Clinical SAS Programmer
ROLE DEFINITION & RESPONSIBILITIES
A Clinical SAS Programmer transforms raw clinical trial electronic data capture (EDC) records into standardized statistical analytical databases following CDISC industry protocols. They write production-grade SAS macros and data steps to validate datasets and generate Tables, Listings, and Figures (TLFs) required for New Drug Applications (NDAs) submitted to global health authorities.
SALARY INTELLIGENCE ROADMAP
LEARNING PATHWAYS
Core SAS Syntax & Data Manipulation
Master DATA step operations, merging, arrays, format creation, and conditional logic.
SAS Macro Language & SQL Integration
Build modular, parameterized reusable macros for automated clinical data handling.
CDISC SDTM & ADaM Implementation
Transform raw CRF data into standardized SDTM domains and build complex ADSL and BDS analysis datasets.
FDA Submission Package Assembly
Execute Pinnacle 21 compliance validation rules, generate Reviewer Guides (cSDRG/ADRG), and inspect define.xml.
CONNECTED ZANE PROED ACADEMY COURSES
Clinical SAS & Statistical Mapping Suite
Complete pathfinder training covering SDTM, ADaM, and validation codes.
VERIFIED INTERVIEW PREPARATION
> Q: What is the architectural difference between SDTM and ADaM data structures?
SDTM (Study Data Tabulation Model) standardizes raw clinical trial observations into standardized domain tables (e.g., DM, AE, LB) organized by subject and visit. ADaM (Analysis Data Model) derives analysis-ready datasets (e.g., ADSL, ADAE, ADTTE) with derived flags, baselines, and windows specifically configured for direct one-proc statistical computation without further data manipulation.
> Q: How do you handle independent double-programming validation in clinical trials?
Validation programming requires two programmers to independently write separate code starting from the raw datasets to generate the identical analysis table or dataset. An automated comparison procedure (PROC COMPARE) is then executed; the output must show zero differences in observations, variables, and calculated statistical values.