Frontiers in drug safety and regulation最新文献

{"title":"Communicating medication risks in pregnancy: Towards shared decision making.","authors":"Ursula Winterfeld, Kenneth Hodson, Maya Berlin, Benoît Marin, Michael Ceulemans, Corinna Weber-Schoendorfer, François R Girardin, David Baud, Béatrice Schaad, Alice Panchaud","doi":"10.3389/fdsfr.2025.1712216","DOIUrl":"10.3389/fdsfr.2025.1712216","url":null,"abstract":"<p><p>Medication use during pregnancy is common, yet safety data remain limited, often leading to exaggerated risk perceptions and suboptimal care. Current communication practices are fragmented: product labeling and patient leaflets tend to emphasize potential harms, while specialized resources are underused. We explore the challenges of conveying accurate risk-benefit information and highlight the need for shared decision making. Integrated, evidence-based resources accessible to both healthcare providers and patients can reduce misinformation, improve adherence to essential treatments, and ultimately enhance maternal and child health. The Swiss MAMA-MEDS initiative illustrates how a unified knowledge base can align messaging, address health inequalities, and support patient-centered pregnancy care.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1712216"},"PeriodicalIF":0.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12587009/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145461124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking drug safety signal detection and causality assessment in the age of AI: the risks of incomplete data and biased insights.","authors":"Priyanka Chhikara, Tarek A Hammad","doi":"10.3389/fdsfr.2025.1678074","DOIUrl":"10.3389/fdsfr.2025.1678074","url":null,"abstract":"","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1678074"},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443104/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145116032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying regulatory outcomes of Non-interventional Post-Authorisation Safety Studies (PASS) in the European repository of studies using publicly available information.","authors":"M F Almas, A Girardi, S Crisafulli, K Gvozdanovic, K M Hakkarainen, G Hyeraci, W E Hoogendoorn, B Rillmann, G Roberto, G Vitturi, G Trifirò","doi":"10.3389/fdsfr.2025.1574430","DOIUrl":"10.3389/fdsfr.2025.1574430","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Post-Authorisation Safety Studies (PASS) generate evidence that may support regulators to evaluate the benefit-risk profile of medicinal products and to take regulatory actions when needed. The European Medicine Agency (EMA) promoted decision-making transparency by publishing regulatory guidelines and endorsing the registration of PASS in the European Post-Authorisation Study (EU PAS) Register (currently HMA-EMA Catalogues of real-world studies). A recent analysis of the EU PAS Register showed a marked increase of PASS conducted as multidatabase studies (MDS) during the last decade.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;This study aimed to assess the feasibility of using public available information from the EMA website to identify regulatory outcomes of PASS and, to describe the retrieved regulatory outcomes of PASS by MDS and non-MDS.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Multidatabase PASS, and an equal number of non-multidatabase PASS, were selected from the EU PAS Register if: completed between 07/2012 and 12/2020, part of the Risk Management Plan (RMP) category 1,2 or 3, required by an European regulator, and conducted in ≥1 European country including United Kingdom (UK). Mentions of the identified PASS were searched in the Pharmacovigilance Risk Assessment Committee (PRAC) meeting minutes, the procedural steps document of the European Public Assessment Report (EPAR), and other publicly available EMA webpages, mainly using study title, acronym, protocol, or regulatory number. Whenever identified, the regulatory outcome information was retrieved.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 84 PASS (42 MDS and 42 non-MDS) were included in the analysis. We could identify 77% of the 84 PASS in at least one of the used sources but the information available was scarce. Among the identified PASS, information on regulatory outcomes was identified for 60%, representing 46% of all 84 PASS, with no differences between MDS and non-MDS. Regulatory outcome information was more frequently identified for imposed (78%) than non-imposed PASS (34%). The availability of regulatory outcomes increased from 25% for PASS completed in the years 2012-2014 to 56% for those completed in 2018-2020. The regulatory outcome information was unspecific for two thirds of the PASS with available outcomes, limiting our description of regulatory outcome types.