Data Integrity in the Pharmaceutical & Life Sciences Industry

Data is everywhere. No matter how big your company is or what its main services or products are, it’s likely that it relies on data for daily operations. Good record management practices, quality risk management, and robust compliance frameworks are standard procedures in industries like pharmaceuticals and life sciences. All of it is done to assure data integrity—the glue that holds together all measures and actions performed to keep the data safe, error-free, and complete. In our new article, you will learn more about data integrity in the pharmaceutical and life sciences industry and why maintaining it matters so much.

Understanding Data Integrity and Its Relevance

Data integrity refers to the concept of keeping data accurate, reliable, and consistent throughout its lifecycle. It is a critical aspect of any organization, as data integrity makes data valuable, enables informed decision-making, and ensures adherence to life sciences and pharmaceutical regulations. Data integrity isn’t a software, service, or product; it encompasses various solutions contributing to improved data maintenance and quality.

Importance of Data Integrity in the Pharma Industry

It takes just one wrong data entry, breach, or incident for patients and clients to lose your trust. Data integrity is more than just data protection; there are many reasons why it should be a top priority for anyone in pharma and life sciences. Here are a few more reasons why it is so important to maintain data integrity:

Patient safety

Accurate and reliable data is a cornerstone of the healthcare industry. Achieving effective communication between a healthcare specialist and a patient is impossible if data the healthcare provider relies on data that can be misunderstood, misinterpreted, and misused. Data integrity is a way for healthcare institutions, life science companies, hospitals, and other healthcare providers to ensure that the information their employees utilize won’t lead to incorrect diagnoses or inappropriate treatments and, instead, positively impacts patients’ health and safety.

Ensuring the quality of products and services

Data integrity equals compliance with all legislations, regulatory requirements, and standards. And when all of these boxes are ticked, it means the products and services are safe for consumers. Even if they’re not the highest quality, they at least pose no risk to anyone’s health.

When it comes to improving the quality of products and services, there is another reason why data integrity is so important. Many companies use data insights to better understand their customers and develop better engagement strategies or more customer-centric solutions. With data integrity, companies can be sure that their data is 100% accurate, empowering businesses to be even more proactive with their decisions instead of taking too long to introduce any changes and improvements. High-quality data equals better patient experience, making data integrity’s role even bigger in the pharmaceutical industry.

Compliance with regulations

Maintaining data integrity is often intertwined with regulation compliance, which is why paying attention to both is even more important. Pharmaceutical companies work with data regularly, and the best way to protect both pharmaceutical industry workers and patients is by achieving full compliance with data integrity requirements and pharmaceutical regulations. This is why it’s so important for companies to utilize proper software for storing and retrieving data, even for processes like content creation. With tools like eWizard, you can guarantee regulatory approval of all your content without needing to go through content manually every time you create something.

Proof of data quality

Data integrity is a direct reflection of data quality. Maintaining one is impossible without maintaining the other, and only if both are preserved can data be trusted and used to make informed decisions. But how can you be sure that your data is of high quality? This is why data integrity principles exist. Adhering to them guarantees that all of the data you work with is accurate, easy to understand, consistent, and properly collected and stored.

Key Principles of Data Integrity

In the 1990s, the FDA developed a list of principles of data integrity, which still serve as a framework for working with data and documenting it. These are so-called ALCOA+ principles, and although there are 5 main ones, it’s continuously expanding, and some experts and companies add more guidelines to the list. Let’s take a look at the core principles used by businesses worldwide to this day:

Attributable

Each piece of data should be attributed to the person who generated it. This information should cover when the piece of data was created and who did it. This can be done with either a physical signature or an electronic one. If every record, document, and any other form of data indicates who was involved in the generation or creation process, it becomes much easier to trace back to the original source in case of any anomalies, errors, or inconsistencies.

Legible

All data pieces are supposed to be easy to comprehend, readable, and coherent. This principle emphasizes the importance of ensuring that data remains understandable at all times, regardless of when it is accessed and by whom. If only a few individuals can read and understand the data, its utility significantly diminishes. For data to consistently remain valuable, it must be kept accurate, easy to interpret, and safeguarded against misinterpretation.

Contemporaneous

According to this principle, any data recording should be made in real time. For example, if an event occurs and needs to be documented, it should be done at the moment it happens to ensure that all findings and observations are accurate and represent a real picture of the events and their correct chronological order. With contemporaneous data documentation, it becomes possible to easily avoid any errors and inaccuracies that might come up after data recordings take place.

Original

All data should be preserved in its original form, and copies should not be used as primary sources. If any piece of data is used after its documentation or creation, it’s crucial that it be attributed to the original source. This principle helps protect data, especially in the long term, by pushing companies, researchers, and manufacturers to create conditions where it is possible to safely store data for longer periods.

