The adoption of quality by design (QbD) in the pharmaceutical industry is an evolving process. To faciliate the implementation
of QbD, the US Food and Drug Administration launched a pilot program in 2005 to allow participating firms an opportunity to submit chemistry, manufacturing, and controls
(CMC) information demonstrating application of QbD. Chi-wan Chen, deputy director of the Office of New Drug Quality Assessment
(ONDQA) at FDA's Center for Drug Evaluation and Research, recently outlined some key lessons learned from the CMC pilot. Chen
described the progress of the initiative at Regulatory Watch 2007, a conference held in September by the Drug, Chemical, and Associated Technologies Association (Robbinsville, NJ) in conjunction with Pharmaceutical Technology.
FDA launched the CMC pilot in July 2005 to evaluate the utility of comprehensive Quality Overall Summary as part of a new
drug application (NDA) and to implement new concepts such as QbD, design space, and real-time release contained in the International
Conference on Harmonization's guidances, Q8 Pharmaceutical Development and Q9 Quality Risk Management and the FDA process analytical technology (PAT) guidance PAT:A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance.
Nine original new drug applications (NDAs) and two supplemental NDAs were accepted into the pilot program. As of Sept. 19,
2007, seven of these NDAs had been submitted, of which six were approved and one was under review. FDA expects to receive
the remaining four NDAs in the next six months, with the goal of concluding the pilot by the end of 2008, says Chen.
The pilot has allowed FDA and industry to work together to explore various ways to implement ICH Q8, ICH Q9, and FDA PAT guidances.
Chen began by outlining FDA's view of QbD. "QbD is a systematic approach to product and process design and development,"
she says. QbD involves the following key elements:
- Target the product profile
- Determine critical quality attributes (CQAs)
- Link raw material attributes and process parameters to CQAs and perform risk assessment
- Develop a design space
- Design and implement a control strategy
- Manage product life cycle, including continual improvement.
Chen then shared some observations made from the CMC pilot as they relate to CQAs, risk assessment, design space, and control
strategy. The lessons learned from the CMC pilot are being considered in the revision of ICH Q8.
The revision of ICH Q8, or ICH Q8 (R1), is an annex to ICH Q8. It provides further clarification of key concepts outlined
in the core guideline and describes the principles of QbD. Q8(R1) was signed off by the ICH Expert Working Group as a draft
(or Step-2) guidance on Nov. 1, 2007, and will soon be published for public comment in each ICH region (Europe, Japan, and
the United States).
Critical quality attributes
Chen described some observations on CQAs. These were:
- Definition of "critical" varied
- Most of the applications related CQAs to those attributes that have a direct impact on product quality, safety, and efficacy
- Most applications included CQAs for the drug product, but only some applications included CQAs for the drug substance
- Some applications considered the drug substance's property affecting downstream manufacturing as a CQA
- Most applications related critical process parameters to CQAs
- Most applications considered a process parameter noncritical if well controlled or well within the design space.
"A question arises on whether a process parameter may be considered noncritical if it is well controlled or well within the
design space," says Chen. "This issue is being considered more fully in the revised ICH Q8," she says.
Chen noted that several applications in the CMC pilot included risk assessments, especially for the drug product by linking
input and process variables to CQAs. Tools used in the risk assessment included the Ishikawa or fishbone diagram, failure
mode effect analysis (FMEA), and Pareto analysis. An Ishikawa or fishbone diagram is used to identify all potential variables,
such as raw materials, compression parameters, and environmental factors, which can have an impact on a particular CQA, such
as tablet hardness. A FMEA can then be used to rank the variables based on risk (i.e., a combination of probability, severity,
and detectability) and to select the process parameters with higher risks for further studies to gain greater understanding
of their effects on CQAs. The risk assessment is amassed by a multidisciplinary team based on prior knowledge and experiments.
"It is important to provide a systematic risk analysis of how raw materials, process steps, and process parameters affect
product quality," says Chen. "One of the points to consider in risk assessment," she says "is to provide an explanation when
citing prior experience as the basis for assigning risk. The risk assessment that leads to the development of a comprehensive
control strategy to reduce risk to product quality should be described, and the risk reduction and control should be discussed
for changes that occur inside or outside the design space, " she says.
"Risk assessment can provide increased assurance to quality," emphasized Chen, because "process variability is identified
and its linkage to product CQAs is understood; process and product controls reduce the impact of variability; and quality
product will continue to be made when movement within the design space occurs in the future."
A risk assessment also is important for effective communication between FDA and industry and for intracompany communication
(such as between research/development and manufacturing and among multiple manufacturing sites), says Chen. "And within FDA,
risk assessment allows for a dialogue between pre-and post-marketing review functions and among review, compliance, and field
Chen also shared some observations from the CMC pilot for design space. "Most applications included a design space for the
drug product, but only some included a design space for the drug substance," she says. Most of the applications included design
spaces for process parameters, but only some included design spaces for formulation components (i.e., excipients and drug-substance)
properties. Methods for determining design space included: one-variable-at-a-time experiments, statistically designed experiments,
and modeling approaches. Methods for presenting design space included graphs (surface-response curves and contour plots),
linear combination of parameter ranges, equations, and models.
In establishing and presenting a design space, Chen identified certain key points to consider:
- Effect of formulation-component properties on process performance and product quality studied
- Multivariate interactions examined
- Supportive mathematical models used, as appropriate
- Scale-up and equipment issues considered
- Effect of operation or site change considered
- Uncertainty addressed with risk management.
Control strategy also is a critical element of QbD, and Chen outlined some points for potential applications to consider when
establishing a control strategy. "The control strategy should be comprehensive," she says, "and should include raw-material
properties and intermediates, in-process controls, and specifications for the drug substance and drug product. It is also
important that the strategy demonstrate control of excipient properties based on the understanding of their effects and not
relying solely on compendial standards," she says.
Other points to consider are:
Chen mentioned that both industry and FDA are "on a learning curve" as it relates to the acceptance criteria for real-time
release. She pointed out, however, real-time release provides manufacturing flexibility and increased quality assurance and
is a more modern approach to manufacturing and controls.
- Better use of process knowledge and understanding in setting specifications
- More meaningful sampling for drug-product testing
- Experience needed in setting real-time release specifications.
"More scientific information was shared with FDA in the pilot NDAs," says Chen, and "elements of QbD were applied and risk-based
regulatory decisions were enabled." She concluded that the pilot benefited FDA and industry in implementing QbD, although
challenges (e.g., cultural change, knowledge, and resources) remain for both.