Why one-size-fits-all paperless validation software is a bad design idea?

 Synopsis:

Any “all-in-one” validation software has a basic flaw – these applications were designed to only carry out qualification activities.  Imagine a surgeon trying to perform an entire operation with a scalpel. The article emphasises differences between qualification and validation. And why we need specific software tools for manufacturing process management and cleaning process management.

The principal data type in qualification management software is textual data whereas a validation/ongoing monitoring platform is meant to collect and analyze data. Data therefore is mainly numeric.  This is why one will see that for process and cleaning validation /monitoring, such “paperless validation” applications act as a glorified document management system.  Yet companies invest large amounts of money in such all-in-one validation applications.  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.

Traditionally, validation has been managed using paper-based systems — the critical process parameters and critical quality attributes monitored not just for the validation runs but also for the productions runs.  This process involved:

• Generating protocols, in MS Word, printed and routed for signatures
• Data recorded manually in printed sheets
• Data then fed into a statistical programs so as to chart the data and for statistical analysis. 
• Deviations tracked in Quality management systems. 

This fragmented approach lead to inefficiencies, delays, and increased risk of human error. To address these challenges, many organizations are shifting toward digital, paperless validation platforms that promise streamlined workflows, faster reviews, and better data integrity.

Digital tools must do more than replicate paper processes in electronic form. They should enable smarter, more integrated validation approaches that align with regulatory expectations and operational needs.

Yet as digital “validation” solutions flood the market, some software vendors blur the lines between validation and qualification, promoting platforms that claim to handle both seamlessly. While these terms are often used interchangeably, they represent fundamentally different concepts. Failing to recognize this distinction has lead companies to capture “validation” documents as one would store in MS Share point or other storage apps, thereby losing out on the end goal which was supposed to be show the regulators that your manufacturing/cleaning processes are in a “state of control”.  Such applications have no capability to address the unique requirements of continuous improvement. 

This article explores the differences between validation and qualification, and why the “one-size-fits-all” approach towards “qualification” and “validation” is a very bad idea.  It has to fail. 

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.  A risk assessment is conducted on the requirements identified in the URS. This step analyses each requirement for its potential impact on product quality, patient safety, and compliance, helping prioritize critical requirements and define suitable verification and validation strategies

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. It is possible that all the requirements in the URS are not met by the vendor.  It is then left to the stakeholders to decide the way forward. 

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 item or system being qualified.

A Traceability Matrix document is then put together detailing the user requirement ID and the test script ID, mapping each requirement to the corresponding tests. 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 is robust, repeatable, and compliant.  Data analysis of the process parameters and quality attributes is extremely critical here. 

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. 

Can ‘One-Size-Fits-All’ Validation Software address validation 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.

What needs to be understood is that the design requirement for a qualification activity has absolutely no relationship with what is to be done in validation and ongoing monitoring.  And this is why such applications will fail. 

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 centres 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 cantered 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

Where is my batch data or its integrity?

In a pharma 4.0 world, a process management application requires input from SAP for the critical raw material attributes, vendor details, scheduling amongst others.  It would need process parameter data from a MES and attribute data from LIMS.  And QMS data for each product. 

All of this gets lost when one goes in for “all-in-one” systems.  With no ability to capture data, the user is left to carry out this activity in other applications or worse on paper.  CPP and CQA data have to be then manually collated and then data analysis executed again in an outside application.  The only activity that this “all-in-one” application can do is to act as storage repository for files.  Such applications consider validation or ongoing process verification runs as static activities with no ability to let the data speak for itself.   

And it is not just the data or its analysis where these “all-in-one” systems miserably fail.  The problem also then extends to having no clarity on what has been validated.  While the vendors promise integration with LIMS, MES, SAP, etc, the question to be asked what are you bringing into such an application, if that data is not analysable. 

Regulatory Expectations Beyond Digital Adoption

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.

Teams using this “all-in-one” application 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.

Sunken costs & Conclusion

In golf, when my ball is on the green,  I would use a putter not a driver.   The same way if you are already using this “all-in-one” solution, restrict it to just qualification.  Get software applications specially designed for manufacturing process management or cleaning process management.  If you have not bought any software for qualification or validation, you have the choice to consider the best for each and which works seamlessly when integrated. 

When the author has brought this up with companies, the most common argument is the sunken cost and the loss of face if management is told about the limitations.  This is the most difficult part to address.  Vendors offering validation solutions should highlight the efficiency that is lost by using the wrong tool.  And the compliance risk. 

And then there is the all-in-one software cost.  “All-in-one” validation solutions are not cheap.  Costs can run up to as much as $1 million per site.  If it is so expensive, why is Big Pharma and even the smaller one’s buying such a solution. That remains an enigma to the author also.    

Software solutions targeted toward manufacturing process management and cleaning process management are available in the market, and they are not expensive to try on a trial basis. 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, adaptable tools could better serve their needs.