Elevating Lab Performance with Quality by Design
QbD centers around ongoing risk assessments of pharma processes
Twenty years ago, the US Food and Drug Administration (FDA) advocated for quality by design (QbD) principles in pharmaceutical development. In the ensuing two decades, QbD has gained momentum, leading to global changes that affect how laboratories operate.
“Over the last 20 years, we have seen a major and concerted focus in the international regulatory community on codifying risk-based and life cycle approaches across the pharmaceutical development and manufacturing landscape,” says Tina Morris, PhD, executive director at the American Association of Pharmaceutical Scientists.
What is QbD?
QbD is a data-driven approach to pharmaceutical development that incorporates the following components, as identified by the International Conference on Harmonisation of the Technical Requirements for Registration of Pharmaceuticals (ICH):1
- Identification of material attributes and process parameters that can influence product critical quality attributes (CQAs)
- Determination of the functional relationships that link material attributes and process parameters to product CQAs
- Use of enhanced product and process understanding in combination with quality risk management to establish an appropriate control strategy
“Such a systematic approach can enhance achieving the desired quality of the product and help the regulators to better understand a [pharmaceutical] company’s strategy,” ICH noted in a guideline called Pharmaceutical Development Q8(R2).2 ICH Q8(R2) connects directly to the FDA report mentioned earlier, known as “Pharmaceutical CGMPs for the 21st Century—A Risk-Based Approach,” Morris notes.3 CGMP refers to current good manufacturing practices.
How does QbD work?
The biggest tenet of QbD is that it provides ongoing, real-time assessments into every phase of pharma design and manufacturing. “A key principle of QbD is to look at pharmaceutical drug substance and drug product quality as the result of an entire life cycle trajectory, in which changes occur and should be assessed from a risk-based viewpoint,” Morris says.
Therefore, methods such as testing to determine a “go or no-go” decision do not factor into QbD. Instead, pharma lab teams use tools, such as risk assessments or software, to gather feedback and determine continuous improvement for quality measures. “The most critical [principle] to me is that you cannot test quality into the product—and I say that as an analytical person by experience,” Morris says.
“It is not enough to apply QbD to your analytics alone if your manufacturing processes do not consistently support a quality product,” she adds. “This observation goes to the core of the QbD concept of having quality built into your manufacturing and development processes by applying the same risk- and performance-based approaches.”
An important decision for lab managers is to determine whether to apply QbD as a “big bang” approach across all legacy and new products, or to only focus QbD efforts on products early in the development stage. Morris suggests the latter approach because it is complicated to insert a new principle into the life cycle of an established product. “It is always easier to build these principles in from scratch, such as for a product in early development, rather than applying them to a legacy product,” she says.
Risk assessment tools aid QbD
Given that QbD identifies process criteria that can influence CQAs, managers need to weigh various risks and how they impact workflows.
Traditional risk assessment tools can help lab managers scope out where quality pitfalls occur.
“Integral to the QbD framework is the principle of risk management,” wrote Sameer Kalghatgi, PhD, director of manufacturing for advanced therapies at Fujifilm Diosnyth Biotechnologies, in a piece published on LinkedIn in October 2023.4
“This involves identifying potential sources of variability in the process, assessing their impact on the CQAs, and devising strategies to mitigate or eliminate these risks,” Kalghatgi added.
Visual risk assessment tools are particularly effective in this regard, ICH noted. For example, a lab team could create an Ishikawa fishbone diagram (Figure 1) to identify variables that affect quality.5 “The team could then rank the variables based on probability, severity, and detectability using failure mode effects analysis (FMEA) or similar tools based on prior knowledge and initial experimental data,” according to ICH.
Software can also offer help in QbD efforts, but it is important for pharma researchers in the lab to understand what these tools are designed to do and accomplish. “Because there’s so much software, people tend to apply it and not necessarily look into what the software is doing,” said Zenaida Otero Gephardt, PhD, PE, professor emerita of chemical engineering at Rowan University, in a 2019 interview with Lab Manager about QbD.6
QbD’s future rests with data
Given the nature of science and today’s corporate culture, Morris contends that data will take a greater role in guiding QbD initiatives. Such information includes data about:
- Method development and validation7
- Performance management
- Life cycle management
“At the same time, this richness in data will also have to be used to prevent or detect data integrity issues,” Morris warned.
QbD also has a role in continuous manufacturing (CM), according to the European Medicines Agency. As opposed to the step-by-step process of batch manufacturing traditionally used in pharma, continuous manufacturing allows for greater component integration and shortens the production phase. QbD’s real-time approach to quality fits well with a constant production model.
“QbD application has been evolving into CM, which holds great promise,” says a spokesperson for the European Medicines Agency. “We have seen some CM developments already, but the uptake of CM is still progressing. Stakeholders were waiting for further regulatory guidance.”
Looking to the future, keen lab managers that lean into QbD will recognize that while the pillars of QbD are important, the mindset of merging QbD into pharma processes is a wider goal.
“QbD represents more than just a set of guidelines or best practices; it signifies a paradigm shift in how we perceive and ensure quality,” Kalghatgi concluded.
References
1. International Conference on Harmonisation of the Technical Requirements for Registration of Pharmaceuticals homepage—https://www.ich.org/page/mission
2. ICH guideline “Pharmaceutical Development Q8(R2)”—https://database.ich.org/sites/default/files/Q8_R2_Guideline.pdf
3. FDA report “Pharmaceutical CGMPs for the 21st Century—A Risk-Based Approach”—https://www.fda.gov/media/77391/download
4. “Quality by Design (QbD) in Biomanufacturing: A Comprehensive Guide”—https://www.linkedin.com/pulse/quality-design-qbd-biomanufacturing-comprehensive-kalghatgi-phd-kp80e/
5. “Risk-Based Programs, Tools, and Techniques”—https://www.labmanager.com/risk-based-programs-tools-and-techniques-28153
6. “Quality by Design for Analytical Laboratories”—https://www.labmanager.com/quality-by-design-for-analytical-laboratories-2136
7. “Ask the Expert: Method Development and Validation for Pharmaceuticals—https://www.labmanager.com/method-development-and-validation-for-pharmaceuticals-2391