Pharmacovigilance depends on the quality of the information used to understand the safety of medicines. For Marketing Authorisation Holders (MAHs), that information comes from multiple sources, including spontaneous reports, clinical studies, medical information enquiries, product complaints, patient support programmes, local affiliates and external service providers. Each source has a role in identifying potential safety concerns, but the information they collect must reach the appropriate pharmacovigilance process and remain traceable throughout its lifecycle.
A suspected adverse reaction may be recorded by a local affiliate but not transferred to the global safety database. A clinical study record may have no corresponding safety case. A vendor may report that data have been transferred successfully, even though some records remain unprocessed or cannot be matched to the receiving system. These issues are not always immediately visible. They may only become apparent when records are compared, reporting histories are reviewed or a quality investigation identifies an unexplained difference.
Pharmacovigilance data reconciliation helps MAHs identify these discrepancies before they undermine the completeness, consistency or traceability of safety information. Its purpose extends beyond matching records that each difference must be assessed, its cause understood, and the appropriate resolution documented. For organisations managing products across several markets, effective reconciliation also supports oversight of affiliates, vendors and other partners involved in safety-data collection and exchange.
What is Pharmacovigilance Data Reconciliation and Why Does it Matter?
Pharmacovigilance data reconciliation is a documented process of comparing safety-related records held in different systems, databases or source logs to identify missing information, inconsistencies, duplicate records and unexplained differences. The comparison may involve a clinical database and a safety database, an affiliate intake log and a global pharmacovigilance system, or a vendor’s transfer records and the receiving organisation’s icsr case-management records. The scope depends on the data flow, applicable regulatory requirements and the organisation’s procedures.
An effective process helps MAHs:
- Identify safety reports that have not reached the intended system.
- Detect incomplete transfers and inconsistencies between records.
- Investigate unexplained differences in case identifiers, status and relevant data fields.
- Monitor reporting and transmission issues that may require escalation.
- Establish accountability for discrepancy resolution and corrective action.
- Maintain evidence that reconciliation activities were completed and reviewed.
Safety data reconciliation is not a substitute for case processing, medical assessment, duplicate management or regulatory reporting. Nor does every unmatched record represent a compliance failure. Systems may use different identifiers, maintain different data fields or apply different inclusion criteria.
For MAHs, the value lies in making the safety-data lifecycle more transparent. Records can be traced from their source through transfer, processing and reporting, while unresolved exceptions remain visible until an appropriate outcome has been established.
Where do Pharmacovigilance Data Gaps Begin?
Safety-data gaps often develop at the points where information moves between teams, systems or organisations. Understanding these interfaces is essential because correcting an individual record may not address the process failure that caused it.
| Where Gaps Begin | How They Occur | Potential Impact |
|---|---|---|
| Fragmented Intake | Safety information is missed or not escalated. | Missing safety records. |
| Inconsistent Identifiers | Systems use different IDs or matching rules. | Unmatched or incorrectly linked cases. |
| Incomplete Transfers | Interface, upload or mapping errors interrupt data flow. | Missing or inaccurate records. |
| Unclear Responsibilities | Teams lack clear transfer and escalation ownership. | Delayed or overlooked reports. |
| Weak Exception Management | Discrepancies lack owners or closure criteria. | Unresolved or recurring issues. |
| System and Source Changes | Migrations, vendor changes or new channels introduce risks. | Existing controls may miss discrepancies. |
These causes require different responses. A mapping issue may need a technical correction, while a missed report may require immediate case assessment, reporting-impact evaluation and a quality investigation. Repeated failures may indicate a broader procedural or governance weakness.
What Types of Safety Data Gaps Should MAHs Look For?
A useful reconciliation process identifies discrepancies that may affect case completeness, data accuracy, reporting timelines or the reliability of safety assessments.
- Missing or unprocessed safety cases: Relevant source reports are absent from the receiving database, with no documented explanation.
- Incomplete or inconsistent case information: Records differ in key fields, such as product details, event dates, seriousness or case status.
- Duplicate or incorrectly linked records: Reports are duplicated, or follow-up information is linked to the wrong case.
- Unresolved follow-up information: Additional information is missing from the corresponding safety case.
- Reporting and acknowledgement discrepancies: Regulatory submissions lack confirmation or show transmission failures or rejections.
- Unexplained differences in record counts: Source and receiving systems show different totals that require investigation.
- Untraceable records: Records lack a clear source link or documented processing history.
Clinical and Safety Database Reconciliation: Where the First Major Gap Can Appear
Clinical safety processes often involve multiple databases and reporting responsibilities. Serious adverse events (SAEs) recorded during a clinical study may be maintained in a clinical data-management system, while individual case safety reports (ICSRs) are processed in a pharmacovigilance safety database.
