Every medicine has a story beyond its label—told not just through clinical trials, but also through everyday encounters in clinics, pharmacies, and patient support programs. These stories often emerge as safety reports, the backbone of pharmacovigilance. But not all reports are created—or collected—the same way.
Accurate classification of adverse event (AE) reports is more than a technical requirement—it impacts regulatory reporting timelines, signal detection, and inspection readiness.
This article explains the key differences between solicited and unsolicited reports in pharmacovigilance, includes examples, and highlights how proper categorization improves safety outcomes and audit performance.
What Is an Unsolicited Report?
An unsolicited report is an adverse event report submitted without any prior request, structured program, or formal data collection effort by the marketing authorization holder (MAH).
Examples of unsolicited sources:
- Spontaneous reports from healthcare professionals or patients
- Reports submitted to regulatory authorities (e.g., FDA, EMA & NAFDAC)
- Literature case reports
- Social media or digital platforms
- News articles or legal sources
These reports often emerge unexpectedly and may vary in quality. However, they are essential for signal detection and early risk identification, especially for rare or serious adverse events.
If the report meets the four minimum criteria (identifiable patient, identifiable reporter, suspect drug, and adverse event), it qualifies as a valid Individual Case Safety Report (ICSR) and may trigger expedited reporting timelines, such as 15-day reporting for serious, unexpected AEs.
What Is a Solicited Report?
A solicited report is an adverse event report obtained through an organized, pre-planned data collection system, often supported or initiated by the MAH or sponsor.
Examples of solicited sources:
- Post-authorization safety studies (PASS)
- Patient support programs (PSPs)
- Market research programs (MRPs)
- Non-interventional studies (NIS)
- Disease or drug registries
- Compassionate use or named-patient programs
Unlike unsolicited reports, solicited reports are expected as part of ongoing pharmacovigilance activities. Even if the patient or physician spontaneously mentions an AE, the report is still considered solicited if collected through a structured program.
All solicited reports require medical assessment for causality, and serious cases may still be reportable within expedited timelines if deemed related and unexpected.
Why This Matters in Modern PV Practice
The distinction between solicited and unsolicited reports is increasingly relevant in today's environment of real-world data, digital engagement, and multiple patient access programs. Proper classification ensures:
- Timely regulatory submissions
- Accurate safety signal detection
- Reliable benefit-risk assessments
- Successful inspections by regulatory authorities
Recommendations for PV Specialists
- Establish clear SOPs and training distinguishing solicited vs unsolicited reports across programs
- Validate data source classification during case intake or triage—not after
- Ensure reconciliation between pharmacovigilance and clinical study teams for solicited report tracking
- Implement review audits specifically targeting report-type misclassification, especially in patient support or non-interventional programs.
Real-World Implications in Case Management
In practice, the classification of reports as solicited or unsolicited directly influences how case processors assess seriousness, causality, and expectedness. A report from a non-interventional study (NIS) mistakenly classified as spontaneous might bypass necessary documentation or causality evaluation, leading to potential non-compliance.
This is particularly risky during inspections or audits where documentation trails are scrutinized. Clear documentation of the source and study protocol in solicited reports is critical for audit readiness.
Moreover, solicited reports often follow structured data collection procedures, which can enhance data completeness but also introduce regulatory nuances—especially when study protocols are amended or reporting responsibilities are shared across partners. Inconsistent classification across different markets or affiliates can also complicate the preparation of aggregate reports such as PSURs or PBRERs, where source type matters in trend interpretation and signal detection.
From a quality management perspective, teams should regularly review a sample of incoming reports to verify correct classification and ensure alignment with Standard Operating Procedures (SOPs) and applicable regulatory guidelines. Ultimately, meticulous source documentation not only improves compliance but also strengthens the integrity and credibility of the safety data being used for global pharmacovigilance decisions.
Automated Systems & Artificial Intelligence
As pharmacovigilance adopts more automation and AI-driven case triage, the risk of systematic misclassification increases if data input rules are not properly calibrated. Algorithms relying solely on narrative content or incomplete metadata may misidentify the report type, especially if the source document does not include explicit program information. This highlights the need for continuous quality checks even in semi-automated workflows.
While automation can greatly reduce manual workload and accelerate case processing timelines, it cannot fully replace human judgment—particularly when contextual nuances are involved. For example, differentiating between a PSP report and a true spontaneous report may require a careful review of program intent, consent forms, and sponsor relationships—elements not always visible to an algorithm.
As AI tools become more integrated into PV systems, it is essential to maintain detailed documentation, apply regular audits of classification decisions, and train pharmacovigilance teams on when to override automated outputs.
A hybrid model that blends technology with pharmacovigilance expertise is likely the most reliable path forward.
In a nutshell, Pharmacovigilance depends on precise and consistent safety data. Classifying reports correctly as solicited or unsolicited strengthens signal detection, supports regulatory compliance, and reduces audit risk. As PV professionals, staying alert to the source of reports is just as important as assessing their content.
