CDISC Standards - In depth

Continuing further from our last post about CDISC, in this post we take a step further and understand why the CDISC standards are required.

Challenges with Raw Data

Raw data or non-standard data is usually messy and it affects our end goal of deriving some useful, meaningful conclusions from it. Clinical or Research data is no different, in fact, more is at stake with clinical and research data as incorrect conclusions could potentially compromise the lives and well being of patients.

Dealing with raw 'Clinical Trial Data' or 'Research Data' is further challenging because there are numerous pharmaceutical companies engaged in several clinical trials for different therapeutic areas and they use many varied systems to capture and process this data. So not only is each entity interested in different data points, but they have their own methods for the collection of data based on their budgets, systems, preferred vendors, therapeutic areas etc.

How do CDISC standards help?

CDISC standards help the ultimate reviewers of such data (regulatory authorities like the FDA, PMDA etc) to receive the data in a standard organized structure, so they can gain speed on the much more valuable review and subsequent approvals etc rather than spending time understanding the data and getting familiar with it.

Adoption of CDISC standards help on various fronts to overcome most of the above mentioned challenges by using clear guidelines, definitions, terminologies, relationships so that the data is represented in a structured way.

Subcategories of the CDISC standards

The CDISC standards can be sub-categorized as:

• Foundational Standards

• Operational Data Model

• Controlled Terminology

• Therapeutic Area Standards

The Foundational Standards

These set of standards 'can be' and 'should be' implemented throughout the different phases of a clinical trial.

The PRM (Protocol Representation Model) helps standardize the protocol elements using a prescribed template for a clinical trial so that the protocol does not miss out on any element which is recommended. The template can be serve as a basis for a company's own internal protocol template and adds value.

The 'EDC/CRF Build' and 'Data Capture' processes can be standardized and streamlined by implementing the CDASH (Clinical Data Acquisition Standards Harmonization) guidelines which helps in getting the correct data into the system so that mapping and programming efforts for the ultimate conversion for the submission are minimized.

The 'Data Aggregation' process which deals with storing and reviewing the collected data can be standardized by implementing the SDTM (Study Data Tabulation Model) guidelines. Implementation of this standard is the need of the hour as it is now mandatory to make submissions to the regulatory authorities in this structure.

The 'Analysis and Reporting' is standardized by implementing the ADaM (Analysis Data Model) guidelines, which again is the mandatory submission standard.

Operational Data Model

The ODM (Operational Data Model) is perhaps the oldest of all CDISC standards and standardizes the storage and exchange of data across platforms or systems so that the data is not platform or system dependent. The ODM model basically is data represented in a machine readable format (XML) which can also be transformed to a human readable format using style-sheets (XLST). The most common ODM extension is the 'define.xml' which is a mandatory component for SDTM and ADaM submissions.

Controlled Terminology

The Controlled Terminology is an important concept to be implemented throughout the process right from the 'EDC/CRF Build' to the 'Analysis and Reporting' because it serves to standardize the data being collected at the 'Value' level.

Therapeutic Area Standards

The Therapeutic Area standards, commonly referred to as TAUG's (Therapeutic Area User Guides) are basic user guidelines from CDISC for specific therapeutic areas. Following the relevant guidelines in addition to the implementation of the above mentioned 'Foundational Standards' is highly recommended to enhance the quality of the data.

As the regulatory authorities become more and more familiar with reviewing the data received in CDISC standard formats, it only makes sense to adopt these standards all the way through your clinical trial processes. Citus Consulting can help you implement these standards in an efficient manner so that your submission packages are truly submission ready.