This is the real cost of a slow or uncertain cleaning validation programme. Not the cost of the instrument. Not the complexity of the method. The cost is measured in hours of lost production, delayed releases and the quiet anxiety of knowing that if an inspector walked in right now, your data trail would not tell a clear and convincing story.

Total organic carbon (TOC) analysis exists precisely to eliminate that anxiety. When implemented correctly, it is one of the fastest, most regulator-friendly, and most operationally practical cleaning verification methods available. This article explains why so many labs are not using it that way and what it takes to change that.

What does a failed clean actually cost?

Most cleaning validation conversations start with the method. They should start with the consequence. A single failed clean in a pharmaceutical or food manufacturing facility does not just mean re-cleaning the vessel. It means halting production, quarantining potentially affected batches, initiating a deviation investigation, documenting the root cause, re-validating the cleaning cycle and demonstrating to QA that it will not happen again. In a worst-case scenario, that is days of downtime on a critical piece of manufacturing equipment.

The Chemetrix team has seen this play out in facilities relying on product-specific methods like HPLC for cleaning verification. When an unknown degradant or cleaning agent residue slips through undetected, the specific method offers no warning. TOC does. Because it measures the total organic carbon in a rinse or swab sample, it catches APIs, degradants, excipients and cleaning agents in a single analysis. There is no invisible contamination with a properly implemented TOC method.

This matters enormously in a regulated environment because it removes operator subjectivity from the result. There is no peak integration to argue about, no ghost peaks to investigate and no ambiguity about whether a signal is real or an artefact. The FDA has issued numerous warning letters specifically for HPLC data integrity failures, including failure to integrate peaks and inadequate investigation of unknown peaks. These problems are structurally unavoidable in product-specific methods because cleaning processes generate degradants and unexpected compounds that the specific method was never designed to detect.

The short answer is yes – in most cases, TOC is more cost-effective than HPLC, often delivering noticeable savings within the first year of implementation.

Chemetrix Insight: “TOC almost always reduces total validation costs within the first year by accelerating batch release and reducing the frequency of re-testing. The instrument cost is recovered faster than most labs expect.”

When TOC results are inconsistent or a cleaning validation programme is not delivering the confidence it should, the problem is almost never the analyser. Here is the hierarchy of where to look first.

What makes the Veolia Sievers M9 the right instrument for pharmaceutical cleaning validation?

At Chemetrix, we have been an authorised Agilent distributor in Southern and East Africa for decades. While our heritage is diverse, our commitment to the pharmaceutical sector is foundational. We don’t just supply instruments; we provide the technical scaffolding that allows pharmaceutical analysts to move from a raw sample to a validated report with total confidence.

Why great hardware isn’t enough

One of the most persistent challenges in the pharmaceutical workflow is the transition from a concept to a robust, validated method. It is a common misconception that high-end instrumentation automatically guarantees ease of use. In reality, pharmaceutical analysts often struggle with the “blank space” between unboxing an instrument and running their first compliant sample.

Whether you are identifying trace impurities, performing stability testing, or conducting complex bioanalysis, the method development phase is often where projects stall. A method that works in a controlled environment can fail in a high-throughput production setting if it hasn’t been stress-tested for robustness. This leads to a reactive cycle of troubleshooting and re-validation, which drains resources and delays time-to-market.

Navigating a shifting regulatory landscape

Data integrity is the non-negotiable cornerstone of the pharmaceutical industry. Global research shows that 90% of pharmaceutical professionals agree that reliable instruments are the single most important factor for a successful workflow. This is because, in this sector, a failure in reliability is a failure in compliance.

The pressure to process more samples while maintaining absolute adherence to 21 CFR Part 11 and EudraLex Annex 11 is immense. Without a partner who understands the nuances of IQ/OQ (Installation and Operational Qualification) and ongoing maintenance, labs risk falling into the “efficiency gap.” This is where sophisticated instruments sit underutilised because the method is too temperamental or the staff lack the specific training required to navigate the software’s compliance features.

Mastery of complex matrices with Agilent LC/MS

For laboratories tackling the most demanding pharmaceutical applications – such as nitrosamine analysis or impurity profiling– Agilent’s LC/MS solutions are globally recognised as the definitive standard. These systems provide the sensitivity and specificity required to detect analytes at levels that were previously unimaginable.

However, the “Chemetrix Edge” lies in how we support this technology. We recognise that method development for LC/MS is a specialised skill. Our support department acts as an extension of your own team, providing on-site assistance to help you develop, optimise, and troubleshoot your pharmaceutical methods. By leveraging our local application expertise, you can reduce the time spent in method development and ensure that your LC/MS system is performing at its peak from day one.

Chemetrix supports this hardware through a comprehensive service programme that goes beyond simple repairs. We offer tailored preventive maintenance and rapid-response technical support to ensure your 1290 Infinity III stays in a qualified state. By integrating our service expertise with this robust hardware, we help labs eliminate the “time traps” of manual intervention. Our goal is to ensure your staff spend less time worrying about baseline
drift and more time focusing on high-value data interpretation.

