2.Process monitoring
P-diagrams allow development teams to produce a comprehensive list of the desired measurement systems for monitoring all three types of variables: inputs, outputs and noise. The aim of the process monitoring stage is to develop and evaluate appropriate measuring analytical systems to measure the process parameters and critical quality attributes shortlisted in the process mapping step.
Having identified which parameters need to be measured, the next step is to identify the measuring system key requirements for each of the parameters, to help identify the most suitable method available. We discuss two key tools used in the process monitoring stage, including the fit-for-purpose approach and the decision matrix.
Fit-for-purpose approach
When defining requirements and developing a measuring system, a useful notion to follow is the fit-for-purpose approach. The idea of fit-for-purpose is to consider the intended use of the data acquired from the developed method when defining requirements, developing and validating the measuring system.
For example, a measurement system used to monitor CQAs in real-time based on which CPPs are adjusted to affect the final product, should be fully validated. Whereas a measurement system used to identify critical process parameters during the early stages of process development may not require the same stringent validation.
By following this approach, development teams can guard against over-investing in a method that might have limited utility. The following is a list of questions that can help when defining key early-stage-requirements, using the fit-for-purpose approach:
- What is the system measuring? Is it measuring the critical parameter/quality attribute directly or an orthogonal metric?
- How should it be measured? Consider interaction with the sample. Should it be off-line, in-line, at-line, on-line or non-contact and non-destructive? Should it be real-time, or taken at fixed intervals? Accurate in-line, on-line and non-contact measurements are the preferred options for real-time monitoring and dynamic control.
- Under what conditions? What environmental conditions would the system operate under (temperature/humidity/pressure) and are there any chemical or sub-system compatibility issues? This is an opportunity to consider any user dependent or external noise factors. For example, sensors interfaced directly to a bioreactor must be sterilisable and should not be affected by fouling or interfere with the medium.
- How well should it be measured? Describe the desired performance metrics in terms of minimum sensitivity (the smallest change in the metric that can be detected), maximum tolerated error (systematic or random deviation from the true metric value) and range (the range of change to detect). Some of the key properties to evaluate for a measurement system include accuracy, precision, linearity, stability and capability.
- Other considerations? Think of any constraints such as GMP compatibility, size, shape and cost.
For many of these requirements, there will be numerous measurement options to select from, including the option to buy and adapt , or make custom measuring systems. In the early stages of process development, where agility is key, buying off-the-shelf solutions is typically the preferred option. However, it is often the case that there are no off-the-shelf solutions capable of satisfying all the desired requirements, meaning adapting these or making custom solutions is worth exploring early on.