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Digital technology has given the biopharmaceutical industry the ability to gather and share data instantly. But it has also created an environment where small errors can have a significant impact, forcing us to take much greater responsibility for the integrity of the data under our control. Maintaining data accuracy and consistency across the manufacturing process is critically important for this industry, both to protect patient safety and to maintain operational capabilities. 

One of the key challenges is that unlike many other industries, biopharma quality issues are difficult to detect, and often cannot be visually identified, increasing our dependence on product data. False data on product identity, quality, purity or potency has serious implications. This may cause patient injury, drug shortages, damage to corporate reputation, lost profits, and both civil and criminal liability. More difficult to quantify is the impact of lost trust in a company among customers, patients and regulators. This can be difficult if not impossible to rebuild. 

In many cases, these data breaches are not malicious. Rather they occur because the corporate culture does not prioritize good data management practices. In such organizations, employees may see nothing wrong with running a sample test multiple times in order to achieve the desired result, writing their password on a post-it note above their computer, or deleting raw data once a process is complete. All of these actions put data at risk, yet many employees think of them merely as efficiency steps. Unless someone tells them otherwise the behavior won’t change.

Such lax data integrity cultures often occur in fast growing companies that haven’t yet seen the need for rigorous controls, in organizations that have gone through multiple mergers and acquisitions resulting in disparate quality systems, or anywhere that financial success is prioritized over product quality. Regardless of the catalyst, when companies are lax about data integrity they put themselves, their brand, and their bottom-line in jeopardy. 

Fortunately, these problems can be eliminated if the organization’s leaders are willing to root out problems and replace them with formal rules, training, and a culture where data breaches are simply not allowed.

Find the problems

The first step to rooting out a lax data integrity culture is figuring out where the most glaring errors occur. To do that, companies should identify a data integrity focused team to complete an audit of the manufacturing process: 

  • Assess the environment: Focus on company values, ethical standards (e.g. zero tolerance), quality manuals, policies and procedures, and organizational design. The Management Control and Reporting Structure should be evaluated, including how success is measured, how data is reviewed and approved, and formal and informal communications relating to Quality should be examined.

  • Take a risk-based approach to conducting interviews and surveys: You want to get a sense of the corporate “culture of quality.” Assess both leadership and teams for engagement and accountability, and evaluate capacity (adequate staffing) and capability (needed skills).

  • Check for presence of controls and the extent of “workarounds” within systems. Review systems and source documents for Part 11 compliance, make sure the system was validated, examine user access rights (rules for getting in and once in, what rights do users have), and ensure that all necessary Standard Operating Procedures are in place. Conduct data reconciliation (seek individual and systemic life cycle issues) and evaluate the scope and content of the Learning Management System.

  • Incorporate search for data integrity concerns into scheduled quality system audits, and integrate and prioritize recent external and internal audits and related open corrective and preventive action (CAPA) items. The latter should include learning key processes and confirming the current status of issues. Initiate checklist driven vertical and horizontal quality system audits.

Fix the problems

Once you understand where your integrity issues are you can implement training, best practices and consequences for failure to conform. To do this you should:

  1. Establish formal processes and procedures for data collection and management. Every point in the manufacturing process has key data collection and/or management steps, and organizations need to have clearly defined protocols for how though steps are completed. These protocols should include periodic audits to verify compliance, and consequences for failure to follow them.

  2. Teach people how to follow them. Once your protocols are defined, create a formal compliance training program that covers every step in the process, why it is important, and what can happen – to the business, the patient, and the employee’s career – if these rules aren’t followed. Such training should be mandatory for all existing and new staff, and should be delivered as a mandatory annual refresher course to ensure data integrity remains top of mind.

  3. Demonstrate leadership commitment to data integrity. No amount of audits or training will matter if leaders don’t demonstrate their commitment to data quality and a zero tolerance policy for failure to follow these rules. Such commitment can’t just happen in the good times. The only way a culture of integrity will take hold, is when leaders demonstrate their commitment through difficult decisions -- i.e. they are willing to shut down an operation when test data doesn’t deliver expected results, penalize a prized employee for ignoring formal processes, and invest the necessary resources to ensure every employee is properly trained and has the necessary tools and technology to adhere to these protocols.

Changing the culture of a company is never easy, but if biopharma companies want to avoid data integrity issues, and the potential damage they can cause, such efforts are necessary to keep clients and the business safe.

This article was co-authored by Glen Potvin, Senior Director, Quality & Compliance Services at Quintiles.

For further information on this subject, please read our white paper: “Good Manufacturing Practice data integrity problems on the rise: Risks, causes and practical solutions”