CDISC Data Standards Explained: CDASH, SDTM, SEND, and ADaM

By Ashley Kesler, MSc (Sr. Director, Statistical Programming, Biostatistics)

What is CDISC and Why Does it Matter?

The Clinical Data Interchange Standards Consortium (CDISC) is a global not-for-profit organization that develops universal standards for data collected during clinical research. Before CDISC was founded in 1997, the lack of standardization in clinical trial data made submissions to regulatory agencies and global data sharing needlessly difficult and prone to delays from submission to approval. These complications impeded therapies from reaching the patients who needed them. Recognizing the need for standardization, Rebecca Kush, PhD., founded CDISC to increase the accessibility, interoperability, and reusability of data from clinical research.

Today, CDISC data standards play a pivotal role in harmonizing clinical research data, helping ensure consistency, accuracy, and efficiency throughout the drug development process. Regulatory agencies such as the U.S. Food and Drug Administration (FDA) and Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) require study data to be submitted in CDISC-compliant formats for regulatory submissions, underscoring the importance of these standards across the industry. 

Adhering to CDISC data standards provides a structured and standardized format for clinical and nonclinical trial data, making it easier for regulatory agencies to review and interpret submitted information. This standardization improves the usability of the data, supports a more efficient regulatory review, and helps reduce avoidable data-related delays in the approval process.

What are CDISC Data Standards?

The data standards created by CDISC can be organized into four key categories:

1. Foundational Standards

 CDISC refers to the foundational standards as the “core principles for defining data standards.” These standards include clinical and non-clinical data, models, and domains, as well as structured information derived from questionnaires, ratings, and scales.

Foundational standards include:

• Clinical Data Acquisition Standards Harmonization (CDASH)
• Study Data Tabulation Model (SDTM)
• Standard for Exchange of Nonclinical Data (SEND)
• Analysis Data Model (ADaM)
• Analysis Results Metadata (ARM)
• Questionnaires, Ratings, and Scales(QRS)

2. Data Exchange Standards

These standards support the transfer of data across different information systems, including systems that do not utilize the foundational CDISC standards (e.g., Define-XML).

3. Therapeutic Area Standards

These standards provide therapeutic area specific extensions to the foundational CDISC standards. They are documented in Therapeutic Area User Guides (TAUGs), which outline how to apply CDISC standards within individual disease areas.

4. CDISC Terminology

CDSIC terminology is a glossary of standardized naming conventions for terms and values within foundational and therapeutic area standards. The remainder of this blog focuses on four of the CDISC foundational standards, CDASH, SDTM, SEND, and ADaM, and provides insight into how they are implemented in practice.

CDASH Standards: How Data is Collected

Clinical Data Acquisition Standards Harmonization (CDASH) establishes uniformity in collecting raw data to support traceability and organization, and facilitates the creation of the Study Data Tabulation Model (SDTM) dataset. This standard is driven by how the data will likely be collected and ensures that reviewers and regulators can effectively compare data across studies, sponsors, and time. For example, a clinical trial participant’s weight may be recorded every visit. One clinical study may have weight labeled as “weight,” while another may use an abbreviation like “WT.” CDASH requires the same label for the value across all studies, increasing efficiency when the data is submitted to regulatory agencies.

While CDASH is not mandated, it is strongly encouraged as it aligns with the regulatory requirements for SDTM. Implementing CDISC standards from the outset of a clinical trial ensures that data is collected, organized, and stored systematically.

SDTM and SEND Standards: How Clinical and Nonclinical Data is Organized

The SDTM is arguably the most well-recognized and widely implemented CDISC standard. It outlines a universal standard for how to structure and build content for data sets for individual clinical studies, while the Standard for Exchange of Nonclinical Data (SEND) is an implementation of SDTM that provides the same structure to nonclinical data. Utilizing SDTM datasets allows for traceability to the source data, maintaining data integrity and quality. Following SDTM structures supports consistent data representation, reducing errors and discrepancies.

Both SDTM and SEND are required by the FDA in the United States, while the PMDA in Japan requires SDTM.  Additionally, SDTM and SEND define each segment of data as a “domain,” which enables the agencies reviewing the data to find the information they need with limited to no study-specific understanding. These domains provide structure to all data, including highly specialized fields like pharmacokinetics (PK).  For additional detail on how PK data aligns with CDISC standards, see our blog Understanding How Pharmacokinetic Data and CDISC Standards Work Together.

ADaM Standards: How Datasets are Built for Analysis

The Analysis Data Model (ADaM) establishes a standardized way to create consistent and well-defined datasets for statistical analysis from SDTM-organized data. ADaM provides predictable and precise uniformity to dataset creation, ensuring the statistical programming processes of creating tables, listings, and figures (TLFs) can be completed efficiently and with clear traceability to SDTM.  

Like SDTM, ADaM is required for submissions by both the FDA and PMDA.

Get Your Data CDISC Ready

Allucent is an industry leader in CDISC standards. Partnering with our CDISC experts provides access to a team dedicated to upholding the highest standards in clinical data services, ensuring your study data meets regulatory requirements and supports a smooth review process.  From early data collection through regulatory submission, Allucent delivers CDISC-compliant datasets and supporting documentation (e.g., Define.xml, ADRG, SDRG).

Our Biostatistics and Statistical Programming and Clinical Pharmacology teams bring deep expertise in SDTM, ADaM, and domain-specific data, and submission documentation to ensure every deliverable supports regulatory clarity and data integrity. To learn more about CDISC standards and how the A-Team can help you prepare CDISC-ready data sets, visit our website, Biostatistics & Statistical Programming | Allucent.