Real-time monitoring

Real-time monitoring of critical quality attributes (CQA) or critical process parameters (CPP) using real-time monitoring by means of soft sensors (Mandenius et al., 2015), (Roch et al., 2016) has enormous advantages over the determination of those off-line after the unit operation. It is much faster and can assess attributes, where no dedicated sensor or analytical method is available. It also provides information in real-time if the process is within the operating range. These soft sensors are also called prediction models (e.g., (Sauer et al., 2019)). Often, we also want to monitor other attributes, which are beyond the CQA, because they are relevant for process economics, but not relevant in respect to patient safety. In a conventional process, particularly in DSP the samples are taken from a pool or intermediates and then subjected to further off-line analysis. Interventions in the upstream process do not require a fast reaction because cells grow slowly and a response after up to an hour is sufficient. Even an at-line measurement using automatic sampling devices with a 30-min lag time is considered as a “real-time” measurement because the return of the measurement is fast enough to control the process (Zhao et al., 2015). Whereas in a lot of situations in downstream processes the decision must be made within seconds, e.g., when a stream is diverted from waste to product collection. Then the decision must be made within seconds and time-consuming analytics become useless.