A laser-induced breakdown spectroscopy-based analytical methodology is developed to study tablet coating variability in pharmaceutical tablets. The method quantifies the amount of coating on a tablet by assigning an average coating thickness score to it. When tested using samples with different amounts of coating, the coating thickness scores showed direct correlation to the weight gain of the tablet, hence validating the analytical method. The relative significance of the processing parameters and the components of variability were computed using statistical techniques. The sampling frequency of laser shots was found to have no significant effect. The effect of the position of the laser pulse on the tablet surface was found to be significant; however, it was determined that this effect was due to the tablet curvature, which resulted in the laser optical path to intersect the coating diagonally. The variability between batches (lots) manufactured under the same processing conditions was not significant. The largest avoidable source of variability was the tablet-to-tablet component, possibly indicating the inadequate mixing performance of the coating device.
Abstract. A combination of analytical and statistical methods is used to improve a tablet coating process guided by quality by design (QbD) principles. A solid dosage form product was found to intermittently exhibit bad taste. A suspected cause was the variability in coating thickness which could lead to the subject tasting the active ingredient in some tablets. A number of samples were analyzed using a laserinduced breakdown spectroscopy (LIBS)-based analytical method, and it was found that the main variability component was the tablet-to-tablet variability within a lot. Hence, it was inferred that the coating process (performed in a perforated rotating pan) required optimization. A set of designed experiments along with response surface modeling and kriging method were used to arrive at an optimal set of operating conditions. Effects of the amount of coating imparted, spray rate, pan rotation speed, and spray temperature were characterized. The results were quantified in terms of the relative standard deviation of tablet-averaged LIBS score and a coating variability index which was the ratio of the standard deviation of the tablet-averaged LIBS score and the weight gain of the tablets. The data-driven models developed based on the designed experiments predicted that the minimum value of this index would be obtained for a 6% weight gain for a pan operating at the highest speed at the maximum fill level while using the lowest spraying rate and temperature from the chosen parametric space. This systematic application of the QbD-based method resulted in an enhanced process understanding and reducing the coating variability by more than half.
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