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The attempt to identify and describe the regulatory outcomes of MDS registered into the EU PAS Register, and compare them to non-MDS, was impaired by the difficulties in retrieving the regulatory outcome insights from the publicly available sources such as, identifying PASS across sources, lack of information and granularity, standardisation and consistency across sources. We advocate for an increased transparency of the regulatory outcomes of PASS through the use of a unique PASS identifier for an easy link across sources, and for a complete regulatory outcome publica","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1574430"},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443101/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A national pharmacovigilance centre perspective on pandemic preparedness - <i>lessons learned from the COVID-19 pandemic</i>.","authors":"Florence van Hunsel, Agnes Kant","doi":"10.3389/fdsfr.2025.1644680","DOIUrl":"10.3389/fdsfr.2025.1644680","url":null,"abstract":"<p><p>The SARS-CoV-2 (COVID-19) pandemic highlighted the critical role of pharmacovigilance in ensuring vaccine and drug safety. This perspective from the Netherlands Pharmacovigilance Centre Lareb outlines key experiences and lessons learned during the pandemic. Lareb managed over 233,000 individual case safety reports (ICSRs) related to COVID-19 vaccines, with a considerable proportion submitted by consumers/vaccinated persons directly. Lareb employed both spontaneous reporting and cohort event monitoring (CEM) to gain a better understanding of the safety of these vaccines in a real-world setting. Challenges included the overwhelming volume of data, limited initial access to national vaccination and healthcare registries, underreporting of adverse reactions to SARS-CoV-2 treatments, and a strain on the trained staff to perform tasks while scaling up in personnel. Lareb addressed some challenges through further automation, although more work in this area is still needed. Communication efforts were expanded with a focus on transparency and timeliness. Key recommendations for future pandemic preparedness include investing in Artificial Intelligence for further automation in the reporting process and in signal detection, looking at ways to tackle underreporting for specific associations or medicines in innovative ways and enhancing timely linkage between vaccination and healthcare data. The article underscores the importance of transparent, independent communication and the need for a resilient pharmacovigilance system capable of rapid scale-up during health crises.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1644680"},"PeriodicalIF":0.0,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443082/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medication beliefs and adherence during and after pregnancy among women at risk for gestational hypertensive disorders.","authors":"Pauline Dreesen, Dorien Lanssens, Sandy Nouwen, Pauline Volders, Febe Janssen, Adelheid Soubry, Wilfried Gyselaers, Michael Ceulemans","doi":"10.3389/fdsfr.2025.1610273","DOIUrl":"10.3389/fdsfr.2025.1610273","url":null,"abstract":"<p><strong>Introduction: </strong>Low-dose aspirin initiated ≤16 weeks of gestation reduces the risk of developing early-onset preeclampsia. However, no recent data are available on women's beliefs about medication and adherence in pregnant women at risk for gestational hypertensive disorders (GHD). This study aimed to evaluate medication beliefs and adherence in this high-risk population, and to explore the relationship between adherence, self-reported aspirin intake, and pregnancy and neonatal outcomes.</p><p><strong>Methods: </strong>Pregnant women at risk for GHD followed up via remote blood pressure monitoring and who were prescribed aspirin 160 mg/day were included (ClinicalTrials.gov ID NCT04031430). Women's beliefs about medication (in general and during pregnancy) and adherence were assessed using the Beliefs about Medicine Questionnaire (BMQ) and the Probabilistic Medication Adherence Scale (ProMAS) administered during pregnancy (at inclusion), at 10-21 days and 4-6 months postpartum. Aspirin intake was self-reported in the MediSafe app. We did not intervene throughout the study.