The transfer of product data into EMA’s Product Management Service (PMS) is rightly regarded as a major milestone for pharmaceutical companies. It represents the culmination of months or even years of preparation, mapping, and technical migration activities. However, reaching this point does not mean the task is complete. In reality, the work is only half done once the migration is executed.
Post-migration analysis becomes the decisive phase. Raw records cannot simply be accepted at face value; they must be thoroughly scrutinized to confirm accuracy, consistency, and compliance with EMA requirements.
Quality checks at this stage are crucial for identifying issues such as incomplete fields, formatting errors, misaligned product hierarchies, or legacy data that no longer aligns with the current regulatory framework. Without this step, organizations risk submitting data sets that are not publication-ready, creating bottlenecks in their regulatory workflows.
In short, data migration to PMS should not be seen as an endpoint but rather as a transition into a new phase of responsibility. Ensuring that migrated information is both reliable and ready for regulatory use is critical. Only through systematic validation and quality control can companies transform a technical transfer into a compliant and business-ready asset.
Understanding PMS Data Migration in Pharma
PMS, or Product Management Service, is EMA’s centralized database designed to harmonize and streamline product-related information across the European regulatory network. Its implementation is closely tied to the Identification of Medicinal Products (IDMP) standards, which aim to improve the quality, transparency, and interoperability of product data submitted by pharmaceutical companies.
Migrating to PMS involves transferring large volumes of structured data from legacy sources such as the extended EudraVigilance Medicinal Product Dictionary (xEVMPD), in-house regulatory databases, and other product information repositories. This process is far more than a technical exercise. It is a regulatory requirement that ensures product data is accurate, consistent, and available to stakeholders across the supply chain.
For companies, the migration marks an opportunity to strengthen data governance. It forces organizations to confront inconsistencies, fill in gaps, and align legacy records with modern data models that are increasingly scrutinized during regulatory submissions and inspections.
Properly executed, PMS data migration not only helps meet compliance obligations but also lays the groundwork for efficiency in variations, renewals, and other regulatory activities.
However, this transition requires a disciplined approach. Without robust preparation and follow-up analysis, migrated records may contain hidden errors or structural weaknesses that undermine their usability. Recognizing PMS data migration as both a regulatory obligation and a strategic opportunity is the first step toward ensuring lasting value from the process.
Why Post-Migration Analysis Is Essential
Even when a migration project appears to have gone smoothly, the real test comes afterward. Regulators will not evaluate the quality of your migration process; instead, they will assess your submission based entirely on the quality of the data that resides in PMS.
If errors, omissions, or inconsistencies remain in the system, these shortcomings will surface during regulatory review, regardless of how carefully the migration was executed.
This is why a structured post-migration analysis is indispensable. It enables organizations to move beyond the technical success of transferring records and focus on the regulatory compliance of the data itself. A focused analysis helps you to:
- Detect critical gaps before submissions fail or regulator queries arise
- Build confidence that mandatory fields and controlled terms are correctly populated
- Protect efficiency by avoiding rework across labeling, lifecycle, and change processes
- Demonstrate readiness to regulators with clear evidence of validation
Ultimately, post-migration analysis is not a remedial exercise but a proactive safeguard. It ensures that the data you rely on for regulatory submissions is reliable, consistent, and inspection-ready, transforming migration from a one-off transfer into a foundation for long-term compliance.
Core Areas to Analyze in PMS
For portfolios under 500 records, companies can take a very targeted approach to post-migration validation. By focusing on the areas regulators scrutinize most closely, you can resolve issues before they impact submissions. Below are the six core areas that deserve systematic attention.
| Area | Common Issues | Practical Check (Excel or Tool) |
|---|---|---|
| Completeness of Mandatory Fields | Missing substance name, MA number | Use filters or conditional formatting to flag blanks |
| Controlled Vocabulary Alignment | Non-SPOR terms, typos | Lookup against SPOR reference lists |
| Referential Integrity | Orphaned pack records | Use pivot tables to find missing parent links |
| Identifiers and Traceability | Duplicates or missing IDs | Apply “Remove Duplicates” and pivot summaries |
| Duplicates/Near-Duplicates | Same product with minor variations | Create concatenated key (Name+MA+Pack) |
| Regulatory Status Accuracy | Wrong lifecycle (e.g., “Authorized” vs “Withdrawn”) | Cross-verify with internal tracking systems |
Completeness of Mandatory Fields
EMA expects every product record to contain all required PMS and IDMP attributes. Missing values can prevent records from being published or trigger additional regulator queries.
