Determining Criticality: Process Parameters and Quality Attributes Part III: Process Control Strategies-Criticality throughout the Lifecycle

With the most recent FDA (1) and Inter-national Conference on Har-monization (ICH) guidances (2-4) advocating a new paradigm of process validation based on process understanding and control of parameters and less on product testing, the means of determining criticality has come under greater scrutiny. The FDA guidance points to a lifecycle approach to process validation (seeFigure 1).

In Part I, the author used risk analysis and applied the continuum of criticality to quality attributes during the process design stage of process validation. After using process knowledge to relate the attributes to each process unit operation, the inputs and outputs of each unit operation were defined to determine process parameters and in-process controls. An initial risk assessment was then completed to determine a preliminary continuum of criticality for process parameters.

In Part II, the preliminary risk levels of process parameters provided the basis of characterization studies based on design of experiments. Data from these studies were used to confirm the continuum of criticality for process parameters.

At this point in the process development stage, the design space has been determined. It may not be rectangular (if there are higher-order terms in the models) and may not include the entire proven acceptable range (PAR) for each critical process parameter (CPP). In fact, the design space is not defined by the combination of the PARs for each CPP, given that the full PAR for one CPP ensures the quality of the critical quality attribute (CQA) only when all other CPPs do not vary. The design space represents all combinations of CPP set points for which the CQA meets acceptance criteria.

Overall, the design space developed from process characterization study models represents a level of process understanding. Like all models, however, the design space is only as good as the data that drives the analysis. The CQAs, on average, may meet acceptance criteria, but individual lots–and samples within lots–are at risk of failure when operating at the limits of the design space. For this reason, the operational limits for the CPPs are frequently tighter than the design space. This tighter space is the last part of the ICH Q8 paradigm (2) (see Figure 2) and is called the control space, which equates to normal operating range (NOR) limits for each CPP.