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How to Ensure Reliable Data in the Lab

The need for tougher controls as regulators hold labs to ever higher standards

by Darren Barrington-Light
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It’s very difficult for patients and consumers to determine whether their medicines are safe to use and will work as intended. At the end of the day, it comes down to trust—trust in the manufacturer’s production and quality control procedures, and in the decisions they have made to enable the batch to be released to the market.

As a result, the reliability of the data that underpins these decisions has long been of interest to pharmaceutical regulators. However, as pharmaceutical development, manufacturing, and supply chains have become more global and complex, regulatory authorities around the world are putting an increased focus on the completeness, consistency, and accuracy of this data throughout its life cycle.

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Recent guidance released by the UK Medicines and Healthcare Products Regulatory Agency and the World Health Organization (WHO), as well as draft guidance released by the US Food and Drug Administration (FDA), have all put increased focus on data integrity.

Defining data integrity

But what does this term actually mean? While somewhat open to interpretation, the WHO and the FDA point to five key principles:

  • Attributable: Who recorded the measurement or performed the experiment? And if changes were made, who did it, when did they do it, and why?
  • Legible: Will the data still be legible 20 or 30 years into the future? Data must be permanently archived and readable in perpetuity—not just for the duration of the project.
  • Contemporaneous: Was the data recorded at the time of measurement? Data collection should be supported by date and time stamps, leaving no room for ambiguity.
  • Original: Is the record an original or approved copy? Even if a paper printout is transcribed into electronic format, the original copy must be retained.
  • Accurate: Does the record reflect what was actually measured? Workflows should be designed to eliminate any potential for data to be changed from its true value.

With an increased focus on these areas, inspectors are looking for any weaknesses in laboratory workflows that may suggest that the environment in which data is collected, managed, and stored is uncontrolled. For pharmaceutical companies, this means being able to prove that results are an accurate reflection of what was measured, according to agreed-upon procedures, and demonstrate that robust control measures are in place to prevent any kind of loss in the integrity of this information.

The majority of chromatography laboratories have made the switch from paper-based systems to electronic processes. But although electronic data can be more secure, harder to modify, and easier to trace, it’s only as good as the digital tools used to manage it. As a result, the most up-to-date chromatography laboratories are turning to integrated informatics platforms, based on a chromatography data system (CDS) and laboratory information management system (LIMS), to ensure that they are working to the highest standards of data custodianship—and can easily demonstrate this to inspectors.

Transparency and traceability

Some of the most common data integrity issues raised by inspectors relate to the way in which electronic data is managed and stored. Here, ineffective internal procedures and inadequate informatics solutions are often to blame.

Earlier this year, the FDA issued a warning letter to an Italian pharmaceutical manufacturer for recording
out-of-specification (OOS) data in an uncontrolled “preliminary” spreadsheet, while the laboratory’s official reports indicated the products had successfully passed QC testing.1 Despite the manufacturer’s claim that a second analyst had retested the OOS samples to obtain the reported results, the regulator could find no documentation or audit trail to support this.

Such incidents highlight the need for robust workflow traceability in the chromatography lab. Thankfully, though, CDS and LIMS platforms offer a convenient solution. Most CDS packages not only securely archive the chromatograms, method parameters, and sequence data associated with a particular run but also all the user interactions made within the software. As a result, every processing event can be documented in the LIMS, along with the identity of the individual who performed it, ensuring complete transparency throughout the entire analytical workflow.

Related Article: Data Integrity and Compliance

Advanced CDS platforms have the ability to version data sets, allowing users—and their supervisors—to compare changes made during processing. The software can even separate audit trails relevant to Good Manufacturing Practice so that lab managers can easily recall those necessary for review.

These comprehensive audit trails and fully searchable workflows can help limit the ability of analysts to perform “off the record” analyses and store data in “unofficial” worksheets. A search for sequences involving just a few injections or those that have been interrupted or aborted, for example, can quickly reveal actions that can subsequently be used by supervisors to further investigate unusual analysis workflows.