Clinical safety data reconciliation commonly involves checking relevant SAE records against corresponding safety database cases to identify missing records, inconsistent information and incomplete transfers.
The process should establish whether:
- Relevant SAE records have corresponding safety database records.
- Matching identifiers and mapping rules reliably link records across systems.
- Differences in event details, dates, seriousness and case status have been assessed.
- Follow-up information has been transferred and incorporated where appropriate.
- Required processing and reporting activities have been completed within applicable timelines.
- Unresolved discrepancies have an owner, an investigation outcome or a defined next action.
Not every adverse event recorded in a clinical study is an SAE, and not every SAE automatically constitutes an individually reportable ICSR under every reporting pathway. Clinical-trial reporting requirements, seriousness, expectedness, causality and other applicable criteria must be considered according to the relevant rules and procedures.
Practical example
A clinical database contains an SAE record associated with a study participant. During reconciliation, the record cannot be matched to a safety database case. The team should first verify the source identifier, study details, relevant dates and matching criteria. It should then investigate whether the report was transferred, whether it exists under a different identifier, or whether a technical or procedural failure prevented processing. If a required safety case is missing, the responsible team must assess the applicable reporting obligations and act without unnecessary delay. Any potential missed deadline should be evaluated and handled under the organisation’s procedures.
The discrepancy should only be closed once the investigation and required actions are documented, the relevant records have been reconciled or an appropriate explanation has been approved, and any necessary corrective action has been completed or tracked through the applicable quality process. This approach turns reconciliation into a meaningful control rather than a comparison exercise that simply produces a list of unmatched records.
How Affiliate, Vendor and Partner Data Creates Global Reconciliation Risk
For MAHs operating in several countries, safety information often passes through a network of local affiliates, distributors, medical information providers, patient support programme operators and pharmacovigilance vendors before reaching the relevant global systems. Each handoff introduces a potential point of failure. A report may be received locally but transferred late, recorded under a different identifier, excluded from an expected data feed or left without a documented downstream outcome.
Global pharmacovigilance reconciliation should therefore address both the quality of individual records and the reliability of the proc Official regulatory references esses through which information moves between stakeholders.
Contracts and safety data exchange agreements establish responsibilities, but they do not by themselves demonstrate that the process is working. MAHs need evidence of actual transfers, reconciliation outcomes and appropriate follow-up. A central safety database can provide a consolidated view of cases, but it cannot compensate for information that never reaches the system. Effective oversight must extend to the interfaces between the database and the organisations that supply safety information.
What ICH E2D(R1), E2B(R3) and EudraVigilance Changes Mean for Reconciliation
Reconciliation procedures should reflect the applicable regulatory requirements and the technical standards used to collect, exchange and report safety information. Three developments are particularly relevant to MAHs operating in the European Union and other ICH regions.
- ICH E2D(R1): Post-Approval Safety Information and Evolving Data Sources
ICH E2D(R1) was adopted on 15 September 2025 and became effective in the EU on 18 March 2026. It updates post-approval ICSR reporting guidance, including considerations for evolving safety-information sources. MAHs should review source inventories, intake procedures and transfer controls to ensure relevant channels are covered. Not every item received qualifies as a valid ICSR; applicable reporting criteria must still be assessed. - ICH E2B(R3): Electronic Case Exchange and Data Consistency
ICH E2B(R3) defines data and message requirements for electronic ICSR exchange. Since 30 June 2022, applicable EU submissions have used the ISO ICSR/E2B(R3) format. Reconciliation should verify case identifiers, required data, terminology, transmission status and regulatory acknowledgements. Generated messages do not guarantee successful submission or acceptance. MAHs should also monitor regional implementation updates, including changes related to the revised E2D(R1) framework. - EudraVigilance: Data Quality and Reporting Timelines
The EMA uses validation, verification and duplicate-management processes to support EudraVigilance data quality. Since September 2025, automated monthly compliance reports have helped monitor applicable ICSR and SUSAR reporting timelines. MAHs should maintain traceable submission records and investigate discrepancies in case status, transmission history and acknowledgements. Reconciliation supports oversight but does not replace legal reporting obligations. Timelines vary by report type, product, jurisdiction and reporting pathway.
How MAHs Can Build an Effective PV Reconciliation Process
An effective reconciliation process needs more than a schedule and a comparison report. It should define the records being compared, the criteria for identifying discrepancies, the responsibilities for investigating them and the evidence required for closure.
