T-14: Automate the Process to Ensure the Compliance with FDA Business Rules in SDTM Programming for FDA Submission
Poster Presenter
Xiangchen Cui
Senior Director
Alkermes Inc. United States
Objectives
This paper presents a systematic approach to automate SDTM programming process to ensure compliance with FDA Business Rules for FDA Submission. The sharing is to assist readers to apply it to prepare FDA Business Rule compliant SDTM datasets for technical accuracy and cost-effectiveness.
Method
This process contains study data collection design, data collection (edit-checking), standard SDTM programming process, and in-house macros for automatically reporting and/or fixing the issues to address non-compliance with “FDA Business Rules” in SDTM programming for FDA submission.
Results
Pinnacle 21 is used by both sponsors and FDA to check compliance with both FDA business rules and CDSIC standards. It is a very useful diagnostic tool for detecting and reporting non-compliance issues of study data. Findings that generate “Error” and/or “Warming” messages, can be categorized as either data issues or SDTM mapping issues, and sponsors must either correct the data issues and/or explain discrepancies in the SDRG (Study Data Reviewer’s Guide), or fix SDTM mapping errors before FDA submission. However it cannot help sponsors to automatically resolve the issues of data conformance, even if it is used at the very early stage of SDTM programming development. Furthermore, some of these non-compliant data issues are often very “costly” and/or too late to be fixed at a late stage.
Hence, a proactive approach is warranted for a high quality and cost-effective SDTM programming for preparing FDA submission. This paper presents a systematic approach to automate SDTM programming process to ensure compliance with FDA Business Rules. This paper further explains why this approach is far superior to Pinnacle 21 in ensuring compliance of SDTM data with FDA Business Rules. This systematic approach avoids inefficient use of resources for repeated verification of the compliance and/or resolution of the findings from Pinnacle 21 for these rules. The sharing of hands-on experiences in this paper is to assist readers to apply this methodology to prepare FDA Business Rule compliant SDTM datasets for FDA submission in order to ensure the technical accuracy and submission quality, in addition to cost-effectiveness and efficiency.
Conclusion
This paper presents a systematic approach to automate SDTM programming process to ensure compliance with FDA Business Rules. This systematic approach is composed of these four pillars: study data collection design, data collection (edit-checking), standard SDTM programming process, and in-house. It illustrates how each pillar can help sponsors achieve full compliance of SDTM data with FDA Business rules. It further explains why this approach is far superior to Pinnacle 21 re ensuring compliance of SDTM data with FDA Business Rules. The sharing of hands-on experiences in this paper is to assist readers to apply this methodology to prepare FDA Business Rule compliant SDTM datasets for FDA submission in order to ensure the technical accuracy and submission quality, in addition to cost-effectiveness and efficiency.
