TL;DR: This blog post outlines ten common mistakes made during a Computer System Validation (CSV) project, such as having an inadequate validation plan or poor documentation. The article offers guidance on how to avoid these errors to ensure a successful CSV project and prevent negative consequences like FDA warning letters or plant shutdowns.

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Validation Plan? 

Test Scripts? 

Testers and Approvers? 

Your Computer System Validation (CSV) project is underway.

Or is it?

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The Items checked above, in addition to a few other documents, are key deliverables for the success of your CSV project. However, within those items, there are crucial details that can easily be overlooked or oversimplified, opening your organization to risk. 

Validation is a process to establish documented evidence that ensures that a computer system will consistently produce results that meet its predetermined specification and quality attributes. (Basically, that it is fit for its intended purpose.) Listed below are common mistakes that companies make during their CSV project without being aware they are making them. We will examine each issue in detail and provide guidance on how to avoid these mistakes in your future CSV projects.

10 Common CSV Mistakes

1. Inadequate Validation Plan

To expedite project initiation or save time, some companies opt for a generic validation plan or adopt a minimalist approach. Your Validation Plan (VP) should reflect CSV best practices based on your quality culture. Create your plan based on knowledge of regulatory policies, validation, and technology (i.e. informatics software, instruments, etc.). Your plan should satisfy all regulatory policies and your industry best practices (e.g., good automated manufacturing practice; GAMP). One important tip would be to have the Validation Plan set and approved at the start of the project. 

2. Incorrect Team Members

Due to time constraints or availability, a company may add members to the project who lack experience with CSV. The heart of creating and implementing an exceptional validation plan and project is having an experienced team of people who are knowledgeable in regulatory practices, validation, laboratory practices, and technology (i.e., instrumentation, informatics software). Furthermore, depending on the size and scope of your project, the number of team members is crucial. You want to ensure that you have the correct number of individuals on your team, so no one has too much on their plate and you have the subject matter experts needed to fill any gaps. 

3. Lack of Attention from Team Members

You may have enough of the correct individuals on your team, but this project may not be their priority. One key to a successful CSV project is not only time/resource availability but that team members have the CSV project designated as one of their main priorities. Having a plan in place that lays tasks out for each team member and the approximate time needed to complete the tasks will also be critical to success. Distributing the plan and schedule at the outset can greatly assist management with determining how much time is needed from individuals and if their normal, daily tasks will need to be reassigned to someone else. 

4. Inadequate Testing With Vague or External Scripts

If your test scripts only assess the base system requirements (i.e., vendor-executed test scripts), you are likely missing other areas of importance specific to your implementation that need to be tested for the successful validation of your informatics software. If you rely solely on the vendor-executed test scripts, they will not reflect your user or system requirements, and you will, therefore, not be truly validating the system for your intended use. Your test scripts need to reflect your user and functional requirements. 

‍5. Overlooking Dry Runs in Test Execution 

You’ve spent weeks, possibly even months, working on your validation project and it is just about time to execute your IQ/OQ/PQ test scripts. But, due to tight deadlines, no time has been budgeted for dry running your scripts. Dry running your test scripts can ensure that the steps make sense, that all of the needed requirements (based on your risk assessment) are tested, and see if there are any bugs in the system. Make sure that when the project schedule is drafted, time is added for test script dry runs.

6. Poor Documentation

This mistake could cause you to fail an FDA audit. Confirm that the documents for your validation project are clear and concise, and that they demonstrate the CSV process. This will help to ensure that you pass the audit. As mentioned in point #2, having the right validation team members who have knowledge of regulatory practices will be advantageous in writing and reviewing documents.

7. Improper Risk Allocation      

Do not waste time on low-value testing activities (e.g., out of the box functionality that has already been tested in OQ). Concentrate on high-risk areas such as configured or custom areas. Your validation efforts should include accurate and informed risk assessments that identify your required test cases and the optimized level of testing for each.

8. Incorrect Execution of OQ or PQ Test Scripts

Incorrect execution of OQ or PQ scripts within the validation environment can result in rejection by quality assurance (QA), the system owner, or the business owner. Such errors often necessitate the initiation of discrepancies or deviations, which may require partial or complete re-execution of the test scripts—ultimately causing project delays.      To mitigate this risk, executors must be fully trained in relevant SOPs before starting. Each test step should be carefully reviewed; executed with attention to detail; and documented with date, time, and signature. Screenshots must be attached where required. Any missed signatures must be justified and corrected with proper timestamps. Executors should also check for typographical errors before final sign-off.     

9. Improper Handling of Deviations 

Upon identifying a discrepancy during test execution, testing must be halted immediately. QA should be notified. A deviation form or log must be completed, detailing the type, severity, occurrence date/time, closure timeline, root cause, and corrective actions. It is critical to involve QA, the system owner, and the business owner throughout the deviation process. Failure to keep stakeholders informed can delay validation reviews and approvals, impacting overall project timelines. It is critical to involve QA, the system owner, and the business owner throughout the deviation process. Failure to keep stakeholders informed can delay validation reviews and approvals, impacting overall project timelines.

10. Incorrectly Addressing Cybersecurity Threats

CSV depends on secure digital platforms. With the rise in cyberattacks, there's a risk of losing critical data, which can compromise system integrity and lead to regulatory issues. To safeguard validated systems, organizations must implement strong cybersecurity measures. These include firewalls to block unauthorized access, strict permissions by user roles, encryption to protect data, and intrusion detection systems to identify threats early. Taking these steps helps keep systems safe and ensures the validation process stays on track.

Approach CSV with the Respect It Deserves          

It is clear from the common mistakes listed here that CSV is complex, time consuming, costly, and risky.

Not properly validating your informatics software can result in:

• 483s (warning letters)
• Consent decrees
• Lawsuits/fines
• Plant shutdowns
• Indictments
• Product recalls
• Layoffs

Fortunately, using the included recommendations and logic can help ensure a successful CSV project. 

If you’re unsure where to start or need help, CSols can help with your validation and compliance needs. 

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What mistakes have you made during a CSV project?