Upcoming Public Training Opportunities:
The Study Data Tabulation Model (SDTM) is a specification for the submission of pre-clinical, clinical and device data to the U.S. Food and Drug Administration in support of marketing applications. The SDTM Implementation Guide for Medical Devices (SDTMIG-MD) is used in conjunction with the SDTM and SDTMIG for Human Clinical Trials to support medical device submissions.
This course combines instruction on using the SDTM IG for Human Clinical Trials (the foundational SDTMIG) and device-specific domains and practices. It uses device-based examples to illustrate the key principles of the SDTM model and implementation guide, and covers the device domains in detail. Device-specific implementations of some core domain, such as AEs, are also included.
Topics covered in the two-day SDTM for Medical Devices course focus on subject-related data and device data, and include:
Exercises are included in numerous places to reinforce the material.
The course merges the foundational SDTM two-day course and the Medical Devices ½-day course, and duplicates much of the material in both. Students should take either the two-day medical device SDTM course OR the combination of the two-day SDTM course plus the ½-day devices course, but not all three.
Learning Outcomes for this course include:
At the end of this course, a student will be able to:
Continuing Education Units (CEUs)
Learners will receive 1.4 CEUs for successfully completing this course.
Alternative Option: ½-day SDTM for Medical Devices
This ½-day course focuses almost exclusively on the medical device domains and the associated implementation guide. Topics include:
A case-based, hands-on exercise reinforces the use of the seven device domains. This course does not cover the basics of SDTM, and assumes the student already has this knowledge.
Continuing Education Units (CEUs) for ½-day SDTM for Medical Devices Course
Learners will receive 0.4 CEUs for successfully completing this course.
Successful Course Completion
A basic understanding of clinical data flow and relational database design is helpful but not required.