“Data Integrity Issues that Defeat the Public’s Trust – The Volkswagen Case and its Relevance to the Good Manufacturing Practices in the Pharmaceutical Industry:
By Anjum Shafi
The breaking news this last week that Volkswagen (VW) has been caught red-handed cheating their way through emissions tests, has much bigger implications for environmental regulators and consumers alike. VW was aware of this issue and publicly admitted on September 18 that it had fit some of its US market diesel vehicles with a software enhancement that only enabled full pollution controls when the vehicle was being subjected to official emissions testing. This came after an investigation by the International Council on Clean Transportation (ICCT) commissioned real-world emissions tests of diesel vehicles, then compared them to the lab results from official US-EPA Tier2-Bin5 tests. This news comes at the time when debates over the environment and climate change are up and among top priorities in the world including Canada.
The industrial sector is huge, investments are significant, and customer expectations are more than ever. It is mandatory for the manufacturers that their products meet the applicable standards if they have to sustain their market presence, unique position, and brand identity. We have seen product recalls for many varied reasons and due to specification failures. This is common and workable as long as the manufacturing industry, regardless of its business type, is conscious of the reputation risk and generate satisfactory accurate data for their production processes and testing services.
Our expectations towards quality have grown over the time and so the number of applicable standards. We want only a high-quality product. Food and Drug Administration (FDA) in the US has legal responsibility to allow availability of safe and efficacious products, including foods, drugs and medical devices. FDA’s actions take significant shift when a quality issue is identified at any stage during product life cycle. Strict measures are taken including product recalls, issuance of warning letters to the manufacturers or distributors, severe penalties, extensive monitoring and market restrictions.
We have seen product recalls for many varied reasons and due to specification failures. This is common and workable as long as the manufacturing industry, regardless of its business type, is conscious of the reputation risk and generate satisfactory accurate data for their production processes and testing services.
Data Integrity and Good Manufacturing Practices:
Data integrity is one of the most common problems that has existed in the manufacturing industry since years. Unsatisfactory documented practices and results have raised concerns regarding the integrity and reliability of the data generated at few of the manufacturing facilities. FDA in the US and regulatory agencies in other countries have noticed through inspections that undesirable results are ignored and not investigated, records are not kept secured and procedures for management of the electronic data do not provide evidence that it is truthful.
Human error and lack of resources cause manufacturing variations and potentially result in poor quality products and some activities leading to data manipulation.
Data generated provides the basis for key decisions for regulatory acceptance and evidence of conformance and compliance with the established manufacturing limits. This is also a common requirement that all data submitted in marketing application in the US or any country must be complete, accurate, and reliable. In this case, accuracy of the data provides confidence that the pharmaceutical industry is following Good Manufacturing Practices (GMP) and authorized products are safe and acceptable for their intended use.
Seeing the manufacturing process as a system rather than as individual parts is the key. It helps discover process interactions, dependencies and weakness. Given the complexity of organizations, system thinking benefits the organization through proper integration of various activities and strengthens collaboration between the working units.
To achieve a high degree of confidence, it is essential that the reported results are reliable and the product meets the specified quality and functional requirements under the recommended conditions of use and throughout its life cycle. To generate reliable data manufacturers need to examine all steps in the manufacturing and testing for completeness and accuracy. Seeing the manufacturing process as a system rather than as individual parts is the key. It helps discover process interactions, dependencies and weakness. Given the complexity of organizations, system thinking benefits the organization through proper integration of various activities and strengthens collaboration between the working units.
The focus should be on correct identification and accurate assessment of the critical process parameters, appropriate selection of the test methods and sampling process that affect the results considerably. These are the critical process parameters that, when vary, impact a product’s quality or functionality. Additional steps may involve developing and employing validated test methods. Selection and qualification of the process and analytical equipment further ensure that the data obtained from the source is reliable and acceptable. When this operational system is managed, operated, and monitored by suitably qualified individuals the human or machine errors are less and the results are reliable. Developing a competency matrix is a simple ready-to-access tool that helps organizations to identify the job specific competencies and build a qualified pool of their workforce. This further ensures that the management is concerned about the quality of their products and only qualified individuals have access to and influence over the manufacturing and testing results.
Lessons learned:
Like the automotive industry including Volkswagen, the pharmaceutical manufacturers acknowledge that making a false or misleading claim or statement about quality of a product or a service is a crime. Voluntary recalls of the marketed products including foods, drugs, and medical devices indicate us that the industry is aware of their responsibility and regulatory agencies are on the right path.
We acknowledge that the manufacturers aim to offer high-quality products and services but this is not enough. WV’s case is just one example where the company admitted their “cheating” action publicly mostly with the fear of competition or reputation risk but after an investigation by the regulators.This specific case does not present a safety threat to the driver on the car seat; this may also be of little importance for the sale of Volkswagen brand cars but there is a severe regulatory action. The environmental regulators have ordered the company to recall nearly 500,000 vehicles in the US. The Volkswagen CEO resigned after Dieselgate Cheating Scandal.
FDA has also discovered “cheating” actions most importantly “data manipulation” in the pharmaceutical industry. These events have raised serious concerns over integrity of the results. The companies involved in defeating the public’s trust are now facing penalties, reputation risk and have challenges in maintaining their international presence. As a first step, FDA in the US has banned the import of drugs from the facilities with data integrity issues.
What else?
Poorly managed processes, procedures and inadequate controls are among the common causes of quality variation that can be improved through tracking, proper investigation of the historical data and monitoring trends in the quality or performance of a product, such as customer complaints and product recalls. Human error and lack of resources cause manufacturing variations and potentially result in poor quality products and some activities leading to data manipulation. Causes of variation and errors can be addressed through proper selection, training and re-training of the workforce, developing strategies to overcome production capacity and with target to limited resources. Under all circumstances, management plays a vital role and has influence over resources and product quality, including design, manufacturing, procurement, supplier selection and data integrity.
In the next part of this series we will examine a few situations that raise concerns over data integrity in the manufacturing or service industry. Stay tuned …
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances and where necessary.
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Author: Anjum Shafi
Quality Auditor, Exemplar Global