The PV Data Reconciliation Process:
| Step | Control | Key Actions |
|---|---|---|
| 1 | Define Scope | Identify sources, data flows and requirements. |
| 2 | Match Records | Set matching rules and identifiers. |
| 3 | Set Frequency | Schedule risk-based checks and escalate urgent issues. |
| 4 | Investigate Gaps | Identify causes and assess reporting impact. |
| 5 | Take Corrective Action | Assign owners, actions and deadlines. |
| 6 | Verify Closure | Confirm resolution and retain evidence. |
| 7 | Monitor and Improve | Track recurring issues and assess CAPA effectiveness. |
Automation can improve efficiency by identifying mismatches, tracking open exceptions and producing reconciliation reports. However, its reliability depends on validated systems where required, accurate source data, appropriate matching logic and effective oversight. Human review remains important when records are ambiguous or a decision requires pharmacovigilance judgement.
The PV Data Reconciliation Control Framework
A structured control framework connects individual reconciliation activities with the wider pharmacovigilance quality system. It should provide evidence not only that comparisons were completed, but also that discrepancies were investigated and appropriate outcomes were documented.
- Control 1 – Source completeness verify that all expected sources, records and periods are included.
- Control 2 – Matching and exception detection Identify missing, duplicate, incomplete or inconsistent records.
- Control 3 – Risk-based investigation Assess discrepancies and promptly escalate high-risk issues.
- Control 4 – Accountability and resolution Assign owners, deadlines and documented corrective actions.
- Control 5 – Evidence and audit trail Retain comparison results, investigation records and closure evidence.
- Control 6 – Effectiveness monitoring Track recurring issues and verify corrective-action effectiveness.
Key Performance Indicators (KPIs):
- Reconciliation completion rate.
- Number and age of open discrepancies.
- Time to resolve high-risk exceptions.
- Recurring discrepancy frequency.
- Corrective-action effectiveness.
The framework should also define how reconciliation findings enter the quality-management system. Significant issues may require deviation management, CAPA, vendor escalation, procedural revision or system remediation, depending on the investigation and applicable requirements.
For MAH pharmacovigilance teams, the ultimate objective is a controlled process that makes gaps visible, establishes accountability and demonstrates that safety information has been appropriately managed.
How DDReg Supports Pharmacovigilance Data Quality
Reliable pharmacovigilance depends on well-defined processes, clear responsibilities and documented quality controls. For organisations reviewing their existing arrangements, DDReg can be a relevant partner in evaluating regulatory and pharmacovigilance processes, identifying control gaps and strengthening compliance-focused documentation, subject to the services confirmed for the engagement.
For MAHs, the priority is to establish a reconciliation approach that fits their operating model, covers relevant data sources and supports effective oversight of internal teams and external partners.
DDReg’s broader pharmacovigilance and regulatory expertise can help organisations assess their requirements and identify where process improvements may be needed.
Conclusion
Pharmacovigilance data reconciliation is an important control for maintaining complete, consistent and traceable safety information throughout a medicine’s lifecycle. Its effectiveness depends on what happens after a discrepancy is identified: the cause must be investigated, the potential impact assessed, the appropriate action completed and the outcome documented. For MAHs, this requires clear source ownership, reliable matching criteria, timely escalation and evidence-based oversight. These controls become especially important when safety information moves between clinical systems, local affiliates, external vendors and global databases.
Regulatory and technical changes make ongoing review equally important. Procedures should reflect applicable requirements, current system implementations and the organisation’s actual safety-data flows. A mature reconciliation process does not simply confirm that two databases have been compared. It demonstrates that relevant differences have been understood, genuine gaps have been addressed, and recurring failures are being reduced.
Frequently Asked Questions
The frequency should be defined in controlled procedures according to the data source, applicable regulatory requirements, reporting timelines and risk. There is no single universal frequency that applies to every reconciliation activity. Potentially urgent safety or reporting discrepancies should be escalated as soon as they are identified.
No. ICSR processing includes activities such as case validation, data entry, medical assessment and regulatory reporting. Safety data reconciliation compares records across sources or systems to identify omissions and inconsistencies. Both support ICSR data quality, but reconciliation does not replace case processing or reporting.
Clinical safety data reconciliation commonly compares relevant clinical-study records, such as SAEs, with corresponding pharmacovigilance safety database records. Global pharmacovigilance reconciliation has a broader scope and may cover affiliate intake logs, medical information, vendors, distributors and other safety-data sources across markets. The exact scope depends on the organisation's documented procedures and applicable requirements.
MAHs should retain evidence of the original discrepancy, the investigation, the decision and the action taken. Closure should be supported by a corrected or appropriately reconciled record, an approved justification where necessary, and verification that the action achieved its intended outcome. Significant or recurring issues may also require documented CAPA and effectiveness checks.