Biomedical Engineering Reference
In-Depth Information
Table 1 Data demonstrating the effectiveness of a process analytical technology-based control
scheme in eliminating process variability. Adapted from Rathore et al. [
19
]
Run
Load purity (% )
PAT pooling
Pool purity (% )
Yield (% )
1
62.8
91.6
81.9
2
72.2
91.1
83.8
3
81.6
90.2
87.8
Identify TPP
Identify CQA
Risk Assessment
Define Product Design Space
Define Process Design Space
Risk Assessment
Refine Product Design Space
Process Characterization
Define Control Strategy
Risk Assessment
Filing
Process Validation
Process Monitoring
Fig. 15 Steps that need to be taken for implementation of QbD for pharmaceutical product
development. Adapted from Rathore and Winkle [
18
] and Rathore [
17
]
pooling of a process chromatography column, up to 20 % variability in the quality
of the incoming feed material results in less than 1 % variability in the product
quality of the resulting pool. If the same occurs at every step of the process,
variability can systematically be reduced or eliminated and the quality of the final
product will be very consistent.
Figure
15
illustrates the roadmap for QbD implementation and shows the key
steps that need to be taken for successful implementation of QbD for a pharma-
ceutical product [
17
,
18
]. Key steps are: identification of the product attributes that
are of significant importance to the product's safety and/or efficacy [target product
profile and critical quality attributes (CQA)]; design of the process to deliver these
attributes; a robust control strategy to ensure consistent process performance;
validation and filing of the process, demonstrating the effectiveness of the control
strategy; and finally ongoing monitoring to ensure robust process performance
over the lifecycle of the product. Furthermore, risk assessment and management,
raw material management, use of statistical approaches and process analytical
technology (PAT) provide a foundation for these activities.
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