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Pharmacovigilance emerged as a critical discipline in response to the thalidomide tragedy of the 1960s. Thalidomide, a sedative drug used as a sleep aide, was prescribed to pregnant women for help with morning sickness. It was later recognized that thalidomide use in pregnancy resulted in severe congenital malformations in thousands of infants worldwide. This public health disaster revealed profound shortcomings in post-marketing drug safety surveillance and prompted the development of formal regulatory frameworks to protect patients.
The Importance of Diversity
It is well known that the safety information of a drug obtained during its pre-authorization phase is limited. Clinical trials enroll specified cohorts of patients according to the inclusion and exclusion criteria. These clinical studies generally restrict comorbid diseases and medications, enroll specific age groups, require strict contraceptive use for women of childbearing potential, and require a specific stage of disease. Therefore, the patients in these clinical trials may not adequately represent the diversity of the population that will use the medication in real life, such as elderly individuals or those with multiple illnesses. Additionally, the sample size and duration of the clinical trial may limit the detection of rare adverse events or adverse events that emerge only with longer term use of the drug. Investigational clinical trials are also conducted under highly supervised, controlled conditions that differ from real-world use of medications by health care professionals. The adverse events identified during clinical trials are critical to the overall safety package, labeling of the drug, and assessment of risk vs. benefit for a patient.
Pharmacovigilance and Risk Detection
Once a medicine is on the market and available to be prescribed, collection of pharmacovigilance information continues to be important and is required by regulatory authorities. Through these efforts, new adverse events and risks can be identified. The risk-to-benefit ratio of a drug may be altered as well as additional disclosures to patients, and additional testing and monitoring may be needed. Throughout a drug’s life cycle, the reporting of adverse effects to regulatory agencies by healthcare professionals, patients, and the pharmaceutical industry is vital to capture a full and accurate understanding of a drugs' safety picture.
In recent years, the conduct of pharmacovigilance post-authorization of a drug has undergone a profound evolution, catalyzed by the integration of real-world data (RWD), digital health technologies, and artificial intelligence (AI). These advancements are fundamentally transforming the methodologies employed for the detection, evaluation, and prevention of adverse drug reactions (ADRs). The field is progressively shifting from reliance on traditional spontaneous reporting systems toward more proactive, data-driven approaches to safety surveillance.
Traditional Practices
Post-authorization pharmacovigilance has traditionally been based on the collection of information through the spontaneous reporting of suspected adverse reactions to regulatory authorities by healthcare professionals and patients, the conduct of post-authorization safety studies (PASS) to investigate specific safety issues or to assess the effectiveness of risk management measures, as well as post-authorization observational studies (EPAS) carried out under normal conditions of use to complement pre-authorization information.
Despite their pivotal role in the identification of safety signals, traditional pharmacovigilance systems continue to face significant limitations, particularly due to the persistent underreporting of adverse drug reactions (ADRs). Empirical evidence indicates that only 5–10% of ADRs are formally reported, with this issue being especially pronounced in resource-limited settings. These systems are often constrained by insufficient data granularity, delayed signal detection, and a lack of contextual information. Consequently, it is increasingly imperative to adopt more integrated and timely pharmacovigilance strategies that enhance the robustness and responsiveness of drug safety surveillance.
Real-World Data (RWD), digital health technologies, and artificial intelligence (AI) for collection of PV information.
Real-world data (RWD) offers the potential for collection of ADRs in a more robust, albeit passive manner than the traditional method of post-authorization safety surveillance which requires active safety reporting.
- Real-world data is data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Examples of RWD include data derived from electronic health records, medical claims data, and data from product or disease registries.
- Real-world evidence is clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD. For instance, data may be collected about dosage reduction or drug discontinuation due to ADRs. These ADRs when compiled may be different in incidence or prevalence than reported on the drug labeling and may also be new ADRs, not previously reported.
As such, RWE plays a pivotal role in monitoring long-term safety, effectiveness, and risk profiles of drugs after market approval. The addition of RWD and RWE helps in the detection of rare or delayed adverse drug reactions, drug interactions, and cumulative toxicities. RWE can ensure data collection from vulnerable groups (e.g., elderly, pregnant women, patients with comorbidities), that were not included in prior clinical studies revealing differential drug responses and safety signals.
Real world data from traditional health care sources can be supplemented by those collected by digital health technologies—such as mobile applications, wearable biosensors, and social media platforms. Such data collection can significantly broaden the scope of pharmacovigilance by enabling the real-time capture of patient-reported outcomes and behavioral data. These tools facilitate continuous engagement with patients outside traditional clinical settings, offering novel opportunities to monitor drug safety in everyday life.
