceutical compounds. Strengthening these approaches is essential to reduce ecological risks, minimise human exposure, and safeguard the long-term integrity of aquatic ecosystems.
The safety signal assessment process evaluates the potential causal association between a medicinal product and a specific adverse event by integrating multiple streams of evidence. Existing causality assessment methods remain challenged by the considerable manual effort involved and by decision variability, even when drawing on the same underlying domains of evidence. This work addresses the need in contemporary pharmacovigilance for a more efficient and harmonized approach to signal confirmation that preserves scientific rigor while mitigating the limitations of the current assessment processes. To address this need, the article describes design considerations for an artificial intelligence (AI)-enabled, integrated approach for safety signal causality assessment, referred to as Signal Confirmation through Omnichannel Pharmacovigilance Evidence (PV-SCOPE). As a conceptual proof-of-principle, the proposed approach describes how the Hammad–Afsar holistic causality assessment framework could be operationalized through multimodal evidence integration and structured approach, while preserving the central role of clinical and scientific reasoning in causality assessment. Because the AI workflow is presented as a design-oriented framework rather than a completed or validated model, the article focuses on architectural logic, governance, and validation and regulatory requirements rather than reporting performance results.
Targeted therapies have transformed the treatment landscape for patients with chronic lymphocytic leukemia (CLL). These therapies include the selective B-cell lymphoma-2 (BCL-2) inhibitor venetoclax and Bruton’s tyrosine kinase (BTK) inhibitors (e.g., ibrutinib, acalabrutinib, zanubrutinib). Especially in a setting of long-term care, safety and tolerability are important considerations. Although generally well tolerated, targeted therapies for relapsed and refractory CLL are associated with potentially treatment-limiting untoward effects, often within weeks to months of initiating therapy. These include myelosuppression (e.g., neutropenia); tumor lysis syndrome, infection, and gastrointestinal effects with venetoclax; as well as cardiovascular diseases (e.g., hypertension, atrial fibrillation/flutter) and infection (e.g., pneumonia) with BTK inhibitors. Instrumental to management of these adverse effects are effective risk assessment, stratification, and modification; prophylaxis; and regimen modifications, with appropriate measures to minimize pharmacokinetic interactions.
The rollout of new vaccines in low- and middle-income countries often faces significant challenges due to underdeveloped disease surveillance and pharmacovigilance practices for monitoring vaccine safety and effectiveness. In 2019, RTS,S/AS01E, the first malaria vaccine to demonstrate efficacy, was piloted in selected regions of Ghana, Kenya, and Malawi to evaluate RTS,S/AS01E real-world safety, effectiveness, impact, and operational feasibility. To strengthen safety monitoring and to gather additional data during rollout, several phase IV studies were conducted that included a capacity-building initiative to enhance disease surveillance and pharmacovigilance practices among healthcare professionals. Here, we describe the capacity-building experience, including targeted training strategies and accompanying paper-based and digital tools developed to improve detection, diagnosis, and reporting of adverse events of special interest (AESIs) and adverse events following immunization (AEFIs). We summarize the impact of the initiative, challenges, and actions taken, and share lessons learned to guide future capacity-building initiatives in low- and middle-income countries. The initiative included tailored, frequent, 2-day in-person training sessions for both medical and non-medical professionals in hospital and community settings, complemented by online courses, practical job aids, a tele-expertise platform, and a mobile alert system to improve adverse event reporting. The initiative reached approximately 5000 community healthcare professionals and 1000 study staff. Knowledge assessments after the trainings indicated marked improvements, with scores increasing from 41
