UV/VIS imaging-based PAT tool for drug particle size inspection in intact tablets supported by pattern recognition neural networks
Keywords:
Image analysis Machine vision Tablet inspection Particle size distributionParticle size analysis Pattern recognition neural networkAbstract
The potential of machine vision systems has not currently been exploited for pharmaceutical applications, although
expected to provide revolutionary solutions for in-process and final product testing. The presented paper aimed to
analyze the particle size of meloXicam, a yellow model active pharmaceutical ingredient, in intact tablets by a digital
UV/VIS imaging-based machine vision system. Two image processing algorithms were developed and coupled with
pattern recognition neural networks for UV and VIS images for particle size-based classification of the prepared
tablets. The developed method can identify tablets containing finer or larger particles than the target with more than
97% accuracy. Two algorithms were developed for UV and VIS images for particle size analysis of the prepared
tablets. According to the applied statistical tests, the obtained particle size distributions were similar to the results of
the laser diffraction-based reference method. Digital UV/VIS imaging combined with multivariate data analysis can
provide a new non-destructive, rapid, in-line tool for particle size analysis in tablets.
