Differences in Data Quality Checks Between FDA and PMDA
Introduction
Submitting SDTM datasets to regulatory authorities like the FDA (U.S. Food and Drug Administration) and PMDA (Japan's Pharmaceuticals and Medical Devices Agency) involves rigorous data quality checks. While both agencies adhere to CDISC standards, their submission guidelines and expectations differ in certain aspects. This blog explores the key differences in data quality checks for FDA and PMDA submissions.
Similarities in Data Quality Checks
Both FDA and PMDA share several common expectations for SDTM datasets:
- Adherence to CDISC Standards: Both agencies require compliance with the SDTM Implementation Guide (SDTM-IG).
- Controlled Terminology (CT): Variables such as AEDECOD and LBTESTCD must align with CDISC CT.
- Traceability: Ensures that derived datasets and analysis results can be traced back to the raw data.
- Define.xml Validation: Both agencies expect a complete and validated Define.xml file for metadata documentation.
Differences in Data Quality Checks
The FDA and PMDA have distinct preferences and requirements that need careful attention.
Aspect-wise Comparison
| Aspect | FDA | PMDA |
|---|---|---|
| Validation Tools |
Primarily uses Pinnacle 21 Community or Enterprise for validation. Emphasis on "Reject" and "Error" findings. |
Relies on Pinnacle 21, but PMDA-specific validation rules are stricter. Additional checks on Japanese language and character encoding (e.g., UTF-8). |
| Validation Rules |
Focuses on U.S.-specific regulatory rules. Requires adherence to SDTM-IG versions commonly used in the U.S. |
Requires alignment with Japanese-specific validation rules. More emphasis on Trial Summary (TS) and demographic consistency. |
| Trial Summary (TS) Domain | FDA expects a complete TS domain but is less stringent on content beyond mandatory fields. | PMDA places greater importance on the TS domain, especially for regulatory codes specific to Japan. |
| Japanese Subjects | Less emphasis on Japanese-specific requirements. | Requires additional checks for Japanese subjects, such as proper handling of kanji characters. |
1. Data Validation and Tools
FDA:
- Relies on specific validation tools like Pinnacle 21 Community/Enterprise to check data compliance.
- FDA has stringent validator rules listed in their Study Data Technical Conformance Guide.
- Focus is on ensuring conformance to CDISC standards such as SDTM, ADaM, and Define.xml.
PMDA:
- Uses a custom validation framework with a focus on Study Data Validation Rules outlined in PMDA guidelines.
- PMDA also emphasizes conformance but requires additional steps for documenting electronic data submissions.
2. Submission File Formats and Organization
FDA:
- Requires datasets in SAS Transport Format (.xpt).
- Submission files need to adhere to the eCTD format.
- Technical specifications like split datasets (e.g., DM datasets with large record counts) need clear organization.
PMDA:
- Aligns with the same .xpt requirement but often asks for additional metadata and dataset-specific documentation.
- Detailed instructions on submission through the PMDA Gateway System.
- PMDA requires notification submissions and extensive Q&A clarifications on data contents.
3. Controlled Terminologies and Dictionaries
FDA:
- Requires compliance with the latest MedDRA and WHODrug versions.
- MedDRA coding consistency is emphasized for all terms and values.
PMDA:
- Accepts MedDRA and WHODrug but requires detailed mapping between collected data and coded terms.
- Has additional checks for Japanese coding conventions and translations.
4. Define.xml
FDA:
- Emphasizes alignment between dataset variables, labels, and metadata.
- Requires accurate representations of origins (e.g., CRF, Derived).
PMDA:
- Additional scrutiny on variable origins and alignment with Japanese electronic standards.
- PMDA often requires clarifications for variables derived from external sources or referenced across multiple studies.
5. Reviewer’s Guides (cSDRG and ADRG)
FDA:
- Provides guidance through templates like the cSDRG and ADRG.
- Focus on study-level explanations for data inconsistencies, derivations, and non-standard elements.
PMDA:
- Requires more detailed explanations in cSDRG and ADRG, especially regarding:
- Variables annotated as Not Submitted.
- Handling of adjudication or screen failure data.
6. Data Quality Focus
FDA:
- Prioritizes ensuring datasets conform to the FDA Technical Specifications.
- Consistency across study datasets within a submission is critical.
PMDA:
- Prioritizes consistency between variables and detailed documentation of derivations.
- More focused on mapping between raw data and analysis-ready datasets.
7. Study Tagging Files (STF)
FDA:
- Requires STF to categorize and link datasets, programs, and metadata documents in the submission.
PMDA:
- Similar to the FDA but emphasizes alignment between the STF and Japanese Gateway system submission requirements.
Regulatory Submission Context
Historical Context: The FDA and PMDA have embraced CDISC standards to enhance global harmonization, ensuring data transparency and reproducibility in clinical trials.
Key Objectives: Both agencies aim to ensure data integrity, accuracy, and traceability, facilitating efficient review processes and better regulatory oversight.
Specific Guidance from FDA and PMDA
FDA: The FDA emphasizes adherence to the Study Data Technical Conformance Guide and Data Standards Catalog to align submissions with their expectations.
PMDA: PMDA focuses on their Notifications on Electronic Study Data and their FAQs for addressing specific queries regarding Japanese regulatory requirements.
Operational Challenges
- Language Considerations: Handling multi-language data, such as English and Japanese, introduces encoding and translation challenges, particularly for kanji characters.
- Validation Tools Usage: Differences in Pinnacle 21 Community vs. Enterprise versions can create discrepancies in validation reports.
Lessons from Common Errors
Data Compliance Errors: Issues such as incomplete Define.xml, inconsistent controlled terminology, and incorrect TS domain entries are common pitfalls.
Mitigation Strategies: Conduct comprehensive pre-submission reviews, cross-checking both FDA and PMDA guidelines to preempt rejections.
Summary of Key Considerations
| Aspect | FDA | PMDA |
|---|---|---|
| Validation Tools | Pinnacle 21 | PMDA-specific validation rules |
| Submission System | eCTD | PMDA Gateway |
| Focus | Conformance to CDISC Standards | Metadata and mapping clarifications |
| Dictionaries | MedDRA/WHODrug | MedDRA/WHODrug + Japanese translations |
| Define.xml | Focus on CRF origins and labels | Additional variable origin documentation |
| Reviewer’s Guide | General inconsistencies and derivations | Non-standard elements and adjudication |
Conclusion
While FDA and PMDA share a common foundation in CDISC standards, their data quality expectations have nuanced differences. Understanding these distinctions is critical for ensuring smooth submissions. By tailoring your SDTM programming and validation processes to address these unique requirements, you can enhance your submission success rate and streamline regulatory review.
