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Data Management and Drug Quality in Pharmaceutical Manufacturing

by Jesse Harris, Marketing Communications Specialist

In pharmaceutical manufacturing, slight variations in process can lead to significant consequences. Any deviation from set procedures can bring about massive recalls, damaged reputations, and legal liability. While it is impossible to eliminate the risk of drug quality issues completely, it is possible to reduce the chance of negative outcomes with the proper procedures and tools. Digitalized data management solutions can help detect issues earlier and allow companies to respond to problems quickly and effectively.

Unfortunately, implementing digitalized data management solutions in drug manufacturing is not an easy task. This article provides an overview of why digitalized data management in the pharmaceutical industry is challenging and explores how effective data management can enhance drug quality.

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Pharmaceutical Companies and Digitalization

The reasons why it has been challenging for the pharmaceutical industry to deploy digital data management are complicated. Chemical and biological data for assessing quality is primarily analytical data. Analytical data is typically stored in proprietary file formats that can only be read by specific software. Many of these proprietary file formats are incompatible, making it impossible to exchange data between users or work with different types of analytical data within the same software.

To avoid these interoperability problems, scientists and engineers often abstract the analytical data and move it into an unspecialized file format, such as Excel, Word, or PDFs. In 2018, C&EN and ACD/Labs assessed the data management practices in the chemical and pharmaceutical industries with a survey. It found that 62% of respondents regularly used Microsoft programs for data management and interpretation. 

While these file formats are more flexible than proprietary analytical files, they have substantial shortcomings. Files must be constantly proofread, revised, and reshared. Which file is the most up-to-date? Has the data been transcribed accurately? Any error in handling these files could lead to drug quality issues.

Analytical and chemical data in an Excel spreadsheet is also “dead,” meaning the data has been disconnected from its raw data source and the ability to interrogate it is lost. “Live” chromatograms showing the presence/absence of an impurity, for example, cannot be accessed from the spreadsheet.

Digitalized data management solutions aim to resolve these issues. Analytical data is stored in a findable, accessible, interoperable, and readable file format. Data is also linked to the raw analytical files to avoid the “live” versus “dead” data issue and simplify data forensics. 

Implementing digital data management in the pharmaceutical industry has been challenging. The 2018 C&EN and ACD/Labs survey found that only 38% of respondents said they use a data management system where data are indexed and easy to find. A January 2020 survey of “leaders in the life sciences industry” found that only 10% of respondents said digital technologies were already in widespread use.

Contract Organization Partnerships

One use case of digitalized data management that is particularly relevant to supply chain management is data sharing with contract organizations. Large pharmaceutical companies often work with contract manufacturing organizations (CMOs) to meet specific strategic goals or logistical needs. By outsourcing some tasks, large pharma companies can access niche expertise or lower costs by reducing the need for specialized equipment.

CMOs have been an essential part of the pharmaceutical industry for many years, but the market sector is experiencing a growth spurt. An April 2020 report from Fortune Business Insight estimated the global CMO market size was 92.4 billion USD in 2018 and is expected to grow to 188 billion USD by 2026. The rapid growth has been propelled by the success of CMOs based in middle-income countries such as India and Brazil.

Though CMO partnerships can be beneficial, they also give rise to challenges. Outsourcing drug manufacturing means passing work to a company that does not have the drug developers “in-house.” Any time work is transferred between organizations there is a risk of miscommunication and a need for complete data transfer.

Software is only part of the story. No technical solution will be a panacea for the data management needs of an organization. Business practice design, workflow management, and rigorous data hygiene are necessary for effective digitalized data management. Pharmaceutical companies must build relationships with their CMO partners where data is effectively managed to maintain drug quality.

CMOs play an essential role in ensuring the integrity of the global supply chain. These companies follow identical regulatory requirements as their sponsors and are well-positioned to deliver high-quality medicine to consumers. Robust data management practices and tools within a pharmaceutical organization and its contracting partners will limit the risk of drug quality issues.

Traceability

From July 2018 to March 2020, a series of recalls were issued for drugs containing Valsartan, a blood pressure medication. N-nitrosodimethylamine (NDMA), a carcinogen, was initially detected in tablets sold by Teva Pharmaceuticals, but follow-up testing found the impurity in products sold by about half a dozen companies.

This incident became public in 2018, but it appears that the roots of the controversy may have gone as far back as 2012. A leading worldwide supplier of Valsartan switched the solvent used in the synthesis. This change from the documented process led to the unintentional production of NDMA, which was then carried into the final drug product because the quality control measures were not assaying for the presence of NDMA.

While the manufacturing change was the source of the contamination, it does not explain the entire situation. Why did it take months between the first and last recall? Were companies able to audit their supply chain to identify the process change? Clearly, there was both a process chemistry and a data management problem at play.

A fully traceable supply chain would allow companies to identify every component’s origin and synthetic pathway in every batch of material in their facilities. In the case of Valsartan, it would be possible to search for any drug made with an alternative synthetic route, test it for the presence of NDMA, and remove it from the supply chain if needed. This would reduce the risk of patients receiving tainted medication and offers protection to both sponsor pharmaceutical companies and any CMO partners.

Future of Digitalized Drug Manufacturing

Digitalization in the pharmaceutical industry has accelerated rapidly in recent years, particularly during the Covid pandemic. A January 2021 report from McKinsey observed that “some experts believe the biopharma industry has moved further in the last ten months than it did in the previous ten years.” A robust data management infrastructure is the best tool to navigate disruptions and shocks to the supply chain. 

ACD/Labs has been working to facilitate this transformation. In 2017 we launched Luminata®, a decision support tool for chemistry manufacturing and control, built on the principles of digitalized data management. The software uses batch genealogy maps to allow companies to track their supply chain. By acting as a central reference, Luminata eliminates the risk of mixing up critical files and data. ACD/Labs also offers extensive support when deploying Luminata to ensure it meets your organization’s operational needs.

Modernizing data management and data sharing is a significant project, but it is essential for building an efficient and secure pharmaceutical supply chain.

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