CDISC Standards and Solutions

CDISC (Clinical Data Interchange Standards Consortium) develops global standards for clinical research data. These standards improve data quality, facilitate data sharing, streamline regulatory submissions, and enable more efficient analysis of clinical trial data

What is CDISC?

CDISC (Clinical Data Interchange Standards Consortium) is a global, non-profit organization that develops and supports clinical research data standards. These standards are designed to improve medical research by enabling data interoperability, enhancing data quality, and facilitating more efficient regulatory submissions.

The CDISC standards have been adopted by regulatory authorities worldwide, including the FDA (Food and Drug Administration) in the United States and the PMDA (Pharmaceuticals and Medical Devices Agency) in Japan. Since December 2016, the FDA has required that clinical trial data be submitted in CDISC format for NDAs (New Drug Applications), BLAs (Biologics License Applications), and ANDAs (Abbreviated New Drug Applications).

By implementing CDISC standards, organizations can streamline their clinical research processes, improve collaboration among stakeholders, and accelerate the development of new medical treatments.

Key CDISC Standards

SDTM

Study Data Tabulation Model - A standard for organizing and formatting data collected in clinical trials to be submitted to regulatory authorities.

  • Standardizes the organization of clinical trial data
  • Creates consistent variable naming conventions
  • Facilitates regulatory submissions
  • Improves data quality and reusability

ADaM

Analysis Data Model - Defines standards for analysis datasets and related metadata that support efficient generation, replication, and review of statistical analyses.

  • Provides clear traceability to SDTM data
  • Supports efficient statistical analysis
  • Enables regulatory reviewers to understand analyses
  • Facilitates the generation of tables, listings, and figures

Define-XML

An XML-based standard that provides metadata for describing the content and structure of clinical trial datasets.

  • Documents dataset specifications
  • Defines variable attributes and origins
  • Maps relationships between datasets
  • Required for regulatory submissions

CDISC Services

CDISC Implementation

Our experienced team can help you implement CDISC standards across your clinical studies, ensuring compliance with regulatory requirements and improving data quality.

  • Gap analysis between existing data and CDISC standards
  • Development of company-specific CDISC implementation guidelines
  • Creation of CDISC-compliant datasets and documentation
  • Validation of SDTM and ADaM datasets

CDISC Conversion

Convert your legacy clinical data into CDISC-compliant formats to meet regulatory submission requirements and enhance data usability.

  • Transformation of legacy data to SDTM format
  • Creation of analysis-ready ADaM datasets
  • Generation of Define-XML documentation
  • Implementation of controlled terminology

CDISC Consultancy

Our CDISC experts provide strategic guidance on standards implementation, helping you optimize your data management processes and ensure regulatory compliance.

  • CDISC standards training and knowledge transfer
  • Development of standardized processes and workflows
  • Regulatory submission strategy and planning
  • Audit preparation and response support

CDISC Data Mapping

Detailed mapping of your clinical data to CDISC standards, ensuring consistency, traceability, and compliance throughout your studies.

  • Creation of comprehensive data mapping specifications
  • Design of standardized mapping templates
  • Implementation of controlled terminology mapping
  • Validation of mapping results

Benefits of CDISC Standards

For Sponsors

  • Streamlined regulatory submissions and faster review times

  • Improved data quality and consistency across studies

  • Enhanced ability to combine and compare data across trials

  • Reduced time and cost for data transformation and integration

For Regulatory Authorities

  • Consistent data formats across submissions

  • Efficient review processes through standardized data structures

  • Improved traceability from analysis results to source data

  • Enhanced capability for cross-study and cross-sponsor analyses