In-line cosmetic end-point detection of batch coating processes for colored tablets using multivariate image analysis

Area of Science:

• Pharmaceutical Technology
• Process Engineering
• Analytical Chemistry

Background:

• Traditional cosmetic tablet coating relies on visual inspection and overage, leading to material waste and extended processing times.
• Ensuring consistent coating uniformity requires robust monitoring, especially under varying operational conditions.

Purpose of the Study:

• To develop and validate an in-line Process Analytical Technology (PAT) for automated endpoint detection in cosmetic tablet coating.
• To assess the accuracy and efficiency of the developed PAT system compared to traditional visual inspection.
• To explore the potential for process optimization and control using real-time image analysis.

Main Methods:

• Utilized an inexpensive industrial camera and lighting system for real-time tablet bed imaging within a pan coater.
• Applied Multivariate Image Analysis (MIA) combined with a stability determination strategy to compute cosmetic endpoints from acquired images.
• Evaluated the system's performance across multiple batches under diverse operating conditions.

Main Results:

• The automated system's detected endpoints showed an average deviation of only 3% from operator-identified endpoints.
• Significant reductions in coating material and processing time (over 40%) were achieved compared to traditional methods.
• Monitoring of color features enabled the identification of process abnormalities affecting coating uniformity.

Conclusions:

• The developed in-line PAT system offers a reliable and accurate alternative to manual endpoint determination in cosmetic coating.
• This technology facilitates substantial material and time savings, enhancing process efficiency.
• The system's ability to monitor uniformity and detect anomalies paves the way for optimized, automated control of coating processes.