By Jessica Umoren
SAS (Statistical Analysis System) is a powerful statistical programming platform made for advanced analytics, especially on large administrative datasets. One of its most prominent and established clients is the U.S. Food and Drug Administration (FDA), a relationship that dates back decades and includes a recent 40-year partnership extension worth $49.9 million to support analytics modernization, AI, and machine learning efforts within the agency.
Some may assume trendier software and programming languages like Python and R is the way to move forward, especially in the age of machine learning and AI, but SAS is central to one of the world’s most important regulatory agencies. The reason lies not in mandate — the FDA does not legally require SAS for its service— but in trust, reliability, and regulatory readiness. For the FDA, the software must be “validated” to prove it produces the same result every single time, regardless of the machine it’s running on. With SAS the vendor (SAS) takes on the burden of validating the underlying code, and when a reviewer runs a procedure, the math is guaranteed. Because R and Python rely on thousands of community-contributed packages that update constantly, the burden of validation falls on the user.
One major factor in SAS’s strong position is its integration with CDISC (Clinical Data Interchange Standards Consortium) standards, which are the structural frameworks regulators use to interpret clinical trial data. Although other tools can be used for analysis, SAS’s original ability to create, manipulate, and deliver data in FDA-preferred formats makes it uniquely suited for submissions that must withstand intense regulatory scrutiny.
Another key benefit is auditability and compliance: SAS environments can document every step of data transformation and analysis, maintaining comprehensive audit trails. This reduces risk in regulatory review cases where accuracy and traceability are non-negotiable.
It’s also about institutional momentum. Decades of FDA reviewers trained in SAS, years of legacy code, and deep integration across government health agencies mean there’s simply less risk in sticking with a known, validated platform.
In short, SAS doesn’t monopolize FDA submissions because of legal requirement — it remains dominant because it meets the unique demands of regulatory science better than most alternatives, blending stability, standardization, and institutional trust in a way that open-source languages still struggle to match.
Sources:
“SAS Becomes FDA-Submission-Friendly.” Fierce Biotech, 31 May 2010, http://www.fiercebiotech.com/it/sas-becomes-fda-submission-friendly.
SAS, na. “FDA Inks $49.9 Million Deal with SAS.” Global Pharmaceutical Technology, 11 Jan. 2021, http://www.pharmatechglobal.net/industry/news/fda-inks-49-9-million-deal-with-sas.
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