</p><p><strong>Results: </strong>A total of 73 participants were recruited at a median gestational age of 14.1 weeks (IQR:13.2-15.6). The mean pregnancy BMQ scores for overuse and harm were 10.6 ± 2.9 and 8.8 ± 2.2 on a total score of 20, respectively. A total of 95% agreed to have a higher threshold for taking medicines during pregnancy and 50% disagreed with refraining from using medicines during pregnancy. Similar positive attitudes towards medicines were observed postpartum. The mean ProMAS score in pregnancy was 10.3 ± 3.9 out of 18. Similar rates were observed at 10-21 days postpartum, while a trend toward lower adherence was seen at 4-6 months postpartum (mean score 8.9 ± 4.5). The mean \"minimal\" and \"maximal\" self-reported aspirin intake was 82.5% and 98.6%, respectively. ProMAS scores were positively correlated with self-reported aspirin intake. Uncomplicated pregnancies showed higher ProMAS scores during pregnancy compared to complicated pregnancies.</p><p><strong>Discussion: </strong>Women at risk for GHD involved in a clinical trial showed positive beliefs about medication use in general and during pregnancy throughout the perinatal period and reported high aspirin adherence rates. However, more research is needed to provide real-world adherence estimates in pregnancy and to assess the predictive utility of the ProMAS instrument to forecast adherence throughout pregnancy and adverse pregnancy and neonatal outcomes.</p><p><strong>Clinical trial registration: </strong>identifier NCT04031430.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1610273"},"PeriodicalIF":0.0,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443123/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145116039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Safety of corticosteroids in respiratory medicine.","authors":"Semra Bilaçeroğlu","doi":"10.3389/fdsfr.2025.1656299","DOIUrl":"10.3389/fdsfr.2025.1656299","url":null,"abstract":"","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1656299"},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Centralized daily drug management in clinical trial institutions and specific implementation plans.","authors":"Yu Tang, Xiaolong Fang","doi":"10.3389/fdsfr.2025.1620314","DOIUrl":"10.3389/fdsfr.2025.1620314","url":null,"abstract":"<p><strong>Background: </strong>Experimental drug management is an important part of clinical trial management and directly relates to the reliability of clinical trial data and the safety of participants. This study explores the implementation of centralized pharmacy management in clinical drug trials, addressing the limitations of decentralized approaches.</p><p><strong>Methods: </strong>It involves the establishment of a centralized drug warehouse with unified processes and digital systems, primarily relying on the Cold Chain Cloud Platform, Service Cloud Platform, and Enterprise WeChat Platform, to enhance precision and efficiency.</p><p><strong>Results: </strong>It indicated a significant reduction in error rates and improved adherence to clinical trial protocols. The centralized model also minimized protocol deviations and strengthened participant safety.</p><p><strong>Conclusion: </strong>It highlights the benefits of centralized management in enhancing drug administration efficiency and maintaining high standards of trial conduct, suggesting future integration with Artificial Intelligence (AI) and Electronic Health Records (EHR) for more precise pharmaceutical services.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1620314"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Federated learning: a privacy-preserving approach to data-centric regulatory cooperation.","authors":"Alexander Horst, Paul Loustalot, Sanjeev Yoganathan, Ting Li, Joshua Xu, Weida Tong, David Schneider, Nicolas Löffler-Perez, Erminio Di Renzo, Michael Renaudin","doi":"10.3389/fdsfr.2025.1579922","DOIUrl":"10.3389/fdsfr.2025.1579922","url":null,"abstract":"<p><p>Regulatory agencies aim to ensure the safety and efficacy of medical products but often face legal and privacy concerns that hinder collaboration at the data level. In this paper, we propose federated learning as an innovative method to enhance data-centric collaboration among regulatory agencies by enabling collaborative training of machine learning models without the need for direct data sharing, thereby preserving privacy and overcoming legal hurdles. We illustrate how Swissmedic, the Swiss Agency for Therapeutic Products, together with its partner agencies, proposes to use federated learning to improve TRICIA, an AI tool for assessing incoming reports of serious incidents related to medical devices. This approach enables the development of robust, generalisable risk assessment models that can potentially improve current processes. A proof of concept was deployed and thoroughly tested during the 14th Global Summit on Regulatory Science using synthetic data with participants from Swissmedic, the U.S. Food and Drug Administration (FDA), and the Danish Medicines Agency (DKMA), with promising initial results. This innovation has the potential to serve as a roadmap for other regulators to adopt similar approaches to optimize their own regulatory processes, contributing to a more integrated and efficient regulatory environment worldwide.