Data integrity ensures accuracy and consistency across your laboratory system, and is essential for regulatory compliance, scientific efficacy, and ethical results. Where many labs fall short and open room for error is often not in the actual experiment or procedure design, but in the movement of the data itself.

In this article, we’ll discuss the critical points of data integrity, where you’re most likely to introduce errors, and the tools and processes that can keep your research on track and above board.

Defining Data Integrity with ALCOA

Data integrity is an essential component of the biopharmaceutical industry’s responsibility to guarantee the safety, efficacy, and quality of therapeutics, and of the FDA’s ability to protect public health. The FDA’s standard for data quality is known as ALCOA — Attributable, Legible, Contemporaneous, Original, and Accurate:

  • Attributable: Who is responsible for entering this data, and when did the action take place?
  • Legible: Data is clear and permanently accessible to others who need to use it. This often means that raw data should be stored electronically, rather than in a paper file.
  • Contemporaneous: Data is documented and logged in real time.
  • Original: Raw data should be readily available in its original form.
  • Accurate: Data is entered as-is, without mistakes.

Since ALCOA’s inception, the following four principles have been added, creating what is now known as ALCOA+:

  • Complete: No data has been removed from original records.
  • Consistent: Data is the same across access points. Anyone accessing the data should be able to see the definitive results without worry that there may be a more up-to-date record.
  • Enduring: The data is stored safely and securely so it can be accessed at any later date.
  • Available: Data is easily obtained when an authorized user requests it.

Why Data Integrity Matters

The goal of data integrity is to ensure that data is recorded as intended, preserved, and remains intact throughout its entire life-cycle, safe from unintentional changes to the information as it was originally recorded. Easy access to complete, reliable data has many critical benefits.

Scientific Efficacy

These standards help keep data secure, free of bias and safe from unintentional manipulation, far improving the chances that manufactured products will be effective and safe.

Legal Protection

The FDA issues warning letters to U.S. laboratories who fail compliance audits (other regions maintain their own set of standards — for example, EudraLex in the EU and MHRA GxP in the UK). Labs that cannot maintain data integrity are vulnerable to legal action that can be expensive, time consuming, and damaging to a company’s reputation.

Operational Efficiency

Maintaining good records gives labs a better chance to look over their operations and make changes, such as streamline workflows or eliminating waste, as needed.

Common Barriers to Compliance

What’s holding your lab back from achieving data integrity? Here are some of the most common issues we find — and our recommendations to address them.

You’re Using Legacy Processes and Tools

There’s a reason digital transformation is such a common topic these days: traditional methods and tools for data collection don’t provide the level of granularity and automation that we need to perform work efficiently and accurately.

To facilitate data integrity, a digital trail must be captured and documented throughout the entire data stream. Within the biological development platform in particular, there are numerous stages of the process that necessitate interim intervention or decision points that require accessing and possibly “re-shaping” data or events in flight. Legacy or not ‘fit-for-purpose’ informatics enterprises often do not have the underlying system architecture for efficiently tracking the resulting data changes.

Your Data is Siloed Across Different Tools

You likely use multiple instruments and pieces of equipment in the process of your work, all recording data critical to your goals. Often, though, this data isn’t easily accessed across the entire lab and may even be siloed within one particular endpoint. At best, this is inefficient. At worst, you risk introducing duplicate data sets, creating inconsistent formatting and rules, or even losing data altogether.

You’re Not Keeping Track of All the Details

Having the full context of where your data came from is essential if you need to access it at a later date — especially if the FDA audits your lab. Make sure you remember the first A of ALCOA — attributable — and keep records of who took the data, and when, where, and why.

Your Data Security Isn’t Strong Enough

An open system is vulnerable to manipulation, whether intentional or not, and while security is essential to any business, it’s especially important for labs, biopharmaceutical or otherwise. General cybersecurity practices still apply, but you may need to go further to ensure data integrity so that only particular team members are authorized to view or edit your data.

You Haven’t Properly Accounted for Data in Transit

Whenever data is replicated or transferred, the opportunity exists for data integrity to be compromised. Error checking protocols and validation procedures are typically utilized to ensure the integrity of data that is transferred or reproduced to verify that it remained intact and unaltered throughout the process. But what about data ‘in flight’? With digital transformation being a key initiative in nearly all scientific laboratories today, maintaining data integrity for data in flight is quickly becoming an area of focus for regulatory compliance measures.

Building Your Data Integrity Plan

You know the pitfalls on the way to data integrity. Here’s the simplest plan to get your lab on track and compliant.

Ensure Your Team Understands the Stakes

Fostering a culture of data integrity needs to be the first step in your plan because any solution you attempt needs to be adopted by everyone on your team. Make sure everyone — lab analysts and decision makers alike — understands how crucial compliance is, for all the reasons we’ve discussed: scientific efficacy, regulatory compliance, and operational efficiency.

Integrate and Automate

Connecting endpoints and automating workflows removes the element of human error from your process and ensures every procedure is recorded the same way every time. Labs use a few different methods to achieve this, often combining some or all to form the framework of their data integrity strategy:

  • Insourcing: Your first option is to build an in-house team dedicated to managing your data, maintaining compliance, and building out the needed infrastructure to consolidate and automate.
  • Outsourcing: You can also opt to outsource to a 3rd party agency. This can supplement an insourced model.
  • Technology: Investment in lab data automation to streamline and secure data management processes can be a cost-effective solution. Subscription based integration platforms (iPaaS) can easily connect lab data endpoints, automate workflows, and maintain audit trails of data transactions. This can maintain data integrity and compliance in an efficient manner throughout the analytical, development, and quality control lab groups. A subscription-based system is often the most cost-effective option and the easiest way to get started.

Get Started with an Integration Platform

The digital landscape of the pharmaceutical laboratory is changing dramatically with the introduction of new technologies, applications and advanced AI/ML solutions. This transition has created increasingly complex data and regulatory compliance requirements that labs struggle to address with traditional workflows and data management strategies.

Integration platforms bring data integrity compliance up to date. Scitara’s Digital Lab Exchange DLX™ cloud platform accomplishes this by addressing the unique needs of the biopharmaceutical laboratory:

  • Enables cell line development through upstream and downstream processing
  • Manages and provides calculations and logic for data in flight between instruments, applications or repositories
  • Allows you to create automated workflows that have gates for review and critical stage decision points
  • Reconstructs digital transaction records as needed
  • Tracks a clear chain of custody as data is moved, merged or transformed.
  • Extends support for GxP compliant processes to data in flight.

Combining the benefits of modern cloud-based architecture with a vendor-neutral peer-to-peer platform with robust security, compliance, and laboratory-specific functionality provides unprecedented insights into laboratory and scientific operations. Scitara DLX’s monitoring system further ensures every data transaction in the lab is captured, creating a trusted digital trail available for further analysis and decision making.

Need to address data compliance issues in your lab? Learn more about DLX here.