In the world of clinical research, Electronic Data Capture (EDC) systems play a pivotal role in efficiently collecting, managing, and analyzing clinical trial data. Once the data is captured and thoroughly reviewed, it needs to be exported in a standardized format for further analysis and regulatory submissions. The Study Data Tabulation Model (SDTM) is a widely accepted format that ensures consistency and interoperability of clinical trial data. In this blog, we will delve into the process of exporting clinical data in SDTM format from an EDC system.
- Understand SDTM: The SDTM is a data standard developed by the Clinical Data Interchange Standards Consortium (CDISC) that provides a structured format for organizing and submitting clinical trial data. It comprises a set of variables, controlled terminology, and guidelines for data representation. Familiarize yourself with SDTM domains, which include demographics, adverse events, medical history, concomitant medications, laboratory tests, and more.
- Ensure EDC System Compatibility: Before exporting data, ensure that your EDC system supports SDTM export functionality. Most modern EDC systems have the capability to export data in SDTM format or offer plugins/extensions for seamless integration with SDTM conversion tools.
- Define SDTM Mapping: SDTM mapping involves mapping the EDC-specific data elements to their corresponding SDTM variables. This step ensures that the exported data is correctly aligned with the SDTM standards. Create a comprehensive mapping document or utilize CDISC-defined SDTM Implementation Guides (IGs) for consistent mapping.
- Validate and Clean Data: Prior to export, perform thorough data validation and cleaning to ensure data quality and integrity. Implement quality checks, including range validation, missing data checks, and consistency checks, to identify and resolve any anomalies or discrepancies.
- Extract Data from EDC: Using the EDC system’s data export functionality, extract the desired datasets as per the defined SDTM mapping. Typically, EDC systems allow users to select specific time points, subjects, and variables for export. Exported data may be in a raw format (e.g., CSV, Excel) or in a vendor-specific format compatible with SDTM conversion tools.
- Utilize SDTM Conversion Tools: To convert the extracted data into SDTM format, employ SDTM conversion tools or software packages available in the market. These tools typically offer automated mapping capabilities based on SDTM Implementation Guides and allow customization options to accommodate specific study requirements. Popular tools include SAS Clinical Data Integration, OpenCDISC, and Pinnacle 21.
- Validate SDTM Dataset: Once the data is converted to SDTM format, conduct a comprehensive validation to ensure adherence to SDTM standards. Employ CDISC’s validation tools, such as OpenCDISC Validator or Pinnacle 21 Enterprise, to verify compliance with CDISC SDTM rules and guidelines.
- Review and Resolve Discrepancies: Review the SDTM dataset to identify any discrepancies or errors flagged during the validation process. Resolve the identified issues by making necessary corrections or adjustments in the original EDC data or by modifying the SDTM mapping and conversion process.
- Generate Define.xml and Other Required Documentation: Generate Define.xml, which provides metadata information about the SDTM dataset, including variables, structure, and relationships. Additionally, create other required documentation, such as the annotated CRF (a cross-reference between CRF variables and SDTM variables), data integration plan, and data standards catalog.
- Submission and Regulatory Compliance: Once the SDTM dataset and associated documentation are finalized and validated, they are ready for submission to regulatory authorities or for further analysis. Ensure compliance with regulatory requirements, such as those specified by the U.S. Food and Drug Administration (FDA) or the European Medicines Agency (EMA).
Conclusion:
Exporting clinical trial data in SDTM format from an EDC system is a critical step in the data management process. By following the steps outlined above, researchers and data managers can ensure the accurate representation and compliance of their data with industry standards. Efficiently exporting data in SDTM format facilitates streamlined analysis, interoperability, and regulatory submissions, ultimately contributing to the advancement of medical research.
Cloudbyz EDC is a user-friendly, cloud-based solution that is designed to store and manage clinical data effectively throughout a clinical trial’s life cycle. Our innovative solution enables clinical research teams to efficiently collect, analyze, and manage clinical data of different complexity and size. Cloudbyz EDC is a scalable solution and meets all the essential regulatory compliance requirements such as FDA- 21 CFR Part 11, GCP, GAMP5, HIPAA, and EU- GDPR.
To know more about Cloudbyz EDC Solution contact info@cloudbyz.com