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Regulatory Requirements

Computer Software Assurance (CSA): What Life Sciences Companies Need to Know

Learn what Computer Software Assurance (CSA) means for life sciences, how it differs from traditional validation, and how to apply a risk-based FDA-aligned approach.

Executive brief

Add a link to the final draft and add a sentence about when the FDA made it final (not just a draft)

Computer Software Assurance (CSA) is the FDA’s risk-based framework for assuring that software used in production and quality systems performs as intended. The FDA finalized its current guidance on February 3, 2026, superseding the prior guidance issued on September 24, 2025.

Rather than treating every function with the same level of testing and documentation, CSA encourages life sciences companies to apply critical thinking, focus on intended use, and match the level of assurance to patient safety, product quality, and process risk.

In simple terms, Computer Software Assurance helps organizations move away from documentation-heavy habits and toward a more efficient, evidence-based approach. The goal is still compliance. The difference is that CSA promotes smarter testing, better use of prior work, and clearer focus on what actually matters.

The FDA has long encouraged risk-based approaches for software and automated systems. CSA brings more clarity to that direction. It supports the broader Case for Quality model, which is meant to help life sciences companies improve product quality and patient safety while reducing unnecessary compliance burden.

Two issues have driven the push toward CSA. First, many organizations have been slow to implement modern automated systems because validation approaches feel outdated, unclear, or too burdensome. Second, companies often spend so much effort producing documentation that they lose sight of the real purpose, understanding system risk, addressing root causes, and improving quality outcomes.

Computer Software Assurance does not eliminate discipline or testing. It changes how assurance is applied. Traditional validation often relied on highly scripted testing and large documentation packages regardless of actual risk. CSA shifts the focus toward intended use, critical functions, and the types of evidence needed to show the system works as expected.

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