Consistent data analysis

When analyzing the purity of pharmaceutical products, standard operating procedures (SOPs) must be in place—and adhered to—in order to ensure reliable data, and this data must be underpinned by robust and reproducible peak detection and integration. Yet, inconsistent or incomplete data processing is a concern frequently cited by regulators.

Last year, a firm in the Czech Republic was sent an FDA warning letter highlighting serious deficiencies in the methods used by the manufacturer to assess the purity of drug products.2 Inspectors found inconsistencies in the manual integrations of peaks in chromatograms, as well as peaks that hadn’t been integrated at all. As a result, the manufacturer was required to review its existing procedures and implement suitable controls.

In an ideal world, all peak detection and integration would be handled by the CDS, but of course this can sometimes be challenging, with baseline noise, rider peaks, and other unresolved peaks adding a significant amount of complexity to the task of data analysis. Using sophisticated peak identification and integration algorithms, modern CDS platforms are helping deliver accurate and reproducible results with the minimum amount of analyst intervention, reducing or even removing the need for manual adjustments. Furthermore, intelligent run-control features built into the latest CDS solutions enable OOS injections to be automatically rerun according to defined method optimization protocols, helping analysts obtain high-quality chromatograms that can be more easily analyzed, automatically delivering more right-the-first-time analyses.

However, even with the most up-to-date informatics solutions, some user-defined integration may still be required. To help ensure that a consistent approach to workflow integration is adopted throughout the team, many chromatography laboratories are turning to enterprise-level CDS solutions, which provide smart graphical integration tools to aid the analyst in selecting appropriate parameters, and can easily identify injections that have been subject to manual interaction. With these chromatograms clearly marked, lab managers are much better placed to assess whether manual integration is being used according to the lab’s SOPs.

Open and honest analysis

Other data integrity issues relate to not recording data at the time that it’s collected, or not keeping original records. In one recent case, the FDA issued a warning letter to a manufacturer in India for data integrity breaches that included writing weight values on pieces of paper before transcribing them onto analytical worksheets and destroying the original copies.3 Another violation occurred within the packaging area, with an operator recording product quantities before the batch had even been weighed.

Leaving a gap between the point at which data is measured and when it is entered into a system leaves data open to honest errors—or worse still, deliberate manipulation. While it may seem unnecessary and even a little inconvenient to retain original paper copies, these documents are the evidence to support the authenticity of the measurement.

Integrated informatics solutions supported by LIMS and CDS can record data as it happens, leaving little room for human oversight and noncompliant behavior. The latest LIMS platforms, such as Thermo Scientific SampleManager software, are capable of recording measurements directly from the instrument, such as a weight from a balance, eliminating paper copies and human error. And because all data collected, as well as any modifications that are made to the record, are recorded with user, time, and date stamps by the software, there is no room for doubt about the integrity of the data.

Furthermore, with a scientific data management system (SDMS) integrated into the LIMS, CDS, and instrument data can be automatically archived and linked to results, ensuring data integrity across the laboratory and delivering the ability to demonstrate a very high level of data protection.

Part of the solution

Of course, robust data integrity controls will never be limited to the use of laboratory informatics software. For example, the requirement for adherence to written policies that hold individuals accountable for actions initiated under their electronic signatures, according to Title 21 of the Code of Federal Regulations Part 11, highlights the importance of staff training and the need for individuals to have a firm understanding of their responsibilities.

However, with regulators continuing to hold the industry to higher and higher standards, the leading pharmaceutical companies want to be better prepared than their competition. As part of their wider data integrity strategies, the most up-to-date chromatography laboratories are adopting integrated CDS and LIMS platforms to achieve the highest levels of data custodianship. Because when patient safety and consumer trust is at stake, the risks aren’t worth taking.


1. Department of Health and Human Services, Warning Letter, January 2017; 

2. Department of Health and Human Services, Warning Letter, October 2016;

3. Department of Health and Human Services, Warning Letter, July 2013;