The reward of proactive support

The transition from a reactive laboratory to a proactive one is transformative. When you partner with a specialist who understands pharmaceutical applications, the results are measured in more than just uptime. You gain the peace of mind that comes from knowing your methods are robust, your instruments are qualified, and your data is defensible.

Our most successful pharmaceutical partners are those who have moved away from viewing instrumentation as a commodity and have embraced it as a collaborative workflow. This partnership leads to faster validation cycles, fewer “Out of Specification” (OOS) investigations, and a laboratory team that is empowered by their technology rather than frustrated by it.

 

Data integrity is a critical aspect in pharmaceutical laboratories, ensuring that the data generated during business operations and drug manufacturing is accurate, complete, and reliable. When data is reliable, business owners can make informed decisions, improve product quality, and contribute to overall success.

Data integrity is important because it builds trust with stakeholders and ensures that the information used to evaluate drug safety, efficacy, and quality is trustworthy. For patients using a pharmaceutical product, it assures them of the safety that is promised and provides qualitative evidence to support the manufacturer’s guarantee.

As W.E. Deming said,

“Without data, you are just another person with an opinion.”

Let’s explore some common myths of data integrity by looking at facts, based on a study of available resources and direct interactions with U.S. Food and Drug Administration (FDA) staff and their consultants.

Myth: All this regulation around data integrity is new

Data integrity has been a concern for decades. The FDA’s focus on it began with 21 CFR Part 11 in 1998. In 2003, after the pharmaceutical industry spent years struggling with the regulation, the FDA released its Scope and Application guidance, clarifying some of the requirements in Part 11. This guidance also included a discussion of the FDA’s selective enforcement strategy based on what the administration was finding during its inspections. In 2010, the FDA announced its focus on data integrity inspections. At that time, however, few people within the FDA were qualified to understand the data integrity aspects of computerised systems. Thus, beginning in 2013, data integrity has been a primary inspection point, and there has been a visible increase in data integrity enforcement across all geographies. In addition, starting in 2014, as a result of those inspections, the FDA has often included the names of hardware and software products in their warning letters and related public information documents in a less than subtle message to the hardware and software makers that the administration expects them to assist customers with data integrity and compliance concerns.

Myth: Data integrity is an IT issue

Success in addressing data integrity relies less on technology and more on fostering a culture, organisation, and mindset conducive to excellence. Key contributors to effective data integrity solutions include a shared vision of data integrity practices and a commitment to continuous improvement. In both paper-based and electronic systems, data integrity issues can arise, each presenting unique challenges and requiring tailored remediation strategies. Many responses to these issues overlook the possibility of such occurrences in paper-based systems, failing to conduct risk assessments or identify areas for remediation. Compliance and best practices must span data generation, transformation, maintenance, accuracy, and consistency. Cultivating the right culture, assembling capable teams, ensuring transparency in data integrity performance, and aligning company goals with data integrity objectives are all essential components of a successful data integrity initiative.

Myth: Only the software needs to be compliant

Software often does not comply with regulations. The software itself is inert; software contains the technical controls to support compliance with the applicable regulations. In addition to technical controls, procedural controls must also be in place. A discussion about procedural controls versus technical controls is often seen in FDA warning letters, particularly when gaps in a system’s ability to support technical controls required by various regulations have been exploited.

A standard operating procedure (SOP), used as a procedural control, can substitute for a technical control as long as:

• People are trained on that SOP

• The SOP is followed

• Adherence to the SOP is confirmed by quality oversight and/or compliance auditing

Often, however, even if SOPs exist, they are not followed, and adherence isn’t properly verified. Consequently, the FDA will demand system remediation to prevent a recurrence of the behaviour. Audit trails within computerised systems are an example of technical controls. The software must be able to generate audit trails that contain all the components the regulations require, and then those controls must be enabled.

Analytical instrument manufacturers are taking compliance and regulations into account with their products. As an example, Agilent is applying critical thinking to redesigning laboratory software to help respond to new regulatory compliance realities. Many systems may generate audit trail reports in printed form, but the new version of the Agilent OpenLAB Chromatography Data System has a built-in tool that allows a user to electronically review electronic audit trails entries. These audit trail entries are organised by type, an online review can be performed, and electronic signatures incorporated.

If data integrity regulation compliance is a necessity for your pharma lab, Chemetrix is able to provide solutions that include instruments and software that can help ensure your data is not only well managed and organised, but kept safe and generated with adherence to all the regulatory guidelines.

Data integrity problems can severely impact business operations, leading to financial losses, legal issues, and damaged reputation. It forms the foundation of for reliable pharmaceutical research, development, and manufacturing and, therefore, should be as error-free and precise as possible. It goes beyond being just a practice; data integrity is the cornerstone of trust and excellence in pharmaceutical labs, paving the way for groundbreaking discoveries and lifesaving innovations.

The final phase of the analytical process is perhaps the most critical stage for assuring data integrity. This is where raw data, factors, and dilutions come together to create reportable values, and labs must consider and respond to the potential for improper manipulation — in all its various forms.

