PROCESS LIFECYCLE VALIDATION - Risk Management Applications in Pharmaceutical and Biopharmaceutical Manufacturing - page 190

parameter at the limit is relatively small. One can conclude that such param-
eters are not critical to product quality as the magnitude of minimizes the

risk of exceeding PAR.
• NOR is close to one or both limits established by PAR and the value of is
relatively small or the variability is large. In these cases, the parameter is a
potential CPP as the likelihood and risk of exceeding the PAR is higher. In
Figure 8.4, the higher variability of the parameter in scenario B compared to
A along with the smaller difference (i.e., the distance between the dashed
line and solid line limits of PAR, 1) would increase the risk and thus lead
to categorizing it as a CPP.

Using RA of process parameters and selection of CPPs is consistent with
strategies used in industry publications [16,22-24]. The risk analysis used to
select the CPPs may be influenced by the ability of the equipment and supporting
systems to control process variables (e.g., temperature, pressure, agitation, com-
pression force, etc.). The equipment's capability to control process parameters
within defined limits is typically demonstrated by commissioning and qualifica-
tion of the process equipment. Figure 8.5 shows a decision tree for evaluation
of CPPs and the role of RAs. A risk-based approach for CPPs is applicable in
both QbD and traditional approaches, but is slightly more extensive in the QbD
approach.
Other aspects of process control that are not operational parameters (e.g.,
output of an intermediate step) should be evaluated as part of the RA. These may
influence equipment qualification, method validation, and/or additional studies
that may be needed because of their importance to product quality, for example,
a performance parameter such as an in-process control (IPC) that may impact a
product CQA:

• endpoint of reaction of an API process;
• blend homogeneity of a drug product;
• level of insoluble particulate matter after filtration;
• environmental condition (e.g., temperature or humidity);
• equipment set points and configurations (nonoperational parameters but they
impact CQA);
• processing time limits, if the probable adverse consequence of exceeding a
time limit results in a risk of unacceptable final product quality, such as the
following:
• permitting an excessive reaction time in a synthetic API process when
this allows formation of an unacceptable amount of a process impurity
not adequately controlled by other means;
• delay in the processing of a mixture;
• other hold time limits that should be identified to understand process
capabilities.