The Study Data Tabulation Model provides the fundamental standard for organizing and formatting clinical trial data for regulatory submission, specifying how raw data from clinical trials should be structured to facilitate regulatory review and analysis. SDTM defines a series of domain models that correspond to different types of observations collected in trials, including demographics, adverse events, concomitant medications, laboratory results, vital signs, and efficacy assessments. Each domain has defined variables with standardized names, labels, and formats, ensuring consistency across studies and sponsors.

The SDTM framework organizes domains into classes based on the type of observation they represent. Interventions domains capture information about treatments administered, including exposure to the study drug and concomitant medications. Events domains document discrete occurrences such as adverse events and protocol deviations. Findings domains contain quantitative or qualitative results from planned evaluations like laboratory tests, vital signs, and efficacy assessments. Special purpose domains address specific data types such as demographics, comments, and subject elements. This classification provides a logical structure that facilitates consistent data organization.

Implementing SDTM requires mapping source data collected in the study database to the standardized SDTM structure, a process that involves transforming variable names, values, and formats to conform to the standard. CDISC provides detailed implementation guides specifying the requirements for each domain, including required variables, expected controlled terminology, and documentation standards. The FDA requires SDTM format for most clinical data submissions and provides technical specifications and validation tools to verify compliance. Sponsors must maintain documentation of the mapping between source data and SDTM datasets, typically in the form of annotated CRFs and define files.

The Study Data Tabulation Model provides the fundamental standard for organizing and formatting clinical trial data for regulatory submission, specifying how raw data from clinical trials should be structured to facilitate regulatory review and analysis. SDTM defines a series of domain models that correspond to different types of observations collected in trials, including demographics, adverse events, concomitant medications, laboratory results, vital signs, and efficacy assessments. Each domain has defined variables with standardized names, labels, and formats, ensuring consistency across studies and sponsors.

The SDTM framework organizes domains into classes based on the type of observation they represent. Interventions domains capture information about treatments administered, including exposure to the study drug and concomitant medications. Events domains document discrete occurrences such as adverse events and protocol deviations. Findings domains contain quantitative or qualitative results from planned evaluations like laboratory tests, vital signs, and efficacy assessments. Special purpose domains address specific data types such as demographics, comments, and subject elements. This classification provides a logical structure that facilitates consistent data organization.

Implementing SDTM requires mapping source data collected in the study database to the standardized SDTM structure, a process that involves transforming variable names, values, and formats to conform to the standard. CDISC provides detailed implementation guides specifying the requirements for each domain, including required variables, expected controlled terminology, and documentation standards. The FDA requires SDTM format for most clinical data submissions and provides technical specifications and validation tools to verify compliance. Sponsors must maintain documentation of the mapping between source data and SDTM datasets, typically in the form of annotated CRFs and define files.