Understanding Computer System Validation

Understanding Computer System Validation

Every regulated pharma organization should have a validation master plan to guide them through the computer system validation process. This is what GAMP 5 guidelines are designed to do.

Understanding how a computer system is validated involves understanding several different things. We’ll look at the concepts of System concept, requirements gathering, defining the scope, testing, and documenting.


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In regulated industries, like pharmaceuticals and medical devices, mistakes in computer systems can have deadly consequences. That’s why computer system validation (CSV) is so important. CSV ensures that regulated data and electronic signatures are treated the same as paper records and handwritten signatures and provides the same confidence level.

So, what is computer system validation? It is a fundamental idea in the world of FDA-regulated sectors, where stringent procedures are implemented to ensure that computer systems suit their intended purpose. A typical CSV project starts with a planning stage, which includes defining user requirements specifications and creating a high-level project plan, timelines, resources, benefits, restrictions, and risks. Then comes the design phase, where a team builds a detailed model of the hardware and software. Then IQ tests are performed, the system is installed in a user environment and undergoes OQ testing to ensure it works as intended.

When any changes to the system are made, they must be documented and subjected to a risk assessment and a full validation. Ideally, any new hardware components are provided by the same supplier to avoid issues with compatibility. The final step in this phase is to perform full data archiving to move the data from the user environment where it was created to another area for long-term storage.


Computer system validation is a delicate task. Regulatory bodies like the FDA take it seriously because, as we all know, software flaws can lead to catastrophic consequences. One only needs to look at the FDA Library of Warning Letters to see a few examples of software that has been blamed for injuries and deaths.

Almost all modern manufacturing facilities have a lot of computer systems that control the entire operation. From local Programmable Logic Controllers (PLCs) controlling manufacturing and laboratory equipment to high-level standalone systems, computer system validation (CSV) is needed to ensure these systems meet industry standards and perform consistently.

CSV is a systematic process that breaks down into distinct phases. The classic V Diagram is commonly used to visualize computer system validation’s different testing and qualification activities. The left side of the V represents your intended use of the computer system and the functional requirements that will enable it to fulfill its function. In contrast, the right side of the V represents the qualification testing performed on the approach to prove it can meet the user requirements.


Computer system validation requires a complete and thorough assessment of the data that will be collected and used by a computerized system. This process ensures that the information produced by the automated system meets quality requirements for its intended use.

The FDA and other regulatory agencies do not take these software issues lightly. Just look at their library of Warning Letters. A good example is the Therac-25 radiation therapy machine that gave patients a massive radiation overdose due to undetected programming issues.

The FDA outlines a comprehensive set of rules for computer system validation in their 21 CFR Part 11 guidelines. This guidance is supplemented by the GAMP 5 guidance, which provides additional details and best practices for computer systems validation. Computer systems must be continuously validated to ensure the hardware and software function as expected. This can be done through regression testing, periodic risk assessments, and a complete update and re-validation of the computerized system when necessary. This approach will help to avoid errors in computer systems that “magically” appear after a software upgrade or hardware change.


Computer system validation (CSV) is crucial for any pharma business. Aside from protecting data integrity and complying with regulatory requirements, CSV also helps to ensure that the end product meets customer expectations. However, a poorly executed computer system validation can have serious consequences. Software defects cause 24% of medical device recalls.

This is why pharma companies must take the time to perform CSV effectively. But how exactly do they do this? This blog post will explore the basics of CSV and why it’s so essential for regulated industries.

There are a few different methodologies for validating a computer system, but the most common one is the classic “V Diagram.” The V-shape of this methodology begins with the planning phase and moves through IQ tests, PQ testing, and finally, reporting. This process aims to prove that the system functions as designed and complies with GAMP (Good Automated Manufacturing Practice) guidelines. This is done through documented evidence demonstrating the approach is safe, installed correctly, and within recommended environmental conditions.


Computer system validation ensures that all automated computer systems in industrial production fulfill their automatic functions and contribute to the traceability of produced batches in compliance with the GxP regulations. This is achieved by applying the principles and approaches of a validation life cycle as defined by the guideline ISPE GAMP 5.

The V-model is an excellent way to visualize the relationship between requirements, specifications, and testing (represented down the model’s right side). IQ tests document what you need your system to do, DS documents how you want it to do this, and OQ tests verify that these specifications are met.

Despite the time commitment, there are several reasons why you should proactively perform CSV. It protects against damage, shutdowns, distorted research results, product and sample loss, and image loss and meets regulatory agency requirements. In addition, it enables companies to reduce operating and labor costs by minimizing errors and maximizing productivity. It also allows for a smooth transition to new systems and applications and helps avoid tech debt. The FDA’s upcoming guidance on computer software assurance will reinforce these benefits and encourage organizations to take a more agile, risk-based approach to CSV.

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