QbD roadmap
A typical QbD exercise is to outline the process flow diagram and construct the process mapping to identify the key process
input variables (KPIVs) and key process output variables (KPOVs). The relative importance of the KPIVs and KPOVs were assessed
with a cause-and-effect (C&E) matrix. The KPOVs with the highest scores (e.g., in the top 20th percentile) were considered
to be CQAs for which process specifications needed to be defined. The C&E matrix result showed that the blending uniformity
before and after the addition of MCT was critical. The blend uniformity before MCT addition determined the blend uniformity
after MCT addition. Therefore, there was only one CQA in the blending process. The detection sensitivity needed to determine
the blend uniformity was based on visual detection by obtaining a blend drawdown. Visual detection under magnification, which
can further ensure uniformity quality, is recommended. From the C&E matrix, the KPOVs with high scores (i.e., raw material
charge and sample checking for blend uniformity) were defined as the CPPs. It is important to control the CPPs to achieve
desirable quality. A failure mode effect analysis (FMEA) was performed based on the CPPs identified.
Coating QbD
Based on the FMEA assessment, the risk-priority number (RPN) was generated, and the raw-material charge had a high RPN. Corrective
action plans were developed to control the raw-material charge procedure and ensure accuracy and execution of the production
procedure. Similarly, the drawdown step was also a CPP. The RPN was not as severe compared with the raw material charge step,
and a process-control procedure was also proposed. The C&E assessment indicated a completely dispersed Spectrablend II pink
in water was a CQA. This CQA could be controlled by visual testing. All KPIVs were CPPs. The coating process had six process
variables (i.e., coating temperature, spray rate, pan speed, atomization pressure, AIR pattern, and air flow).
Relative coating effect
The C&E assessment suggested coating efficiency, drying efficiency, and coating quality were the CQAs. Drying efficiency is
a visual observation during coating and is dependent on the operator's experience. Coating quality can be quantitatively measured
by colorimetry and other rheological tests. The C&E assessment suggested all six KVIPs had a significant effect. A FMEA assessment
was performed.
FMEA for coating process
Tablet charge, air flow, coating temperature, spray rate, and pan speed needed to be controlled. Tablet-charge amount should
be maximized according to the pan-coater design. Air flow was correlated to coating temperature and should be adjusted to
the optimal setting to stabilize the coating temperature. Pan speed should be adjusted to have an ideal flow without excessive
tumbling to cause tablet or coating chipping. The coating temperature and spray rate effect were more subjected to the coating
material as previously described.
Conclusion
Critical quality attributes, such as color shade, gloss, slip, and adhesion, can be controlled by proper material and process
specification. A QbD approach is a practical tool to understand and control quality and the process.
Eric Van Ness* is technical support manager, Beverly Schad is technical sales manager, Thomas Riley is formulations manager, and Brian Cheng is formulations scientist, all at Sensient Pharmaceutical Coating Systems, Saint Louis, MO, tel. 314.286.7135, Eric.VanNess@sensient.com
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*To whom all correspondence should be addressed.
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