Artificial Intelligence enables the scanning, collection and analysis of the information on drug safety collected via real world evidence and from digital health technologies. Safety signals that might otherwise be delayed or misattributed may be able to more easily and accurately detected by the addition of AI.
Pharmacovigilance teams on the CRO and sponsor side are utilizing artificial intelligence (AI) applications to enhance early detection of safety signals in clinical data, RWE, and digital biomarker data, and using AI to help automate case processing and reporting workflows.
Regulatory Shifts
Regulatory bodies such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are increasingly utilizing Real-World Evidence (RWE) to complement the traditional system of adverse event reporting in regulatory decision-making.
The FDA formalized its approach to RWE through the 21st Century Cures Act, establishing a framework in 2018 to support drug approvals, new indications, and post-marketing safety evaluations. Similarly, the EMA launched the DARWIN EU® initiative, a coordinated network designed to generate high-quality RWE from healthcare databases across Europe.
Recent analyses reveal that RWE is being increasingly applied in both pre-authorization and post-authorization contexts, reflecting a broader trend toward more flexible, data-driven regulatory frameworks aimed at enhancing the timeliness, relevance, and patient-centeredness of drug safety evaluation processes.
Agencies use Real-World Evidence to monitor drug safety and assess long-term effects once a product is on the market, thereby providing continuous safety oversight and real-world adherence patterns.
Future directions of RWE in Pharmacovigilance
The progressive integration of Real-World Evidence (RWE) into pre-authorization assessments, post-marketing surveillance activities, and risk management strategies by the Regulatory authorities facilitate continuous safety monitoring throughout the entire lifecycle of medicinal products.
The future landscape of RWE is expected to continue to expand significantly, incorporating data from digital health technologies, patient-reported outcomes, social media platforms, mobile applications, and genomic and biomarker sources. This evolution will enable more personalized and population-specific safety insights.
Moreover, international regulatory bodies including the FDA, EMA, MHRA, PMDA, and NMPA are working toward harmonizing standards for the use of RWE in pharmacovigilance. These efforts promote cross-border data sharing, unified safety frameworks, and collaborative signal detection initiatives. In parallel, regulatory agencies are initiating their own RWE studies to complement industry submissions and address evidence gaps, particularly in areas such as rare diseases, pediatric populations, fetal effects of drugs, and long-term safety monitoring.
Conclusion
The evolution of pharmacovigilance is driven by digital innovation and real-world insights. Stakeholders must adapt to leverage these tools for improved patient safety and regulatory compliance.
References
1.Pathuri, V. (2020). Next-generation pharmacovigilance: AI, real-world evidence, and global harmonization for proactive drug safety monitoring. IOSR Journal of Pharmacy and Biological Sciences (IOSR-JPBS), 15(1, Ser. IV), 59–64. https://doi.org/10.9790/3008-1501045964Imbrici, P., De Bellis, M., 2.Liantonio, A., & De Luca, A. (2025). Investigating the benefit-risk profile of drugs: From spontaneous reporting systems to real-world data for pharmacovigilance. Methods in Molecular Biology, 2834, 333–349. https://doi.org/10.1007/978-1-0716-4003-6_16
3.Aher, S., Mahajan, M., Upaganlawar, A., & Upasani, C. (2024). Pharmacovigilance in the digital age. International Journal of Pharmaceutical Sciences, 2(4), 691–711. https://www.ijpsjournal.com
4.FDA – Real-World Evidence Program
Overview of FDA’s framework for integrating RWE into regulatory decision-making, including post-marketing safety evaluations.
FDA RWE Program [Real-World...ence | FDA]
5.EMA – Review of RWE Use in Regulatory Decision-Making
Details regulator-led studies and the DARWIN EU® initiative supporting lifecycle safety monitoring.
EMA RWE Review [Use of rea...– EMA ...]
6.Hernandez, R., Pugeat, A., Collet, J., Lopez-Grancha, M., Fazeli, M. S., Hofer, K., & Collet, J.-P. (2025, May). Real-world evidence in FDA and EMA regulatory reviews: Insights on its role in submission packages and approvals [Conference poster]. ISPOR 2025, Montréal, Quebec, Canada. Value in Health, 28(S1), HPR82. Retrieved from https://www.ispor.org/heor-resources/presentations-database/presentation-cti/ispor-2025/poster-session-3/real-world-evidence-in-fda-and-ema-regulatory-reviews-insights-on-its-role-in-submission-packages-and-approval
Author:
Pilar Larrodera, Senior Pharmacovigilance Officer
Linical