The application of Process Analytical Technologies in pharmaceutical manufacturing has been the subject of many studies. Active pharmaceutical ingredient monitoring in real time throughout the manufacturing process is commonly the target of many such implementations. The tools in place must be sensitive to, and selective of, the parameter(s) to be monitored, i.e. in the case of component quantification, they must respond to the component in question and be robust against all others. In this study, four different ingredients (riboflavin, ferrous fumarate, ginseng, and ascorbic acid) in a multi-component blend were monitored by three different tools (near infrared spectroscopy, laser-induced fluorescence and red-green-blue camera) using a full factorial design. The goal was to develop efficient and robust concentration-reading/prediction models able to assess and monitor component interference. Despite relatively high complexity of the blend studied, the three tools demonstrated reasonable specificity for the tracked ingredients (and showed advantages when combined), taking into account larger acceptance criteria typical of dietary products. In certain cases, some interference might lead to biased predictions, highlighting the importance of good calibration. The tools tested and the methodology proposed has divulged their potential in monitoring these components, despite the complexity of the 31-component blend.
Keywords: Process analytical technology; color imaging; interference; light-induced fluorescence; near-infrared; specificity.