In September 2025 (and again in February 2026), the FDA finalized its Computer Software Assurance (CSA) guidance, reinforcing a risk-based approach to validating software used for production and quality systems. For organizations still relying on traditional Computer System Validation (CSV) practices, the guidance provides greater regulatory clarity around applying risk-based assurance to modern software environments.
Many of the principles behind CSA are not new. What is changing is how organizations apply those principles as technology, software platforms, and regulatory expectations continue to evolve.
This article is the first in a four-part series exploring the evolution of software assurance in the life sciences industry. We’ll examine the regulatory drivers behind CSA, common implementation challenges, organizational readiness, and the role emerging technologies such as AI can play in modern software assurance.
Whether you’re evaluating CSA for the first time or refining an existing validation program, this series is designed to provide practical insight into building a sustainable, risk-based approach to software assurance.
Why Traditional CSV Is Being Reexamined
Computer System Validation (CSV ) has been the default operating model for life sciences companies using GxP software. Every system from a simple electronic logbook to a full-scale manufacturing execution system was typically pushed through the same rigid lifecycle.
That lifecycle promoted exhaustive requirements of documents, scripted test cases for every function regardless of risk, and stacks of signed paper evidence. Validation became one of the most expensive, time-consuming, and change-averse processes within many organizations.
The intent behind CSV has always been sound. Establishing confidence that software performs as intended is essential for patient safety, product quality, and regulatory compliance.
Over time, many organizations found that the level of validation effort was no longer proportional to system risk. Under classic CSV, a low-risk internal tracking spreadsheet often received nearly the same documentation burden as a system directly controlling a critical manufacturing step. Teams spent the majority of their time generating paperwork to *prove* testing happened, rather than actually *doing* testing that mattered.
FDA’s Case for Quality initiative, led by CDRH since 2011, identified many of these same challenges: excessive documentation, duplicated vendor testing, and a validation culture that discouraged companies from adopting newer, safer, more efficient technologies simply because validating them looked expensive on paper.
The Regulatory Foundation Behind CSA
CSA does not replace validation requirements. It provides a risk-based framework for meeting those requirements.
It is worth understanding the regulatory backbone it sits on:
21 CFR Part 820
21 CFR Part 820 establishes the FDA’s Quality System Regulation (QSR) for medical device manufacturers. As of February 2, 2026, the amended regulation aligns more closely with ISO 13485:2016 by incorporating the international standard by reference for most requirements.
General Principles of Software Validation (GPSV)
Issued in January 2002, the FDA’s General Principles of Software Validation (GPSV) provides foundational guidance on software validation principles. It focused primarily on software embedded within devices and offered limited coverage of the internal, non-product software (quality systems, production tooling, document management, etc.) that many organizations rely on today.
FDA Computer Software Assurance Guidance
Initially released as draft guidance in September 2022 and finalized on September 24, 2025 (updated again in February 2026), the FDA’s CSA guidance directly supersedes Section 6 of GPSV. It gives manufacturers a formal, risk-based framework for assuring the software used in production and quality management systems.
21 CFR Part 11
Requirements governing electronic records and electronic signatures remain fully in effect. CSA does not loosen Part 11 obligations. Instead, it helps teams focus Part 11 controls on the records that actually constitute regulatory evidence, rather than logging everything indiscriminately.
ISPE GAMP 5 Second Edition
GAMP 5 (2nd Edition) is ISPE’s long-standing risk-based framework for computerized system validation. It aligns closely with CSA’s philosophy and is widely used as the practical implementation methodology alongside FDA’s guidance.
Notably, FDA’s CSA guidance explicitly addresses modern technology realities that older guidance never contemplated: cloud computing (SaaS, PaaS, IaaS), automatic vendor updates, and even the use of AI tools within production or quality systems. Those alone signal this is a framework designed for where the industry is headed, not just where it has been.
What Changes Under CSA
The core shift is this: instead of applying uniform, exhaustive testing to every system regardless of risk, CSA asks teams to follow a proportionate, four-step process:
- Define intended use: What is this software actually supposed to do in this specific context?
- Assess the risk of failure: What is the real-world impact if this specific function fails? High process risk (direct impact on product quality or patient safety) gets rigorous scrutiny. Low-risk functions receive assurance activities commensurate with their potential impact.
- Plan assurance activities: Select the right method for the risk level, which may include scripted testing, unscripted/exploratory testing, ad hoc testing, or leveraging vendor documentation and system-generated evidence.
- Document confidence, not just activity: Records should capture the rationale for the assurance approach, not just evidence that a checklist was completed.
This is a genuinely different mindset from “validate everything the same way, exhaustively, just in case.” It asks teams to think critically about risk rather than defaulting to maximum documentation as a safety blanket, which is precisely why the transition to CSA is as much a cultural and organizational change as it is a procedural one.
Why This Matters Now
Several factors are driving this transition.
- With the September 2025 final guidance (and the February 2026 update) in place, CSA is no longer a “wait and see” draft concept. It is FDA’s stated expectation for how production and quality system software should be assured going forward.
- Technology has outpaced legacy validation models. Cloud-hosted platforms, continuous vendor updates, and AI-enabled tools do not fit neatly into validation frameworks built for on-premise, static, infrequently updated software.
- Resource pressure is not going away. Life sciences companies are being asked to do more with leaner quality and IT teams. A framework that reduces low-value documentation while increasing rigor where it actually matters is a direct answer to that pressure.
Looking Ahead
Understanding the principles behind CSA is only the first step. The harder work is adoption in the organization: getting people to trust a new way of thinking about risk, building the internal skills to apply it well, and modernizing the legacy systems and processes built around the old CSV mindset, all without compromising compliance or patient safety.
In Part 2, we will tackle the challenge that derails more CSA transitions than any technical gap: cultural resistance, and how to build genuine organizational buy-in for a risk-based mindset.
How RCM Life Sciences Can Help
RCM Life Sciences helps organizations move from traditional CSV to a more efficient, risk-based CSA model without losing control of compliance, quality, or data integrity. Our team brings practical experience across quality, regulatory, computer system validation, eQMS, project management, and digital transformation initiatives, helping clients assess current validation practices, redesign SOPs and templates, define risk-based assurance strategies, train cross-functional teams, and support inspection-ready implementation.
Whether you’re evaluating CSA for the first time or refining an existing validation program. RCM can help assess the compliance impact of cloud and AI-enabled systems and develop a practical roadmap for risk-based software assurance. Contact our team to learn more.
Next in the Series: How to Successfully Transition from CSV to CSA: Building Organizational Readiness (coming soon)