If you have a background in pharmacy, life sciences, biotechnology, or statistics – and you’re curious about the world of clinical research – there’s one career path you might want to explore: clinical SAS programming.

Maybe you’ve heard the term before and wondered what it really involves. The good news? With a focused approach and the right resources, it’s entirely possible to build the skills you need in just six months. Let’s walk through what that journey might look like.

What does a clinical SAS programmer do?

At its core, a clinical SAS programmer is someone who helps turn clinical trial data into something usable and compliant. They work closely with biostatisticians and data managers to clean, structure and analyze data collected during clinical trials – and ensure it aligns with global standards.

You’ll often hear about two major Clinical Data Interchange Standards Consortium (CDISC) standards:

• Study data tabulation model (SDTM): Used to organize and structure raw clinical data for submission.
• Analysis data model (ADaM): Focused on data that's ready for statistical analysis.

If you enjoy problem-solving, working with structured information, and supporting medical progress behind the scenes, this role might be a great fit.

How does SAS help?

You might be wondering, “Why should I learn SAS specifically?” Well, in clinical research, SAS is more than just a tool – it’s a global standard. SAS supports analysis and outputs that are fully compatible with the requirements of regulatory agencies like the U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA). Many pharmaceutical and contract research organization (CRO) teams use it exclusively for clinical data analysis.

In other words, if you want to work in clinical programming, learning SAS gives you a serious advantage.

A month-by-month learning roadmap

Here’s a rough sketch of how your learning journey could unfold over six months:

Month 1: Start with the basics

Begin by getting comfortable in the SAS environment. You’ll learn how to:

• Import and manage datasets.
• Clean and transform data.
• Write your first programs using DATA and PROC steps.

By the end of the month, you might even be ready to try the SAS Base Programming certification exam.

Month 2: Automate and optimize

Now that you’re grounded in the basics, it’s time to step up your skills:

• Explore SAS Macros to automate repetitive tasks.
• Learn advanced Structured Query Language (SQL) for complex data operations.

This stage is all about writing smarter, more efficient code.

Month 3: Understand the clinical world

Clinical programming isn’t just about code – it’s about context. You’ll dive into:

• Clinical trial phases and stakeholder roles (sponsor, investigator, CRO)
• Regulatory frameworks like Good Clinical Practice (GCP), International Council for Harmonisation (ICH) and 21 CFR Part 11 (U.S. guidelines for electronic records).

You might also review case report forms (CRFs) and clinical study reports (CSRs) to understand how data flows through a study.

Months 4 and 5: Learn CDISC Standards

This is where things get more structured (literally). You’ll learn how to:

• Convert raw data into SDTM and ADaM datasets.
• Use mapping strategies to align data with CDISC specifications.
• Work with tools like define.xml (a metadata file that documents your datasets).

Hands-on practice is key here – whether through mock projects or training datasets.

Month 6: Reporting and final prep

In your final stretch, focus on presenting data clearly and effectively:

• Use PROC REPORT and Output Delivery System (ODS) to create tables, listings, and figures (TLFs).
• Simulate clinical reporting tasks using real-world examples.
• Start preparing for the SAS Certified Professional: Clinical Trials Programming exam.

By this point, your skills will be coming together – and you’ll be thinking like a clinical programmer.

Tools and resources you’ll want on hand

To make your journey smoother, consider gathering the following:

• SAS software access (academic or trial versions can work for practice)
• Sample clinical datasets (many training programs provide mock data)
• CDISC documentation for SDTM and ADaM
• Mentorship or community support, such as connecting with peers on SAS Communities

Final thoughts

Becoming a clinical SAS programmer isn’t just about learning a language – it’s about stepping into a role that supports scientific discovery and public health. With steady learning and consistent practice, even someone new to clinical research can build job-ready skills in about six months.

If you’re just starting out, don’t worry about mastering everything at once. Focus on one step at a time, stay curious and lean on the SAS community when you need help.

You’ve got this and there’s a whole field of opportunity waiting.

Start your learning journey today and unlock exciting career opportunities in clinical research!

Dr. Sunil Bhardwaj co-authored this blog post.

Sunil is a SAS Certified Data Scientist working as a Senior Analytics Training Consultant at SAS. He has more than 14 years of experience in Academia and Industry in the area of Data Science. He has mentored many SAS clients across geographies, including a wide range of SAS Technologies and SAS Solutions. Sunil resides in Mumbai, India.