Pharmacovigilance

RWE Methods · Pharmacovigilance

Pharmacovigilance and Real-World Safety

14 to 15 October 2026Hampton Inn by Hilton, Boston Seaport, USA

Pharmacovigilance is the science of detecting, assessing and preventing the adverse effects of medicines. Real-world data is making it faster and broader.

Safety, signal detection and the real-world data behind them are on the agenda at RWE Connect 2026 in Boston.

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    150+Attendees
    60%Director / VP and Above
    40+Speakers
    200+Meetings Facilitated

    The sources

    The Data Behind Pharmacovigilance

    Safety surveillance draws on many streams of data, each catching signals the others might miss.

    Spontaneous Reports
    Adverse-event reports in systems such as FAERS and VigiBase.
    EHR & Clinical Notes
    Structured and unstructured data from routine care.
    Administrative Claims
    Large-population safety signals from billing data.
    Product & Disease Registries
    Long-term, structured safety follow-up.
    Medical Literature
    Published case reports and studies.
    Patient-Generated & Social
    Real-world reports from patients and communities.

    How it works

    The Pharmacovigilance Process

    From a first hint of a problem to action, safety surveillance follows a disciplined path.

    Step 1
    DetectSurface a potential safety signal.
    Step 2
    ValidateConfirm the signal is real, not noise.
    Step 3
    AssessWeigh causality, severity and frequency.
    Step 4
    PrioritizeRank signals by risk and impact.
    Step 5
    ActUpdate labels and risk-management plans.
    Step 6
    CommunicateInform regulators, clinicians and patients.

    The shift

    How Real-World Data Strengthens Pharmacovigilance

    Real-world data is moving safety surveillance from periodic and reactive to continuous and proactive.

    Broader Signal Detection
    Real-world data catches signals that spontaneous reports miss.
    AI and NLP
    Machine learning mines unstructured records for adverse events.
    Continuous Monitoring
    Near real-time surveillance instead of periodic review.

    The techniques

    Signal Detection Methods

    Finding a genuine safety signal in a sea of reports takes statistical rigor. These are the workhorse methods.

    Disproportionality Analysis
    Flag drug-event pairs reported more often than expected, using the PRR and ROR.
    Empirical Bayes (EBGM)
    Shrinkage methods that stabilize signals when the data are sparse.
    Observed-to-Expected
    Compare observed events against an expected background rate.
    Data Mining
    Automated scanning of large safety databases for emerging patterns.
    Temporal & Subgroup Analysis
    Spot signals that emerge over time or in specific populations.
    Machine Learning
    Triage cases and mine unstructured text for adverse events at scale.

    The rules

    The Pharmacovigilance Regulatory Landscape

    Safety surveillance operates inside a global framework of regulators, databases and standards.

    FDA (United States)
    FAERS for adverse-event reports; REMS for risk-management programs.
    EMA (Europe)
    EudraVigilance, the European Union adverse-reaction database.
    WHO
    VigiBase, the global database of individual case safety reports.
    ICH Guidelines
    E2E, E2D and related international pharmacovigilance standards.
    MedDRA
    The standard terminology used to code adverse events consistently.
    Periodic Safety Reports
    PSUR and PBRER summarize a product’s evolving benefit-risk profile.

    The hard parts

    Challenges in Real-World Pharmacovigilance

    Real-world safety data is powerful but messy. Knowing the challenges, and how teams address them, is what keeps surveillance credible. These are the recurring ones, debated at RWE Connect 2026.

    Under-ReportingSpontaneous reports capture only a fraction of events. Real-world data and active surveillance widen the net.
    Signal-to-NoiseMost flags are false positives. Statistical shrinkage and triage focus attention on real concerns.
    Confounding & CausalityAssociation is not causation. Structured causality assessment and comparators help.
    Data Quality & CodingInconsistent coding obscures signals. MedDRA and NLP bring standardization.
    Duplicate ReportsThe same event reported many times distorts counts. Deduplication cleans the data.
    Alert FatigueToo many low-value alerts overwhelm teams. Prioritization and ML triage cut through.