There are a few critical choices to be made around calculation and reporting that impact compliance, the trustworthiness of results, and even the reputation of the lab.

Watch our webinar on Addressing Data Integrity Gaps webinar

No lab wants to go through all the work of setting up methods, conducting analysis and gathering data only for it to be for nought or at risk because the data integrity system wasn’t up to par. Here is our advice for maximising lab efficiency and data integrity simultaneously:

Go paperless as far as possible

No matter where calculations happen, it must be possible to see the original data, calculation procedure (method), and outcome. In addition, there must be sufficient transparency to capture any changes to factors, values, or the calculation procedure for review. To meet these requirements, there are three primary options to consider:

A spreadsheet: This remains the least efficient, least compliant, and least effective option for data integrity. A spreadsheet typically has manual data entry and permits an analyst to recalculate results before printing and saving the desired result values for the permanent batch record. Why do so many labs continue to choose it? Not simply to support the paper industry but because it is familiar and comfortable. It is time to move on to better options.

A LIMS or ELN application: If configured correctly, many of these applications have audit trail capabilities, access controls to prevent unauthorised actions and versioning of calculations, the ability to perform calculations that are problematic for chromatography applications, and more. However, their ability to interface is a process strength and data integrity weakness. Data sent into LIMS or ELN can be manipulated externally and then sent to the LIMS or ELN for calculation.

A CDS application: The chromatography data system is often the best calculation location. It usually provides access control to prevent unauthorised changes, versioning of calculations, and audit trail reviews for changes in calculated values and the calculations themselves. In addition, the calculations are in the same system that holds the original (raw) data, so that review is usually within one system.

Cut reporting time without increasing data integrity risks

Focus on the highest risks and use a CDS application to accelerate the reporting process. Interestingly, the greatest data integrity risks are sometimes indicated by a lack of out-of-specification (OOS), out-of-trend (OOT), or out-of-expectation (OOE) results. In many cases, falsification activities are directed at making test results that would fail the specification into passing results through various forms of data manipulation. This makes it prudent to carefully review results near specification limits (say, within 5%) to verify that all changes and calculations are scientifically justified.

Review your management policies

Management can inadvertently create a climate where personnel are encouraged to manipulate test results. Mandates such as “zero deviations,” “no product failures,” and “meeting production targets” can encourage data manipulation. Throw in the possibility of a demotion or dismissal for failure to meet any of these mandates, and the environment is ripe for data manipulation.

The irony is that two losers are created: the patient who receives a sub-standard product, and the company that no longer knows its true capability or process trend—or worse, suffers reputational damage. This phenomenon is recognised by the Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operation Scheme (PIC/S) data integrity guidance, warning that management should not institute metrics that cause changes in behaviour to the detriment of data integrity.

Learn more about the capabilities of OpenLab CDS

The newest release of OpenLab CDS software helps you strengthen data integrity while accelerating calculation and reporting processes. To cite just a few key features and capabilities:

The Custom Calculator tool: automatically computes unique values directly within the software, removing error-prone calculation steps and allowing you to meet compliance requirements faster and with less effort. Custom Calculator can also flag changes made after initial use of the calculation procedure — telling the reviewer that audit trails should be checked to assess the scientific merit of the change or changes. Download the Technical Overview

Automated reporting: with OpenLab CDS, analysts no longer have to enter data manually or print everything. If you analyse approximately 500 samples per month at 10 minutes per sample, including data review time, manual data entry takes about 1000 hours per year or about 25, 40-hour weeks—half of an analyst’s time. Using OpenLab CDS, reporting time can be reduced to 5 minutes per sample for time savings of 500 hours or 12.5 weeks per year.

Technical controls: within the audit trail give analysts the ability to highlight data changes and deletions to facilitate the review process, enable review by exception and create efficient search routines within an individual project or the whole database to identify data trends and inconsistencies. The application also documents that audit trail entries have been reviewed.

To learn more about OpenLab CDS for your lab and the preservation of your data integrity, learn more about the software on our Solutions page.

The traditional approaches to laboratory data integrity are insufficient to meet today’s increased scrutiny of computerised systems and the terabytes of data they produce. To successfully present your results, you must be prepared to prove that your data have not been compromised—and that can be a challenge.

Does your lab have a data integrity strategy? Are data integrity gaps putting your company at risk?

Learn how to perform data process mapping on a chromatographic process from the set-up of analysis through calculating the reportable result. From this map, the data integrity gaps can be identified, and the risk assessed to determine how critical the gaps are so that a plan and strategy to remediate or remove the risks can be implemented.

What you will learn

• Understand the scope of a data integrity program
• How to perform data process mapping on a chromatographic process to identify data integrity gaps, assess the risk posed by those gaps, and determine how to remediate or solve them.
• Understand options for short-term remediation and long-term solutions

Who should attend

Analytical chemists, technicians, laboratory managers, regulatory affairs personnel and others working in R&D and QA/QC in the pharmaceutical industry.

Speaker