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Clinical Data Interchange Standards Consortium is a non-profit organization that provides a complete suite of standards for supporting clinical and non-clinical research processes. It is dedicated to improving complete medical research through standardizing the data. The organization states, ‘We develop and advance data standards of the highest quality to transform incompatible formats, inconsistent methodologies, and diverse perspectives into a powerful framework for generating clinical research data that is as accessible as it is illuminating.’1

CDISC promotes many worldwide standards aimed at improving the quality and interoperability of research and healthcare. During clinical trials or non-clinical research, US Food and Drug Administration, urge collecting, organizing, and analyzing the data as per the standards set by CDISC.

Clinical Data Interchange Standards Consortium supports various standards to promote the smooth process of the research (as shown in figure below). However, there are three key standards that CDISC supports, including the (SDTM), (ADaM), and (SEND).2

Of these, SDTM and ADaM are CDISC standards for clinical research, whereas SEND is used for nonclinical investigations. In addition, SEND is basically an implementation of the SDTM standards for non-clinical investigations. Other than this, CDISC also promotes Clinical Data Acquisition Standards Harmonization (CDASH). In this blog, we’ll briefly discuss these standards and their relevance and importance in clinical and non-clinical research.

The main objective of the CDASH is to describe the basic standards for the consistent collection of clinical trial data. The data for each clinical trial differs, and so do their data collection methods. The clinical trial procedure necessitates accurate and concise data collection at the source as well as statistical analysis to determine the primary and secondary objectives. The accuracy with which raw data is collected has a direct influence on the statistical outputs created in accordance with the statistical analysis strategy. As a result, the data collection methods utilized for data transcription must be simple, traceable, and accurate. Allowing the investigator to submit reliable subject data. Further, to collect data consistently across the studies and sponsors, CDASH recommends the set standards to provide uniform and traceable data collection formats and structures. These standards help deliver more accurate and transparent data to the concerned regulators and the reviewers.3,4 

In simpler terms, CDASH basically represents the common best practices for developing case report forms (CRFs). Regulatory authorities like the FDA widely recommend using various domains frequently employed in most clinical trials across different therapeutic areas.

In addition, since CDASH standards are a subset of SDTM, starting the data collection at the source ensures a smooth data collection and interpretation flow. Moreover, it is highly recommended by the CDASH standards to collect only the key data required for the statistical analysis, eliminating the need for non-relevant fields in the CRFs.3 The figure below presents the benefits of utilizing the CDASH standards in the clinical trial process.

SDTM is a standard for organizing and developing data in order to expedite data collection, management, analysis, and reporting procedures. Among all the CDISC data standards, SDTM is one of the most important. It’s a framework for organizing data generated during clinical trials involving humans. It is also one of the required standards by the FDA and the Japan Pharmaceuticals and Medical Devices Agency (PMDA) for data submission.5

The FDA has also published recommendations requiring sponsors to submit clinical trial data in the CDISC-developed Study Data Tabulation Model format. As per FDA’s 745A(a) of the Federal Food, Drug, and Cosmetic Act (FD&C Act) (21 U.S.C. 379k-1(a)), ‘at least 24 months after the issuance of a final guidance document in which the (FDA or the Agency) has specified the electronic format for submitting certain submission types to the Agency. Such content must submit electronically and in the format specified by FDA.’6

Prior to CDISC SDTM implementation, there was no established standard to describe different domains and variables. Which made it harder for the regulatory reviewers as they had to spend a significant amount of time putting the data into a standard format and finding out the domain and variable names in each dataset. This caused a great delay in the clinical trial procedures. Thus, the fundamental goal of implementing the SDTM standards is to provide regulatory authorities and reviewers with a clear description of the structure, characteristics, contents, and variables presented in an organized manner as part of the clinical study.

In addition to clinical trials, SDTM may be used to build a clinical research data warehouse that will allow researchers to pool clinical research study data from different studies that are undertaken in the same disease area.7

ADaM standards outline the specifications for a subject-level analysis file and a fundamental data structure that may be applied to a wide range of analysis techniques. Additionally, these standards explain how to produce analysis datasets and related metadata, allowing statistical programmers to quickly generate tables, listings, and figures (TLFs).

It specifies a consistent and reproducible method for organizing databases, datasets, and variables for analysis and reporting. These standards also include guidelines for developing analysis datasets, defining variable names and labels, and creating metadata that documents the analysis process. The figure below represents the key principles and benefits of implementing ADaM standards during the clinical trial process.8,9

CDISC is a global organization that develops and promotes CDASH, SDTM, and ADaM standards to improve efficiency and effectiveness in clinical research. The purpose of these standards is to promote data transparency and interoperability while reducing inefficiencies and costs associated with clinical trial data management. Moreover, DISC guarantees that clinical trial data may be easily collected, analyzed, and shared across many systems, platforms, and organizations by providing uniform formats and standards.

  1. CDISC. About CDISC. Accessed 04 October, 2023.
  2. CDISC. Standards, Accessed 06 October, 2023.
  3. Gaddale JR. Clinical Data Acquisition Standards Harmonization importance and benefits in clinical data management. Perspect Clin Res. 2015;6(4):179-183. doi:10.4103/2229-3485.167101
  4. CDISC. CDASH. Accessed 06 October, 2023.
  5. CDISC. SDTM. Accessed 06 October, 2023.
  6. US Food and Drug Administration. Providing Regulatory Submissions in Electronic Format — Standardized Study Data. Published June 2021. Accessed 06 October, 2023.
  7. Yamamoto K, Ota K, Akiya I, Shintani A. A pragmatic method for transforming clinical research data from the research electronic data capture “REDCap” to Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM): Development and evaluation of REDCap2SDTM. J Biomed Inform. 2017;70:65-76. doi:10.1016/j.jbi.2017.05.003
  8. CDISC Wiki. Analysis Data Model. Published 30 May, 2008. Accessed 06 October, 2023.
  9. CDISC. ADaM. Accessed 06 October, 2023.

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