- by Handson
- November 6, 2025
Free Sample Clinical Data Management Project Case Study: Clinical Trial Safety Data Analysis Using Base SAS & Advanced SAS Industry: Pharmaceuticals & Life Sciences
Industry: Pharmaceuticals & Life Sciences
Domain: Clinical Data Management (CDM) & Clinical SAS Programming
Tools Used: Base SAS, SAS SQL, SAS Macros (Advanced SAS), PROC FREQ, PROC MEANS, PROC REPORT
Skill Level: Beginner to Intermediate Clinical SAS Analyst
Introduction
Clinical Data Management ensures that clinical trial data is accurate, consistent, validated, and audit-ready. SAS is widely used due to its reliability and regulatory acceptance by US FDA, EMA, CDSCO.
This project demonstrates how Base SAS and Advanced SAS are used to prepare and analyze clinical trial safety data.
Project Scenario
A Phase III clinical trial is being conducted for a new Type 2 Diabetes drug. Patients are monitored for adverse events, vital signs, lab results, and treatment effects.
You will clean, validate, analyze, and summarize patient safety data.
Project Objective
-
Standardize patient-level datasets
-
Identify missing and inconsistent data
-
Summarize adverse events by treatment group
-
Generate safety listings and summaries for CSR
Datasets Used
| Dataset | Purpose | Key Variables |
|---|---|---|
| DM | Demographics | Subject_ID, Age, Sex, Treatment |
| AE | Adverse Events | AE_Term, Severity, Outcome, Dates |
| VS | Vital Signs | BP, Heart Rate, BMI |
| LB | Lab Values | Blood Glucose, Hemoglobin |
SAS Workflow Summary
Step 1: Import Raw Data
proc import datafile="/path/AE.csv" out=AE_raw dbms=csv replace;
guessingrows=max;
run;
Step 2: Clean and Standardize
data AE_clean;
set AE_raw;
Subject_ID = strip(upcase(Subject_ID));
AE_Severity = propcase(AE_Severity);
if AE_Severity="" then AE_Severity="Not Reported";
run;
Step 3: Validate Data
proc freq data=AE_clean;
tables AE_Severity AE_Outcome / missing;
run;
Step 4: Summarize Adverse Events
proc sql;
select Treatment_Group, AE_Severity, count(*) as Event_Count
from AE_clean
group by Treatment_Group, AE_Severity;
quit;
Step 5: Safety Summary Report
proc report data=AE_clean nowd;
columns Subject_ID Treatment_Group AE_Term AE_Severity AE_Outcome;
run;
Step 6: Automate with Macro
%macro AE_summary(dataset);
proc freq data=&dataset.;
tables AE_Severity*Treatment_Group / nocol norow;
run;
%mend;
%AE_summary(AE_clean);
This project reflects real CDM workflows used in Pharma & CRO environments and develops both Base SAS and Advanced SAS programming skills.
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