Why Pharmaceutical Data Integrity Is More Important Than Ever

With radical pharmaceutical industry changes in the air, the importance of data integrity and the steps the pharmaceutical industry must take are clear.

By Ashley Ruth, Senior Consultant, Analytical Services, BioTechLogic, Inc.

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The pharmaceutical and biopharmaceutical industries must give immediate and strategic consideration to data integrity practices for two critical reasons:

  1. increased attention to data integrity shortcomings by global regulatory agencies and
  2. the possibility of a less stringent regulatory environment.

To understand the pressing ramifications of the data integrity issue, we must remind ourselves that data is both the backbone of CGMP compliance and the fuel of the digital economy. In the pursuit of increased efficiency, digital approaches are being used for risk reduction and greater innovation in pharmaceutical lifecycle processes—from discovery to commercial manufacturing—and must continue to be further leveraged. Additionally, data must become less siloed and flow much more seamlessly throughout pharmaceutical organizations at various stages of the product lifecycle. However, just as if gasoline in a car engine is contaminated, it will damage and/or cease the engine, the same is true for “digital fuel.” Correct and uncorrupted data must flow through a pharmaceutical organization so that correct and reliable decisions can be made.

Even without sophisticated digital data management considerations, data integrity of even the most basic data systems must be assured to ensure compliance.

REGULATORS INCREASED ATTENTION TO DATA INTEGRITY

For several years, the FDA and other global regulatory bodies have emphasized the importance of accurate and reliable data in assuring drug safety and quality. However, in tandem with increased digital sophistication and the role of global manufacturing partners, data integrity violations have been on the rise.

As a reflection of the importance of this issue, in April, 2016, the FDA released draft guidance, “Data Integrity and Compliance With CGMP Guidance for Industry.” Within the guidance itself, the FDA notes the trend of increasing data integrity violations.

The guidance states, “In recent years, FDA has increasingly observed CGMP violations involving data integrity during CGMP inspections. This is troubling because ensuring data integrity is an important component of industry’s responsibility to ensure the safety, efficacy, and quality of drugs and of FDA’s ability to protect the public health. These data integrity-related CGMP violations have led to numerous regulatory actions, including warning letters, import alerts, and consent decrees.”

The phrase “data integrity” often conjures the image of intended and dishonest manipulation of data to achieve some benefit or avoid negative consequences. While purposeful data adulterations do occur, many data integrity violations are not purposeful and are a result of improper training, ineffective SOPs, corrupt systems, or lack of clarity within the regulations themselves. The CGMP framework recognizes that technologies and approaches evolve over time which reflects advances in innovation. Therefore, regulations and guidance are created with built-in flexibility to accommodate these changes. However, often these accommodations result in a lack of clarity.

POSSIBILITY OF A LESS STRINGENT REGULATORY ENVIRONMENT

President Trump has vowed to overhaul the FDA and sharply reduce the regulatory burdens of the current drug approval system. In fact, arguments have been made, by people associated with the administration, to completely eliminate pre-market approval clinical trials that are currently required to demonstrate drug efficacy and safety.

While eliminating clinical trials is a very extreme position and is unlikely to happen, the Trump administration is decidedly moving in the direction of sharply decreased regulation. A regulatory structure that is less burdensome does not eliminate the need for the development and production of safe and effective drug products. In addition, pharmaceutical companies need to demonstrate the value of a new drug to payers to ensure reimbursement and, therefore, the marketability of a new drug.

Data—which is the fuel of decision making, continuous improvement, quality, and the demonstration of clinical value must hold high levels of integrity regardless of the regulatory environment. However, strong arguments can be made that the importance of data will radically increase within a less regulated environment. The highest levels of data integrity will be needed if some regulatory checks and balances that have historically protected patients and facilitated marketability of a drug are removed.

NEEDED DATA INTEGRITY APPROACHES FOR THE PHARMACEUTICAL INDUSTRY

Given the factors that are bringing data integrity to the forefront of pharmaceutical industry priority, how should a pharmaceutical company approach the effort?

Setting regulatory requirements aside, data serves two critical functions within pharmaceutical organizations: efficiency of innovation and assurance of quality.

“The value of the economy today, and even more so tomorrow, lies in data, often called the 21st-century oil. But the comparison isn’t entirely apt: oil companies in the 20th century often had the monopoly, whereas we’ll need a different model for data,” stated French Secretary of State for Digital Affairs, Axelle Lemaire.

Modeling, sequencing, continuous improvement, root cause analysis, and many other areas of pharmaceutical development and manufacturing should be as automated as possible and continuously improved. High quality data that is not organizationally or functionally siloed is required to accomplish these ends.

From a quality standpoint, data integrity is a critical component of a company's Quality System. Quality data provides the basis for the confidence that the company uses correct data to operate in accordance with regulatory requirements. In addition, it is high quality data that provides the basis for product, process, true product quality understanding, and determination.

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