Accurate

All data should always reflect real events and conditions and be complete. All data presented, recorded, and stored should be error-free and complete. At the moment of documentation, data should be recorded without any changes to prevent falsifications and misinterpretations. To achieve data accuracy, every piece of data should be verified and only modified by authorized personnel with proper access.

Note: the “+” in the ALCOA+ abbreviation stands for extended principles created after the original ones. Some of these principles are Avaiable, Enduring, Complete, and Consistent.

Possible Challenges in Maintaining Pharmaceutical Data Integrity

Most data integrity issues are caused by a bad quality culture, poor behavior at the company, bad leadership, disorganized processes, or improperly used technology. In other words, there are quite a few challenges when it comes to implementing data integrity and maintaining it, such as:

Too much reliance on legacy systems

Many companies in the pharmaceutical industry are still using old, outdated systems to store and manage data. Most businesses realize this is a problem, but due to the inability to retrain staff or invest in better software, no changes have been made. The use of legacy systems might not necessarily be a bad thing, but consider the fact that every year, the use of data continues to increase, and with outdated software, it’s going to get harder to properly store and manage data, which could potentially lead to leaks and breaches if not taken care of.

Manual processes

Manual processes take a lot of time and are more unreliable and prone to errors. This has nothing to do with the level of expertise or experience of people who work with data. The human factor plays a significant role in gathering and managing data, and with the large volumes of data today, making manual processes error-free is more challenging than ever before. Minimizing human intervention is the best way to achieve maximum data collection and analysis effectiveness, leading to fewer mistakes and safety issues.

Poor and infrequent audits

Data auditing is a process of reviewing and evaluating a company’s data to guarantee its accuracy, reliability, and compliance with modern standards and regulations. Frequent auditing allows for better control of data and quick identification of any inconsistencies, anomalies, and errors. Data integrity inspections are a normal procedure, and businesses that desire to protect both their employees and patients should be ready to conduct regular audits to monitor and verify the entire data lifecycle.

Data integrity breaches and cyberattacks

Cyberattacks are probably the biggest enemy of data integrity. Hackers who get their hands on valuable data can do a lot of damage to it and the company that owns the data, such as distributing it to third parties, tampering with it, deleting critical information, etc. This is why it’s so important to implement access controls—cyberattacks can happen to even the smallest companies, so protecting data and its integrity should be a top priority for any organization.

Lack of proper training

It is true that some, if not most, data-related activities can be automated, but it’s not possible to eliminate human intervention completely. This is why it’s crucial to properly train everyone who might have to work with the company’s data; mishandling data or neglecting safety measures when accessing corporate information that’s not meant only for inner circles can lead to serious issues, including data integrity violations.

Current Key Trends in Pharma Data Integrity

As both life sciences and pharma industries continue to evolve, data integrity changes as well. New ways to achieve data reliability are already emerging, making once unbelievable technologies a tool for battling hackers, data loss, and other dangers that pose a risk to data integrity. Let’s take a look at 3 biggest trends in pharma data integrity right now:

Blockchain technology

Blockchain is one of the best solutions for maintaining and ensuring data integrity. Here is a thing: as said before, one of the biggest challenges of data integrity is cyberattacks and data breaches. Blockchain technology almost entirely solves this problem, as when data is recorded on the blockchain, it cannot be changed even slightly without all participants agreeing to the changes. Moreover, blockchain offers much-needed decentralization, where there is no control by a single entity, which leads to increased transparency and minimizing data manipulation. With blockchain, companies can rest assured that their data is protected, properly recorded, and can be easily verified.

AI and ML technologies

Data has always been prone to errors, and with the rising amount of data in the world, it’s become harder to control data quality. With the help of artificial intelligence and machine learning, it is now possible to detect any data integrity issues at early stages, allowing for corrective action to be taken before any anomalies or errors significantly impact. Artificial intelligence can help manage data quality and safety and reduce manual workload, thereby mitigating human errors and inconsistencies and lowering the risk of cyberattacks. And when it comes to security, adopting AI and automation solutions can actually cut breach costs and improve data protection, helping companies deal with data breaches more effectively.

Data governance frameworks

According to Gartner, 80% of organizations trying to implement digital transformation will fail because they do not take a modern approach to data governance. Data governance frameworks are crucial for standardizing various data documentation and management processes, including established procedures for gathering, storing, accessing, and retrieving data. Even small businesses today are building data governance frameworks to improve data management, as nearly every modern company collects and stores data in some form.

Final Thoughts

The role of data integrity in pharma is still evolving. With Pharma 4.0, it will become much easier to integrate good documentation practices, AI-powered tools and systems, blockchain, advanced analytics, and other important technologies to safeguard data and maintain its quality at high levels.

If you are ready to learn more about maintaining data accuracy and integrity and the best tools and solutions, leave us a message, and we will contact you immediately.

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