- Confirm that all records include key fields such as substance name, dosage form, marketing authorization (MA) number, and pack size.
Tip: Use Excel filters or conditional formatting to flag blanks in mandatory columns.
Controlled Vocabulary Alignment
PMS fields linked to EMA reference lists (SPOR) must exactly match the allowed values. Even minor deviations, such as free text or spelling variation,s will cause rejection.
- Validate that dose form, unit of measurement, and country codes follow EMA standards.
Tip: Run a lookup in Excel against the SPOR lists to catch mis-typed or non-standard entries.
Referential Integrity
PMS data must maintain valid parent-child relationships. Orphan records, such as a pack configuration without a linked product, undermine both compliance and traceability.
- Check that each product is correctly linked to its substances, packs, and marketing authorization records.
Tip: Use relational checks or pivot tables to identify records without valid connections.
Identifiers and Traceability
Regulators rely on unique identifiers to confirm audit trails and traceability. Duplicate or missing IDs make it difficult to reconcile product histories.
- Verify the uniqueness of product IDs, MA numbers, and migration timestamps.
Tip: Apply Excel’s “Remove Duplicates” or create pivot checks to confirm one-to-one uniqueness.
Duplicates and Near-Duplicates
Conflicting records in PMS create ambiguity during review and can delay the acceptance of submissions.
- Look for repeated combinations of product name, MA number, and strength or pack size.
Tip: Create a concatenated key (e.g., product name + MA number + pack size) to reveal duplicate entries.
Regulatory Status and Lifecycle Accuracy
Lifecycle information is critical for compliance. Incorrect statuses such as “authorized,” “withdrawn,” or “suspended” are frequent rejection points and undermine regulatory trust.
- Ensure that statuses are accurate and aligned with the company’s regulatory tracking system.
Tip: Cross-verify statuses with internal systems before finalizing records in PMS.
Practical Ways to Run the Checks
Effective validation of migrated PMS data does not always require sophisticated software or complex programming. With a simple Excel or CSV export, you can carry out meaningful checks that highlight the majority of issues regulators will flag.
The goal is not to build a perfect system but to surface the most common and high-risk errors quickly so that they can be corrected before submission.
- Pivot Tables – Summarize records and instantly count where mandatory values are missing. This provides a quick overview of completeness across the portfolio.
- Lookup Functions (VLOOKUP or XLOOKUP) – Compare migrated fields against official SPOR reference lists to ensure that controlled terms are used exactly as required.
- Sorting and Filtering – Spot duplicates, near-duplicates, or anomalies by ordering key fields such as product name, MA number, or pack size.
- Manual Spot-Checks – Select 10 to 20 records at random and compare them directly against the source documents. This reassures you that the migration process preserved accuracy at the individual record level.
Even these straightforward reviews can uncover the “top 10 issues” that are most likely to cause regulatory queries. Having a focused and actionable list not only speeds up remediation but also provides a clear narrative of data quality efforts that can be presented during inspections.
| Issue Type | Example | Regulatory Impact | Mitigation |
|---|---|---|---|
| Missing mandatory fields | No pack size entered | Record not publishable | Complete missing entries |
| Incorrect SPOR term | “Tab.” instead of “Tablet” | Rejection by PMS | Align to controlled list |
| Duplicate product entries | Two MAs for same product | Confusion during submission | Merge and revalidate |
| Outdated lifecycle | “Authorized” product already withdrawn | Compliance gap | Synchronize with internal DB |
| Orphan link | Pack without parent product | Traceability issue | Re-link to valid product ID |
Prioritizing Fixes
When timelines are tight, it is unrealistic to expect every data issue to be corrected at once. Instead, companies should apply a risk-based approach that focuses resources where they will have the greatest regulatory and business impact. The goal is to resolve the most critical blockers first, so that submissions can move forward while broader clean-up continues in parallel.
