Batch processing, quality monitoring during

Details of the specific types of apparatus need not normally be given except for nonstandard processes. A flow chart of the manufacturing operation and the in-process controls (and acceptance limits) is required. Proposals for alternative processes will need to be supported by appropriate data to show that the finished products resulting from these are consistent with the finished product specification. Certain manufacturing operations such as mixing may require additional information on quality parameters monitored during production and prior to batch release. Appropriate quality parameters should be included in the finished product specification regardless of the outcome of validation studies (e.g., content uniformity for solid and semi-solid products). 

Concurrent validation is conducted under a protocol during the course of normal production. The first three production-scale batches must be monitored as comprehensively as possible. The evaluation of the results is used in establishing the acceptance criteria and specifications of subsequent in-process control and final product testing. Some form of concurrent validation, using statistical process control techniques (quality control charting), may be used throughout the product manufacturing life cycle. 

The reactions in Steps lA, IB, and 1C were monitored by HPLC during the early runs. A peak eluting after 17 was consistently observed at 0.1 to 1 area % in the in-process HPLC analysis of step lA during several pilot runs however, it was observed at higher levels (5 to 20 area %) in later runs. Nevertheless, all of these batches afforded acceptable quality API, with no discernible difference in yields over the previous batches. 

Very often in DCS-operated batch polymer reactors the primary process variables such as pressure, temperature, level, and flow (Section 12.2.1-12.2.4) are recorded during the batch as well as the quality variables at the end of the batch. However, it may be very difficult to obtain a kinetic model of the polymerization process due to the complexity of the reaction mechanism, which is frequently encountered in the batch manufacture of specialty polymers. In this case it is possible to use advanced statistical techniques such as multi-way principal component analysis (PCA) and multi-way partial least squares (PLS), along with an historical database of past successful batches to construct an empirical model of the batch [8, 58, 59]. This empirical model is used to monitor the evolution of future batch runs. Subsequent unusual events in the future can be detected during the course of the batch by referencing the measured process behavior against this incorrective action during the batch in order to bring it on aim. 

---