Increased process understanding
Process understanding is fundamental to the whole QbD approach. Regulatory flexibility comes from showing that a given process
is well understood. According to FDA, a process is generally considered to be well understood when the following conditions
are met:
- All critical sources of variability are identified and explained
- Variability is managed by the process (8).
Product-quality attributes can be accurately and reliably predicted within the design space established for the materials
used, process parameters, manufacturing, environmental and other conditions.
Figure 2: The interrelationship between variation, process understanding, and risk reduction. (FIGURE IS COURTESEY OF THE
AUTHOR)
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Process understanding is needed not only for product and process development, but also for successful technology transfer
from development to manufacturing and from site-to-site, which includes transfer to contract manufacturing organizations (9–11).
It is very difficult, if not impossible, to successfully and effectively create, operate, improve, or transfer a process that
is not understood.
Table II: Tools for developing process understanding. (TABLE IS COURTESEY OF THE AUTHOR)
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Process variation, process understanding, process risk, and compliance are related (see Figure 2). Understanding and reducing
process variation increases process understanding, which in turn leads to reduced risk and improved compliance. QbD and its
associated statistical tools help increase the understanding of process variation. The tools for developing process understanding
(see Table II) include those of process analytical technology (PAT) as outlined below:
- Multivariate tools for experiment design, data acquisition, and analysis
- Process analyzers
- Process-control tools
- Continuous improvement
- Knowledge management
Figure 3: Tools for developing process understanding. (FIGURE IS COURTESEY OF THE AUTHOR)
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The Lean Six-Sigma tools are also useful in developing process understanding (see Figure 3) (12). A combination of some, or
all, of the PAT and Lean Six-Sigma tools may be applicable to a single unit operation or to an entire manufacturing process
and its quality assurance.
Studies critical to developing and assessing process understanding include assessment and improvement of the following:
- Process stability, capability, and robustness
- Measurement of process control, quality, and robustness
- Process models developed using statistical DOEs and other techniques to predict process performance and create the design
and control spaces
- Understanding of how the process can fail using failure-modes-and-effects analysis (FMEA).
Case study: quality by design in late-stage development
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After conducting these studies, the risks in the process and thus to the patient are better quantified and understood, thereby
enhancing compliance. The identification, characterization, analysis, and interpretation of variation in the performance of
the product, process, and analytical methods are central to these studies.
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