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1579922"},"PeriodicalIF":0.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corticosteroids in lung cancer.","authors":"Vesna Ćeriman Krstić, Milija Gajić, Leonida Djukanović, Dragana Jovanović","doi":"10.3389/fdsfr.2025.1528468","DOIUrl":"10.3389/fdsfr.2025.1528468","url":null,"abstract":"<p><p>Despite significant advances in lung cancer treatment, patients with this disease still present with multiple symptoms that are very hard to control. Corticosteroids are widely used in patients with lung cancer, but without clear evidence for their efficacy. Thus, corticosteroids have been used for the treatment of conditions arising due to the tumor itself, adverse effects of the applied specific therapy and symptom palliation. In this review we are going to summarize clinical indications for corticosteroid use in patients with lung cancer: malignant airway obstruction, superior vena cava syndrome, brain metastases, treatment-related adverse events, anorexia and cachexia, fatigue, dyspnea, nausea and vomiting, spinal cord compression, and pain.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1528468"},"PeriodicalIF":0.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing decision support algorithm for hypertension medications for use in a digital therapeutic system.","authors":"Jeannie K Lee, J Skye Nicholas, Amani Albadawi, Kathleen C Insel","doi":"10.3389/fdsfr.2025.1476998","DOIUrl":"10.3389/fdsfr.2025.1476998","url":null,"abstract":"<p><strong>Introduction: </strong>Adherence to hypertension medications is low among older people, and there is limited guidance on the safety of taking a missed medication. Knowing the window of time when an older individual can safely take a missed medication could improve adherence and reduce the fear of overdosing. We developed and implemented a decision support algorithm for missed hypertension medications in a digital therapeutic system designed to facilitate self-management of hypertension medications and blood pressure among older adults.</p><p><strong>Methods: </strong>The medication formulary included hypertension medications and doses available in the United States that are safe for use by older people. The decision support algorithm was developed through a literature review of clinical and pharmacokinetic studies and knowledge of the pharmacology of aging (pharmacokinetics and pharmacodynamics). The algorithm was peer-reviewed and checked against available provider and patient instructions about missed hypertension medications. Case scenarios were used to code the algorithm into the app.</p><p><strong>Results: </strong>A total of 117 hypertension medications and combination products were included in the formulary of the <i>Medication Education, Decision Support, Reminding, and Monitoring</i> (MEDSReM^©) system, a mobile digital therapeutic. The formulary contains medication names and dose options available for selection at onboarding or when medication changes occur. The safe window for taking missed/overdue medication was programmed into the MEDSReM^© app for each medication and dosing frequency. The users are presented with \"take, snooze, and skip\" options when they receive a reminder and open the app to take the medication. If they open the app past the safe window hours, a recommendation to skip that dose and take the next dose at the regular time is presented. If the user decides to take the missed dose, a decision to take or skip the next dose is shown.</p><p><strong>Discussion: </strong>The MEDSReM^© decision support algorithm provides a safe window of time for each hypertension medication for older adults when they need to take their medication after the intended target time has passed. The interdisciplinary collaboration of clinical, technology, and research teams resulted in a novel, older adult-centered, time-specific digital therapeutic intervention to support decision-making about taking missed hypertension medications.</p>","PeriodicalId":521057,"journal":{"name":"Frontiers in drug safety and regulation","volume":"5 ","pages":"1476998"},"PeriodicalIF":0.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12443122/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}