Data Integrity as Current Good Manufacturing Practice

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In April 2016, in the guidance document Pharmaceutical Quality/Manufacturing Standards (CGMP) Data Integrity and Compliance With CGMP, FDA began discussing its remit with a foreboding introduction stating that, “In recent years, FDA has increasingly observed CGMP [current good manufacturing practice] 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” (1). The context and consequences of those warning letters was made clear in com- mentary by Peter Zipfell, product marketing manager at Thermo Fisher Scientific, who spelled out that “... based on findings from a 2019 report on drug shortages, of 163 drug shortages in the US between 2013 and 2017, 62% of supply disruptions were associated with manufacturing or product quality problems” (2).

In that FDA 2019 Drug Shortages Report (updated February 2020), the second recommendation was to “create a rating system to incentivize drug manufacturers to invest in achieving quality management system maturity... as the market does not recognize and reward mature quality management systems. This recommendation aims to rectify this failure by suggesting the development of a system to measure and rate the quality management maturity (QMM) of individual manufacturing facilities based on specific objective indicators” (3). This new framework appears near introduction as FDA issued a white paper last month (March 2022) on the QMM program and will be holding two workshops in May to gain further input from stakeholders.

The drug shortages report goes on to say that, “A rating system could be used to inform purchasers, Group Purchasing Organizations (GPO) and even consumers about the state of, and commitment to, the quality management system maturity of the facility making the drugs they are buying. Pharmaceutical companies could, at their discretion, disclose the rating of the facilities where their drugs are manufactured. GPOs and purchasers could require disclosure of the rating in their contracts with manufacturers. This effort would introduce transparency into the market, and provide firms committed to quality management maturity with a competitive advantage, potentially enabling them to obtain sustainable prices as well as grow market share” (3). So, change is coming, and with it the requirement to tighten up on how data are collected, collated, and shared.

PAT AND DATA INTEGRITY

Because past is prologue, BioPharm International asked Edita Botonjic-Sehic, director, Global Analytics, Pall Life Sciences if the original push by FDA to promote process analytical technology (PAT) adoption was helpful in setting expectations and in creating a new tools and services ecosystem. “Yes,” Botonjic-Sehic says, “advanced technologies and computation modeling has contributed significantly to making this capability come to life. By utilizing PAT into integrated bioprocessing, better process understanding is gained, production cycle time is reduced, improvement of yield is achieved, efficiency is improved, and cost reduction is achieved by the reduction of waste and energy consumption resulting from the real-time release of a batch with improved quality.” She goes on to explain, “Biotech processes consist of several unit operations, with each unit operation serving a defined purpose. The need for appropriate control of each step and continuous evaluation of its performance is critical. To date, there are still gaps in the area of advanced analytics for the process; however, computational modeling has slowly started to contribute towards process characterization. The goal is to have both process technologies and advanced computing used in real-time for process control.” So along with the rest of the world, pharmaceutical manufacturing is becoming a digital undertaking.

When asked if increasing compliance and validation requirements lead to more processes and documentation burden, Botonjic-Sehic responded that, “Data driven frameworks and transformation to digitalization will lead to a new future state. There are still many challenges in bringing technological innovation and advancement due to lack of adoption and change in processes ... FDA has been very much involved with the industry to support the adoption of the advancements in the process. It may seem as if it is complex at this given moment; however, the ultimate goal is to make the process and filing seamless and putting in the effort upfront is a necessity in order to make the future of manufacturing much easier.”

MEASURING COMPLEX PRODUCT QUALITY ATTRIBUTES

For the future of the industry, does biological complexity require a more diverse set of scientists and wider array of team members? Botonjic-Sehic consid- ers a “lack of advanced process analytical technologies capable of measuring product quality attributes in real-time [as] a change today; however, Pall Life Sciences and many other companies have been investing in making these technologies available to customers that support biotherapeutics manufacturing. Computational techniques supporting predictive outputs of the process are also at the early stages; however, we have seen a much larger uptake of such innovations being utilized in the bioprocess. Integration of process technologies and advanced analytics will support Industry 4.0 and provide bioprocessing manufacturing with real-time process monitoring and control. As far as scientific experts— many of the process analytical scientist and chemometricians (data scientist) come from small molecules manufacturing industry and there is a growing need for these skills sets to move forward faster as we progress in providing advanced technologies for biomanufacturing processes,” concludes Botonjic-Sehic.

This coincides nicely with comments from Dr. Natalia Vtyurina, senior quality assurance officer at HALIX B.V., who, in a blog post for the International Society for Pharmaceutical Engineering (ISPE) emphasized that in every highly regulated industry there are specific rules and regulations that when embedded in guidelines, help shape both culture and data collection while streamlining future planning and optimization. Dr. Vtyurina points out that “a data integrity (DI) maturity program uses standard rules and procedures that will take the organization through all aspects of DI. It will support your organization towards a safe environment and a strong culture by properly managing data, ensuring high-quality standards, and improving efficiency. On top of ensuring a high-quality product, your business’s core processes’ costs will be significantly reduced. A DI program will also help you to identify, remediate, and manage potential risks to DI” (4).

To round out the discussion, BioPharm International asked Stefan Holzner, vice president R&D, Pall Life Sciences, if momentum toward modular manufacturing with continuous adjustments and improvements creates a premium for real-time feedback, and has the industry hit a rate limiting bottleneck or bottlenecks. Stefan’s position is that there is a need to get real-time data and make it actionable. “This requires state-of-the-art sensors to cover a wide array of parameters (including different types of metabolites etc.). The data needs to be transferred into insights to make them actionable. Multivariate data analysis could be a tool to achieve this. However, it does (seem) like we have reached a bottleneck as new sensors are required that enable better real time data as well as the proper ecosystem to process this data in real time and allow insights to act accordingly,” Holzner says. Some growing pains allows us some room to grow into, it seems. Data are now how business performance is officially measured and recorded. The sooner DI is controlled for, and firmly established, the earlier organizations will reap its rewards.

REFERENCES

1. FDA, Guidance to Industry, Data Integrity and Compliance With cGMP (CDER, Rockville, Md., 2016).
2. P. Zipfell, “Strengthening Data Integrity and Traceability,” PharmTech.com, March. 19, 2021.
3. FDA, Drug Shortages–Root Causes and Potential Solutions, 2019, updated Feb. 21, 2020 (FDA, 2019).
4. N. N. Vtyurina, “Why is Data Integrity Critical in the Pharma Industry,” iSpeak Blog, Pharmaceutical Engineering, ISPE.org, July 7, 2021.

About the authors

Chris Spivey is the Editorial Director of BioPharm International.

Article details

BioPharm International
Volume 35, Number 5
May 2022
Pages: 42-43

Citation

When referring to this article, please cite it as C. Spivey, “Data Integrity as Current Good Manufacturing Practice” BioPharm International 35 (5) 42-43 (2022).