Understanding ADAPT in the SDTM TS Domain: Adaptive vs Non-Adaptive Trials Posted by Sarath Annapareddy | May 14, 2025 The Study Data Tabulation Model (SDTM) plays a critical role in organizing and submitting clinical trial data. One of the key parameters regulatory agencies look for in the Trial Summary (TS) domain is the ADAPT parameter ( TSPARMCD=ADAPT ), which identifies whether the trial uses an adaptive design. In this post, we’ll break down what ADAPT really means, when to use TSVAL=Y , and why multiple protocol amendments alone do not make a study adaptive. What is ADAPT in the TS Domain? The ADAPT parameter tells regulators whether the clinical trial used an adaptive design ( TSVAL=Y ) or a non-adaptive (fixed) design ( TSVAL=N ). "Adaptive clinical trials allow for changes in design or hypotheses during the study based on accumulating data, without undermining the validity or integrity of the trial." – FDA Guidance Example 1: Non-Adaptive Trial (...

SDTM Trial Summary Domain: ACTSUB vs Screen Failures Understanding SDTM Trial Summary Domain: ACTSUB vs Screen Failures In the world of clinical data management, the Study Data Tabulation Model (SDTM) plays a vital role in organizing and submitting clinical trial data to regulatory agencies. One of the most essential domains in SDTM is the Trial Summary (TS) domain, which provides key information about the clinical trial itself. In this blog post, we will explore the Actual Number of Subjects (ACTSUB) and how it differs from screen failures. We will also reference regulatory guidelines and SDTM Implementation Guides to ensure a deeper understanding. What is the TS Domain? The Trial Summary (TS) domain contains high-level information about the clinical trial. This includes essential data such as the number of subjects, the start and end dates of the trial, trial objectives, and much more. The TSPARMCD variable define...

Understanding EC vs. EX Domains in SDTM: When to Use Each Understanding EC vs. EX Domains in SDTM: When to Use Each In SDTM, the EC (Exposure as Collected) and EX (Exposure) domains are both used to capture data related to drug or therapy exposure, but they serve different purposes depending on how the exposure data is collected and whether the study is blinded or unblinded. Key Updates from PharmaSUG Papers: PharmaSUG 2017 Paper DS08 introduces the historical context of the EC domain, which was established in SDTMIG v3.2 to support the EX domain by providing detailed traceability for exposure data. EC helps capture deviations, titrations, and other variations from planned dosing, especially when the collected data doesn't match protocol-specified dosing. PharmaSUG 2022 Paper DS121 emphasizes the importance of capturing dose modifications using the EC domain, which often occurs in oncology trials. By utilizing EC, sponsors can accurate...

Study Start Date in SDTM – Why Getting It Right Matters Study Start Date in SDTM – Why Getting It Right Matters The Study Start Date (SSTDTC) is a crucial element in the submission of clinical trial data, especially in meeting regulatory requirements. Since December 2014, the FDA has provided explicit guidance on defining and utilizing this data point, but many sponsors and service providers face challenges in its consistent application. Missteps in defining the Study Start Date can lead to technical rejection during submission reviews, delaying the regulatory process. This article explores the definition, importance, and proper implementation of the Study Start Date in SDTM (Study Data Tabulation Model) submissions, based on regulatory guidance and best practices. FDA’s Definition of Study Start Date The FDA, in its 2014 guidance, clarified that the Study Start Date for clinical trials is the earliest date of informed consent for any subject ...

Best Practices for Joining Additional Columns into an Existing Table Using PROC SQL Best Practices for Joining Additional Columns into an Existing Table Using PROC SQL When working with large datasets, it's common to add new columns from another table to an existing table using SQL. However, many programmers encounter the challenge of recursive referencing in PROC SQL when attempting to create a new table that references itself. This blog post discusses the best practices for adding columns to an existing table using PROC SQL and provides alternative methods that avoid inefficiencies. 1. The Common Approach and Its Pitfall Here's a simplified example of a common approach to adding columns via a LEFT JOIN : PROC SQL; CREATE TABLE WORK.main_table AS SELECT main.*, a.newcol1, a.newcol2 FROM WORK.main_table main LEFT JOIN WORK.addl_data a ON main.id = a.id; QUIT; While this approach might seem straightforward, it leads to a warning: "CREATE T...

Comprehensive SDTM Review Mastering the SDTM Review Process: Comprehensive Insights with Real-World Examples The process of ensuring compliance with Study Data Tabulation Model (SDTM) standards can be challenging due to the diverse requirements and guidelines that span across multiple sources. These include the SDTM Implementation Guide (SDTMIG), the domain-specific assumptions sections, and the FDA Study Data Technical Conformance Guide. While automated tools like Pinnacle 21 play a critical role in detecting many issues, they have limitations. This article provides an in-depth guide to conducting a thorough SDTM review, enhanced by real-world examples that highlight commonly observed pitfalls and solutions. 1. Understanding the Complexity of SDTM Review One of the first challenges in SDTM review is recognizing that SDTM requirements are spread across different guidelines and manuals. Each source offers a unique perspective on compliance:...

Revolutionizing SDTM Programming in Pharma with ChatGPT Revolutionizing SDTM Programming in Pharma with ChatGPT By Sarath Introduction In the pharmaceutical industry, standardizing clinical trial data through Study Data Tabulation Model (SDTM) programming is a critical task. The introduction of AI tools like ChatGPT has opened new opportunities for automating and enhancing the efficiency of SDTM programming. In this article, we will explore how ChatGPT can assist programmers in various SDTM-related tasks, from mapping datasets to performing quality checks, ultimately improving productivity and accuracy. What is SDTM? SDTM is a model created by the Clinical Data Interchange Standards Consortium (CDISC) to standardize the structure and format of clinical trial data. This model helps in organizing data for submission to regulatory bodies such as the FDA. SDTM programming involves mappi...