- Submission Blockers – Empty mandatory fields, missing MA numbers, or invalid controlled terms will prevent records from being published in PMS and will stop submissions from proceeding. These should be resolved immediately.
- High-Impact Products – Prioritize corrections for products that represent major markets, high sales, or priority submissions. Delays in these areas can have disproportionate consequences for both compliance and commercial objectives.
- Regulator-Sensitive Fields – Pay particular attention to attributes that EMA reviewers consistently scrutinize, such as dosage form, pack configuration, and product status. Errors here are among the most common causes of rejection.
By addressing these three categories first, organizations can significantly reduce regulatory risk while maintaining momentum for broader data quality initiatives. This staged approach ensures that compliance obligations are met without paralyzing teams under the weight of a complete portfolio clean-up.
Demonstrating Readiness to Regulators
Once data has been validated internally, the next step is to ensure that the effort is transparent and defensible to regulators. EMA does not simply expect companies to submit accurate records; it also expects to see evidence that the data migration and subsequent checks were performed under controlled, documented conditions.
Demonstrating readiness means showing that your organization has treated data migration with the same rigor as any other GxP process.
Documenting Validation Activities
Keep a clear record of every check performed, including the method used, the number of records reviewed, and the issues identified. Even simple tools such as Excel logs or issue trackers can provide valuable documentation when inspectors ask for proof of your process.
Audit Trail Evidence
Ensure that product IDs, timestamps, and reconciliation reports are retained as part of the migration history. These serve as the backbone of traceability, allowing regulators to confirm that the data in PMS matches its source and that no unauthorized changes were made after migration.
Inspection Readiness
Be prepared to explain not only what issues you identified but also how you resolved them. A concise narrative—“we ran completeness checks, identified 40 missing MA numbers, corrected them, and revalidated the dataset”—gives regulators confidence that you maintain control over your data.
Cross-Functional Oversight
Involve both Quality Assurance and Regulatory Affairs in the validation process. Their participation demonstrates that migration is not treated as an isolated IT exercise but as a business-critical activity embedded in the company’s quality system.
By combining thorough validation with transparent documentation, companies can approach inspections with confidence. Readiness is not only about having clean data, but also about demonstrating how that state of compliance was achieved and maintained.
FAQ
What is the Difference Between PMS and xEVMPD?
PMS is designed to replace xEVMPD by offering a more robust, IDMP-compliant structure for product data. Unlike xEVMPD, PMS allows for richer product hierarchies and greater interoperability with global systems. The transition also aligns better with EMA’s long-term digitalization strategy.
How Does PMS Link to SPOR Services?
PMS relies on SPOR (Substance, Product, Organisation, Referential) data services for controlled vocabularies and identifiers. This ensures consistency across regulatory submissions. Any misalignment between PMS and SPOR can lead to rejection or delays.
What Metrics Can Be Used to Monitor Migration Success?
Metrics include the percentage of complete mandatory fields, the number of duplicates removed, alignment with SPOR lists, and resolution time for identified issues. Tracking these metrics provides management with visibility into progress and residual risk.
How Does PMS Migration Impact Global Submissions?
Although PMS is an EMA system, global regulators increasingly expect IDMP-aligned data. Migrating to PMS improves readiness for multi-region submissions by aligning product data to internationally accepted standards.
How Does PMS Migration Interact with Electronic Submissions (eCTD)?
eCTD submissions often draw on product data maintained in PMS. Poor-quality PMS data can therefore cause inconsistencies in dossiers and delay approvals.
What Is the Link Between PMS and Pharmacovigilance Reporting?
Accurate PMS data supports pharmacovigilance by ensuring that safety reports are linked to the correct product records. Errors in PMS can create mismatches in safety case reporting.
Closing Thoughts
Analyzing your migrated PMS data is less about perfection and more about fitness for purpose: ensuring that regulators receive accurate, consistent, and complete product information. For organizations with smaller datasets, this is a manageable task — one that can be accomplished with disciplined checks in familiar tools like Excel.
The key is to treat analysis as a structured step in your migration journey, not an afterthought. Done well, it accelerates submissions, reduces back-and-forth with regulators, and sets the foundation for long-term IDMP compliance.
