From Raw Data to Submission: Our End-to-End SAS Programming Workflow

IDDCR Research Team
Jul 24, 2025
3 min read

At IDDCR Global Research CRO, our SAS programming workflow is designed to transform raw clinical trial data into high-quality, submission-ready datasets that comply with global regulatory requirements. From the first data transfer to the final Define.xml, our process ensures efficiency, compliance, traceability, and accuracy—helping sponsors stay ahead in their regulatory timelines.

Here’s an inside look at our end-to-end SAS programming workflow for clinical research.

Collaborative session on optimizing the end-to-end SAS programming workflow with detailed flowcharts and design elements displayed on a laptop and paper.

1. Raw Data Acquisition & Initial QC

The journey begins with the transfer of raw clinical data from Electronic Data Capture (EDC) systems such as Medidata Rave, Oracle InForm, or Veeva Vault.

Our approach:

Conduct initial data QC to identify duplicates, missing values, and outliers.
Validate structure against expected CRF/eCRF design.
Implement raw-to-interim mapping for early insights.

Tools: SAS BASE, PROC CONTENTS, PROC FREQ, QC macros

2. Mapping to CDISC SDTM

We convert raw data into standardized Study Data Tabulation Model (SDTM) datasets in line with CDISC and FDA submission requirements.

Key steps:

Use annotated CRFs (aCRFs) and SDTM specifications.
Apply standard mappings (e.g., demographics → DM, adverse events → AE).
Populate controlled terms and ISO-compliant date/time formats.
Generate SUPP-- datasets and RELREC for relationships.

Tools: SAS macros, CDISC Library, Pinnacle 21 Validator

3. SDTM QC and Validation

Our independent QC team validates all SDTM outputs through double programming or independent review, ensuring 100% traceability.

Validation process includes:

Compare SDTM datasets against raw data sources.
Validate controlled terminology and variable consistency.
Run Pinnacle 21 for compliance with FDA or PMDA standards.

Output: Clean SDTM packages ready for Define.xml generation.

4. ADaM Dataset Development

With SDTM as the foundation, we create Analysis Data Model (ADaM) datasets tailored to the statistical analysis plan (SAP).

Process highlights:

Derive key variables: flags (e.g., AVALC, ANL01FL), baseline logic, change-from-baseline, censoring indicators.
Ensure ADaM datasets are analysis-ready, traceable, and align with TLFs.

Example datasets: ADSL, ADAE, ADLB, ADVS

5. ADaM QC and SAP Alignment

Every ADaM dataset undergoes thorough review against:

SAP derivations and mock shells.
Independent programming QC for derived variables.
TLF programming compatibility checks.

Result: ADaM datasets that directly feed into accurate tables, listings, and figures (TLFs).

6. Statistical Outputs: TLF Generation

Using validated ADaM datasets, we develop:

Tables (e.g., demographic summary, efficacy results)
Listings (e.g., subject-level AE data)
Figures (e.g., Kaplan-Meier plots, forest plots)

Our TLF programming is:

100% reproducible.
Annotated and traceable to ADaM variables.
Designed for cross-program review and validation.

7. Metadata and Define.xml Creation

We create comprehensive metadata for submission using Define.xml 2.0 standard.

Components include:

Dataset and variable-level metadata.
Controlled terminology and value-level metadata (VLM).
Derivation methods and algorithm descriptions.
Links to annotated CRFs and reviewer guides.

Output: Fully validated Define.xml using Pinnacle 21 and XML viewer tools.

8. Final QC, Submission Package Assembly & Support

We conduct a full dry-run review of all components:

Check alignment across SDTM, ADaM, TLFs, and Define.xml.
Conduct cross-dataset traceability checks.
Assemble submission-ready packages (eCTD format) for sponsor or direct agency upload.

Also included: Reviewer’s Guide (SDRG, ADRG), annotated CRFs, and programming logs.

Why Our Workflow Stands Out

Regulatory Compliance: Aligned with FDA, PMDA, EMA expectations

Traceability: Clear linkage from raw data to analysis
Automation + Flexibility: SAS macro libraries and re-usable templates
FSP Model Ready: Scalable support to biotechs, CROs, and sponsors
Expert Team: Certified SAS programmers and CDISC specialists

From Data to Submission – Simplified

With IDDCR Global Research CRO, you’re not just getting programmers—you’re getting strategic partners who understand regulatory science. Our SAS programming workflow ensures that your data tells the right story, in the right format, at the right time.

Let’s Make Your Submission Count.