Clinical Data Interchange Standards Consortium (CDISC)
The Pharmaceutical Industry is well-known for it's different mergers and acquisitions. These changes over the period of time have led to the radical changes in the way the clinical data is collected, analyzed and submitted.
This takes a toll on the SAS Programmers and Statisticians as they have to keep changing their process of data analysis according to the policies brought out by the merging and acquisitioning organizations. This mainly affects the long-term studies as they will have to manually redo all of the past analysis as per the new standards.
The different processes followed for the collection and submission of clinical data is harder on the regulatory bodies like FDA, PMDA etc., as for instance, an organization would code the gender value, Male as 'M', whereas another organization would tag the same as '0' or small m ('m') or any other code as per their internal standards. These differences delayed the drug approval process and thereby causing a delay in delivering life saving drugs to the patients.
In order to accelerate the drug approval process, the U.S Food and Drug Administration decided to implement a universal standard across all pharmaceutical organization.
CDISC was founded by Dr. Kush in 1997. She has over 40 years of experience in medical research and related process improvement, technology and standards. CDISC began as an all-volunteer organization with no funding, which later on grew to over 400 member organizations, an annual revenue of $7.5 million from diverse sources, and thousands of volunteers.
Now, U.S. (FDA), Japan (PMDA) and the European Medicines Agency (EMA) require CDISC standards to be adopted in the clinical trial applications.
CDISC Standards in the Clinical Research Process
SEND stands for “Standard for the Exchange of Nonclinical Data.” SEND guides the organization, structure, and format of all nonclinical data. The SEND Implementation Guide (SEND-IG) provides predefined domains and examples of nonclinical (animal) data based on the structure and metadata defined by the SDTM.
PRM stands for "Protocol Representation Model" provides a standard for planning and designing a research protocol with focus on study characteristics such as study design, eligibility criteria, and requirements from the ClinicalTrials.gov, World Health Organization (WHO) registries, and EudraCT registries. PRM assists in automating CRF creation and EHR configuration to support clinical research and data sharing.
CDASH stands for "Clinical Data Acquisition Standards Harmonization". CDASH establishes a standard way to collect data consistently across studies and sponsors so that data collection formats and structures provide clear traceability of submission data into the Study Data Tabulation Model (SDTM), delivering more transparency to regulators and others who conduct data review.
SDTM stands for “Study Data Tabulation Model.” SDTM is arguably the most well recognized and widely implemented CDISC standard. SDTM outlines a universal standard for how to structure and build content for data sets for individual clinical study data.
ADaM stands for “Analysis Data Model.” ADaM can also be thought of as data that is “analysis ready.” The main difference between ADaM and SDTM standards is the way in which the data is displayed. ADaM datasets can be used by the FDA to easily recreate analyses.
The above mentioned standards are termed as "Foundational Standards".
CDISC Foundational Standards are the basis of the complete suite of standards, supporting clinical and non-clinical research processes from end to end. Foundational Standards focus on the core principles for defining data standards and include models, domains and specifications for data representation.