Online Monitoring of Pharmaceutical Materials Using Multiple NIR Sensors—Part II: Blend End-point Determination

Abstract

The effect of various blend end-point algorithms on the observed blending time of pharmaceutical powders and content uniformity of subsequent tablets was investigated for a five-component system. The blending process was monitored online, in real time, using two near-infrared sensors. Algorithms based on the standard deviation, average, and distributions of concentration predictions were tested for all major blend constituents, respectively. The potential to combine sensor outputs in the end-point decision was contrasted by the consideration of the two sensor outputs individually or simultaneously. The algorithms employed demonstrated highly variable end-points when compared with the final tablet quality, although blends were deemed to have reached homogeneity faster when only the active ingredient was considered. Some algorithms proved to be either too sensitive to local mixing and demixing phenomena or not sensitive enough, yielding results not consistent with the observed tablet content uniformity. Results showed that the choice of an end-point algorithm must be directed by the product of interest (nature of the active, therapeutic window, etc.), the particular characteristics that the delivery forms should have (immediate release, sustained release), and most significantly, the purpose of blending. A single algorithm is not expected to be adequate across all formulations. However, as the complexity of the blending process increases (multiple sensors, trends of multiple ingredients to follow, etc.) the decision process becomes more complex with not only calibration maintenance issues to consider, but also calibration transfer, relevance of the criteria for the actives, and the desired final product properties.