Dolutegravir, the anchor drug of combination antiretroviral therapy (cART), has been associated with sexual dysfunction. We have evaluated the burden, correlates and nature of sexual dysfunction among Ugandan males living with HIV receiving dolutegravir-based antiretroviral therapy. In a cross-sectional study in one health centre, we collected sociodemographic and clinical data via structured interviews, undertook clinical examinations and performed data abstraction from electronic medical records. Sexual function was evaluated using the International Index of Erectile Function and the Changes in Sexual Functioning Questionnaire. Modified Poisson regression was utilised to estimate prevalence ratios (PRs), modelling dolutegravir exposure as the primary independent variable while adjusting for sociodemographic and clinical factors as secondary covariates. The prevalence of erectile dysfunction among males receiving dolutegravir-based cART for > 1 day to 6 months was twice that of cART-naive males (59
Medication shortages are a considerable and ongoing issue in healthcare, disrupting consumer access to medicines. Since 2021, Australia’s national medicines regulator has issued Serious Scarcity Substitution Instruments (SSSIs), allowing pharmacists to substitute a specific therapeutically equivalent strength and/or formulation of a medicine without prior approval from a prescriber. The impact of SSSIs on utilisation of medicines has not been investigated. To determine whether SSSIs are effective in addressing medicine shortages and meeting patients’ needs. This retrospective cohort study used aggregated pharmacy claims to examine the utilisation of 12 medicines, which had an SSSI. We calculated the percentage change in defined daily doses dispensed per 1000 population per day in the 11 months after SSSI implementation, compared with the previous 2 years. A percentage change of less than 20
BACKGROUND:Category X medicines are those which have such a high risk of causing foetal harm that they are contraindicated in pregnancy. When used in reproductive age women, risk management strategies are warranted to reduce unintended pregnancy exposure. OBJECTIVE:To identify documentation of pregnancy risk management strategies for Category X medicines across Australian medicine information sources. METHOD:The TGA Prescribing Medicines in Pregnancy Database (PMPD) was searched to identify Category X medicines licensed for indications relevant to reproductive age women. For each Category X medicine included in this evaluation, regulatory documents (Product Information [PI] and Consumer Medicine Information [CMI]) and corresponding monographs/chapters in clinical resources (Australian Medicines Handbook [AMH] and Therapeutic Guidelines [TG]) were reviewed for boxed warnings relating to pregnancy risks, pregnancy testing and contraception recommendations, and formal pregnancy prevention programs. RESULTS:Thirty-nine Category X medicines were retrieved through the TGA PMPD, 19 of which met the inclusion criteria. Boxed warnings documenting pregnancy risks were present for 47% (9/19) of medicines. Pregnancy testing and contraception recommendations appeared in most PIs and CMIs (89%, 17/19), as well as in 15 of 17 (88%) medicines listed in the AMH, but were only present for one of 12 (8%) medicines listed in the TG. Structured pregnancy prevention programs exist for only 16% (3/19) of medicines. CONCLUSIONS:Pregnancy risk management strategies for Category X medicines are inconsistently employed across Australian medicine information sources. Improving the quality and consistency of pregnancy risk management strategies is necessary to avoid harms from inadvertent exposure during pregnancy.
Biologic and targeted synthetic disease-modifying antirheumatic drugs effectively manage rheumatoid arthritis but are associated with varying risks of adverse events. Comparing the risk of key clinical events across biologic and targeted synthetic disease-modifying antirheumatic drugs to guide safer prescribing behavior. A population-based cohort study analysed patients with rheumatoid arthritis initiated on one of 12 biologic and targeted synthetic disease-modifying antirheumatic drugs (2009–22) in Hong Kong, with adverse events assessed over 5 years, including major adverse cardiovascular events, infections, malignancies, diabetes mellitus, depression, hospitalisation and all-cause mortality. Marginal structural models with inverse probability weighting addressed time-varying confounding and selection bias. Death was treated as a competing risk, and Bonferroni correction accounted for multiple comparisons. Among 2697 patients with rheumatoid arthritis (4276 treatment episodes), the estimated 5-year cumulative probability of adverse events were broadly comparable across biologic and targeted synthetic disease-modifying antirheumatic drugs: with hospitalisation that ranged from 0.48 (95
