One-Size-Fits-All Paperless Validation – Is It Really Fit for Use?

Synopsis:

Popular validation tools have a basic flaw – these applications were designed to only carry out qualification activities. This article emphasises the differences between qualification and validation, and why for process and cleaning validation/monitoring, such “paperless validation” applications offer little more value than a document management system. An efficient digital validation platform has to be a suite of applications each performing what it has to be designed for, qualification, manufacturing process management, cleaning process management separately, but still integrated so as to provide a smooth flow of data.

Introduction :

No manufacturing sector can survive without a relentless focus on quality—because the very essence of manufacturing is to produce consistent and standardized product. Any lapse in quality in pharmaceutical industry leads to regulatory scrutiny, fines, damaged reputations, and ultimately business failure. 

In pharmaceutical manufacturing, the regulatory expectation is that the process be in “a state of control”. And historically we “validate” processes, e.g., manufacturing, packaging, cleaning or QC method. The core objective of validation is to demonstrate document consistent, controlled performance over time. Validation is more than a regulatory requirement—it is the foundation of operational consistency, product quality and most importantly.

As digital “validation” solutions flood the market, the expectation is that these digital tools do more than merely replicating paper processes in electronic form – that they will enable smarter, more integrated validation approaches that align with regulatory requirements and operational needs. But do they deliver on this promise?

This article explores the differences between validation and qualification, and why the “one-size-fits-all” approach towards “validation” is an idea that falls well short of customer expectations.

Let’s Clarify the Basics

Before delving deeper, it is crucial to differentiate between the two terms that are often confused: qualification and validation.

• The expectation from Qualification is that the equipment, utilities, instruments, software used in a GMP environment have been installed correctly and function as intended.
• Expectation from Validation is to show that the processes are “in a state of control”. 

In simple terms, Qualification answers, “Does that entity work as per our requirement?” while Validation dives deeper to explore, “Can we get a reliable and consistent product?” 

Understanding Qualification

The User Requirements Specification (URS) is usually the first document created when a new entity/asset is being planned, detailing the requirements, including business, compliance, and operational requirements. This activity is done by stakeholders who are either responsible or accountable for that asset/entity.

The selected vendor(s), or the internal resource where applicable, respond with a Functional Specification (FS) detailing how the requirements in the User requirement will be met.

The specific test script document requirements vary depending on what is being qualified. However, the intent remains the same: to demonstrate, through test scripts, that the User Requirement Specification (URS) requirements have been met. These test scripts may be documented in Factory Acceptance Tests (FAT), Installation Qualification (IQ), Operational Qualification (OQ), Site Acceptance Tests (SAT), or Performance Qualification (PQ). The selection of which of these to include depends on the particular asset or system being qualified.

A Traceability Matrix document is then put together mapping each requirement to the corresponding tests, detailing the user requirement ID and the test script ID. This matrix provides clear visibility of how every user requirement specified in the URS is verified through specific test cases. 

In this sense, qualification is more likely to be a documentation-driven, structured and checklist-based approach, focusing on verifying that vendor-supplied asset/entity meet predefined specifications. 

Understanding Validation

Validation, by contrast, focuses on ensuring that processes consistently produce outcomes that meet predetermined specifications.

According to the FDA, validation is: “Establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its predetermined specifications and quality attributes.”

Where qualification proves that an asset/entity is installed and functions correctly, validation demonstrates that the processes using that asset/entity are robust, repeatable, and compliant. Furthermore, it is even more critical that “effective monitoring and control systems” are put in place for “process performance and product quality, thereby providing assurance of continued suitability and capability of processes”. This is a requirement as per ICHQ10 and continues to be for the last decade one of the most cited observations. The goal in validation and monitoring is not just compliance but smarter, data-driven decisions, continuous improvement being an important pillar. 

Validation, therefore, is data-driven and is focussed on data analysis providing the assurance that the process will consistently produce product whose quality meets predetermined specifications.

Given that qualification and validation have very different approaches and end goals, is it possible to use one software tool to manage both requirements?

Many software vendors market “all-in-one” applications as a one-stop solution. These apps promise to provide a unified platform for validation. At first glance, the appeal of a unified system is undeniable. After all, a single tool that manages documentation, qualification, and validation activities across an entire organization sounds like a great solution.

However, when the design requirement for a qualification activity has absolutely no relationship with what is to be done in validation and ongoing monitoring, how is it possible to combine the use cases? 

The data type that a qualification management system main data type is textual information. User requirements are primarily captured as detailed text entries within structured tables, and supporting test scripts are also documented largely in text form. While most data centers around descriptive narratives—such as specifications, acceptance criteria, and rationales—numeric data appears mainly when recording process parameters during process qualification (PQ) for equipment. This emphasis on text ensures that every requirement and its verification are clearly documented for traceability, auditability, and regulatory compliance.

Validation and ongoing monitoring activities are fundamentally centered around the defined product specifications, attribute specifications, equipment process parameter ranges and how these are met. The primary data type handled in this context is numeric, as these processes often involve the collection and analysis of quantifiable results—such as, equipment process parameter range for a noted batch, attribute measured results—to demonstrate compliance with set limits or acceptance criteria. This numerical data provides objective evidence to verify that equipment operate within their approved specifications, and enables continuous, data-driven monitoring to promptly detect deviations or trends. While supporting documentation like SOP may include textual explanations or rationales, it is the structured numeric data that forms the backbone of validation and monitoring efficacy.

Pharmaceutical regulators expect manufacturers to proactively show processes are in control, detect deviations, implement timely corrections, and continually improve processes to guarantee product safety and efficacy. While qualification is an integral part of the process validation program and expects all entities/assets used in the product manufacture to be shown to be “fit for use”, the expectation is also timely access to real-time or trending data, making it easy to promptly identify deviations, detect process drifts, or generate automated alerts.

So an “all-in-one” application designed to aid in qualification and CSV, can only act as storage repository for files associated with process validation. Such applications consider validation or ongoing process verification runs as static activities with no ability to let the data speak for itself.  These teams rely on time-consuming, error-prone manual reviews to collate and interpret data, increasing the risk of missed trends and delayed responses to quality issues. Furthermore, static documentation impedes data integration, reduces the potential for cross-functional collaboration, and hinders the effectiveness of continuous improvement initiatives—ultimately compromising regulatory compliance and the robust oversight expected in modern pharmaceutical manufacturing.

Conclusions

Ultimately, companies must weigh the true cost of investment, both in terms of efficiency and compliance risk, when selecting validation tools. It may be time for the industry to reconsider whether costly all-in-one solutions are necessary, or if more focused, built for purpose software solutions targeted toward manufacturing process would better serve their needs.

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