Disclaimer: This article contains brief, abridged, and informal synopses of remarks from a US FDA regulator during the 2018 ISPE Continuous Manufacturing Workshop proceedings in June 2018. This content has not been vetted by the agency and does not represent official guidance or policy of the FDA.
Six Sigma is defined as “a disciplined, data-driven approach and methodology for eliminating defects (driving toward six standard deviations between the mean and the nearest specification limit) in any process—from manufacturing to transactional and from product to service.”
The path to Six Sigma in pharmaceuticals, Yu said, is being driven by certain factors that are unique to the industry. These include economic factors that favor quality, and increased emphasis on performance-based regulation that can give the pharma industry greater flexibility in managing and improving quality. Continuous manufacturing and process analytical technology (PAT) play important roles; continuous improvement and operational excellence are also needed.
Economic Drivers
Quoting FDA CDER Director Janet Woodcock, Yu noted that “The fundamental problem we identify is the inability of the market to observe and reward quality. This lack of reward for quality can reinforce price competition and encourage manufacturers to keep costs down by minimizing qua lit y investments.”
This makes manufacturers vulnerable to quality issues, leading in some cases to product recalls and supply disruption.
Performance-based Regulation
Yu defined performance-based regulation as a regulatory approach that focuses on desired, measurable outcomes rather than prescriptive processes, techniques, or procedures regarding how those results are to be obtained.
At the Nuclear Regulatory Commission, for example, performance-based regulatory actions focus on identifying performance measures that ensure an adequate safety margin and offer incentives to improve safety without formal regulator y intervention by the agency.
Pharmaceutical regulation should similarly be designed to improve the performance of individual and organizational behavior in ways that protect and promote public health, he said. This will give the industry enough flexibility to manage and improve quality on its own. Advances in machine learning, big data, and other Pharma 4.0 technologies that can measure and analyze processes in real time will further encourage performance-based regulation.
Emerging Technologies
Yu talked about improving quality through PAT
and continuous manufacturing. Both will help with the move toward Six Sigma. A quality by design (QbD) approach and willingness to embrace new technology are also necessary.
The impact of Industry 4.0, which is based on cyber-physical systems (linking real objects with information-processing/virtual objects and processes via information networks such as the internet), will gradually affect pharma manufacturing in personalized medicine, artificial intelligence, and other areas. “It is coming,” he said.
“There are many new answers we have to face with emerging technology but I’m very pleased with the progress we are making,” Yu observed.
Quality by Design
QbD is a systematic approach that emphasizes product and process understanding and process control based on sound science and quality risk management. QbD is another step on the path to Six Sigma quality. Tools for QbD include prior knowledge, risk assessment, design of experiment (DOE) and data analysis, and PAT tools.
Yu explained that QbD objectives are:
- To achieve meaningful product quality specifications that are based on assuring clinical performance
- To increase process capability and reduce product variability and defects by enhancing product and process design, under- standing, and control
- To increase product development and manufacturing efficiencies
- To enhance post-approval change management
Yu compared quality by testing (QbT) and QbD: QbT has acceptance criteria based on data from one or more batches; testing must be done before they can be released. QbD has acceptance criteria based on clinical performance; testing may not be necessary to release batches.
It is not enough to comply with the FDA to achieve total quality, however. “We need to decouple acceptance criteria from process variability,” Yu noted.
Continuous Improvement and Operational Excellence
Citing the McKinsey & Company book Flawless: From Measuring Failure to Building Quality Robustness in Pharma, Yu discussed “the challenge of shifting mindsets across industry that has focused predominantly on compliance rather than on truly knowing the root causes and effects on quality issues.”
He defined a culture of quality as an environment in which employees not only follow quality guidelines but also consistently see others taking quality-focused actions, hear others talking about quality, and feel quality all around them. The four essentials for quality are: u Maintaining a leadership emphasis on quality
- Ensuring message credibility
- Encouraging peer involvement
- Increasing employee ownership and empowerment
Conclusion
Yu said that consumers and patients deserve Six Sigma quality products with minimal risks of shortages or recalls. The pharma industry can get there by following the five steps discussed in his presentation:
- The market observes and rewards quality
- Regulatory quality oversight becomes performance-based, not management-based
- Pharma develops and adopts emerging technologies
- Pharma adopts pharmaceutical QbD
- Development of continuous improvement and operational excellence
He closed his presentation by listing future directions for continuous manufacturing:
- Understand and control raw materials
- Develop modular and flexible manufacturing platforms
- Strengthen collaborations among industry, regulatory agencies, and academia
- Evolve regulatory oversight standards