    The direction of travel

    Where Pharmacovigilance Is Heading in 2026

    Drug safety is being transformed by AI and real-world data. These are the shifts defining modern pharmacovigilance, and the debates on the agenda at RWE Connect 2026.

    Generative AI for Case Processing
    LLMs automating intake, coding and narrative writing, with human oversight.
    Active Surveillance Networks
    Distributed networks such as FDA Sentinel monitoring safety in near real time.
    Real-Time Signal Detection
    Continuous monitoring replacing periodic, retrospective review.
    Predictive Safety
    Machine learning anticipating risks before they surface in reports.
    Data Standards (IDMP & E2B)
    Global harmonization of how safety data is structured and exchanged.
    Patient-Centered Surveillance
    Social listening and patient-reported outcomes broadening the signal base.

    Sponsor RWE Connect 2026

    Meet the Safety and Real-World Evidence Buyers in Boston

    Drug-safety and real-world evidence leaders gather at RWE Connect 2026: 150+ attendees, around 60% at Director or VP level and above.

    Reach the BuyersDrug safety, pharmacovigilance and RWE leaders evaluating partners and platforms.
    Pre-Scheduled 1:1 MeetingsName the buyers you want; the Partnering Lounge books the meetings before the doors open.
    Demos and SpeakingShow your safety and analytics capabilities to the teams who deploy them.

    RWE Connect 2026

    Get the RWE Study Methods Primer

    A plain-English guide to the core RWE methods, including safety surveillance and signal detection. See the methods, then meet the people applying them in Boston.

    • How safety signals are detected
    • The data sources behind pharmacovigilance
    • Where real-world safety is heading in 2026

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      Pharmacovigilance: Common Questions

      What is pharmacovigilance?

      Pharmacovigilance is the science and set of activities related to detecting, assessing, understanding and preventing the adverse effects of medicines and other drug-related problems.

      What is a safety signal?

      A safety signal is information that suggests a possible new causal association, or a new aspect of a known association, between a medicine and an adverse event, warranting further investigation.

      What is signal detection?

      Signal detection is the process of identifying potential safety signals from data sources such as spontaneous adverse-event reports, electronic health records, claims and the medical literature.

      How does real-world data support pharmacovigilance?

      Real-world data broadens and speeds up safety surveillance beyond spontaneous reporting, using electronic health records, claims and AI or NLP to enable near real-time, continuous monitoring.

      What is FAERS?

      FAERS is the FDA Adverse Event Reporting System, a database of adverse-event and medication-error reports. VigiBase is the equivalent global database maintained by the WHO.

      How is AI used in pharmacovigilance?

      AI is used for natural language processing on unstructured records, automating case intake and processing, and improving signal detection at scale.

      What is disproportionality analysis?

      A statistical method that flags drug-event pairs reported more often than expected across a safety database, using measures such as the proportional reporting ratio (PRR) and reporting odds ratio (ROR).

      What regulations govern pharmacovigilance?

      Requirements from the FDA, the EMA (through EudraVigilance), the WHO and ICH guidelines such as E2E govern how adverse events are collected, assessed and reported.

      What is a PSUR?

      A Periodic Safety Update Report (PSUR, now often a PBRER) is a regular report summarizing a medicine’s worldwide safety data and benefit-risk balance.

      When and where is RWE Connect 2026?

      14 to 15 October 2026 at the Hampton Inn by Hilton, Boston Seaport District, Boston, MA.

      What is signal validation?

      Confirming that a detected signal reflects a genuine safety concern rather than statistical noise or a data artefact, before it is escalated for full assessment.

      What is causality assessment?

      Evaluating whether a medicine likely caused an adverse event, using structured frameworks such as the WHO-UMC system or the Naranjo scale.

      What is active surveillance?

      Proactively monitoring defined data sources, such as the FDA Sentinel system, for safety signals, rather than waiting for spontaneous reports to arrive.

      What is the difference between a PSUR and a PBRER?

      Both are periodic safety reports. The PBRER is the ICH-harmonized format that emphasizes an integrated benefit-risk evaluation, and it has largely replaced the older PSUR.

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