Integration of Near-Infrared Spectroscopy and Mechanistic Modeling for Predicting Film-Coating and Dissolution of Modified Release Tablets
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© 2015 American Chemical Society. This study demonstrates the feasibility of predicting polymeric film coating and dissolution of theophylline (active pharmateutical ingredients, API) tablets based on integration of multivariate data analysis of near-infrared (NIR) spectra and first-principal modeling. Tablets of various API strengths were manufactured and were spray-coated in a fluid bed using a mixture of ethyl cellulose and hydroxypropyl methylcellulose. Tablets were subjected in NIR spectroscopy and in vitro USP dissolution testing. The characteristic peaks of coating materials were identified via Norris Gap second derivative preprocessing of the NIR spectra of coated tablets. Principal component analysis revealed a linear relationship between PC1 score and tablet coating level. Principal component regression and partial least squares calibration models were developed to correlate the NIR spectra with the dissolution data within the time window of 10-120 min. A linear relationship between tablet initial dissolution rate and tablet coating level was found with a slope of S. On the basis of a Fickian diffusion model, a mathematical equation was derived to relate S to the diffusion coefficient (D) of the drug across the polymeric film. The mechanistic modeling of the film-coated theophylline tablet dissolution profiles suggested that the film-coated tablet dissolution process might be governed by Fick diffusion control for the initial and early release, and governed by the Hixson and Crowell first order kinetics for the late release stage. Finally, some of the current challenges and future outlook on development of such a hybrid modeling approach for characterizing and understanding film-coated tablet manufacturing and dissolution via process analytical technology implementation was discussed from both a technical and a regulatory science perspective.
author list (cited authors)
Wu, H., Lyon, R. C., Khan, M. A., Voytilla, R. J., & Drennen, J. K.