Webinar Series: Enabling real time release testing by NIR prediction of dissolution of tablets by Co
The methodology enables real-time release testing. Tablets were made at a target drug concentration of 9% APAP, containing 90% lactose and 1% Magnesium Stearate, and at a target compression force of 24 kN. A model for predicting dissolution profiles was developed using a fractional factorial experimental design built around this targeted condition. This experimental design consisted of a 3^(4-1) fractional design resulting into a total of 27 testing conditions with additional repeated center points. Four variables were included: API concentration (low, medium, high), Blender speed (150rpm, 200rpm, 250rpm), feed frame speed (20rpm, 25rpm, 30rpm) and compaction force (8KN, 16KN, 24KN). The tablets thus obtained were scanned at-line in transmission mode using Near IR spectroscopy. The dissolution profiles were described using two approaches, a model-independent “shape and level” method, and a model-dependent approach based on Weibull’s model. Multivariate regression was built between the NIR scores as the predictor variables and the dissolution profile parameters as the response. The model successfully predicted the dissolution profiles of the individual tablets (similarity factor, f_2 ~72) manufactured at the targeted set point.
Pallavi Pawar is a post- doctoral associate in the Department of Chemical and Biochemical Engineering at Rutgers University. She received her PhD in Chemical Engineering from Rutgers University in 2016. Her area of expertise includes Real Time Release testing for tablets obtained from batch and continuous processing. She completed her Bachelor’s degree in Chemical Technology from Institute of Chemical Technology, Mumbai in 2010.
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