A validation of discrete-element model simulations for predicting tablet coating variability.

Autor: Sivanesapillai R; Bayer AG, Chemical and Pharmaceutical Development, Wuppertal, 42117, Germany., Ehrig A; Bayer AG, Engineering and Technology, Leverkusen, 51368, Germany., Nogueira LW; Ansys do Brasil LTDA, Florianópolis, Brazil., Vukosavljevic B; Bayer AG, Chemical and Pharmaceutical Development, Wuppertal, 42117, Germany., Grilc B; University of Ljubljana, Faculty of Pharmacy, Department of Pharmaceutical Technology, Ljubljana, 1000, Slovenia., Ilić IG; University of Ljubljana, Faculty of Pharmacy, Department of Pharmaceutical Technology, Ljubljana, 1000, Slovenia., Bharadwaj R; ANSYS Inc., Canonsburg, United States. Electronic address: rahul.bharadwaj@ansys.com., Sibanc R; Bayer AG, Chemical and Pharmaceutical Development, Wuppertal, 42117, Germany. Electronic address: rok.sibanc@bayer.com.
Jazyk: angličtina
Zdroj: International journal of pharmaceutics [Int J Pharm] 2023 Jul 25; Vol. 642, pp. 123109. Date of Electronic Publication: 2023 Jun 07.
DOI: 10.1016/j.ijpharm.2023.123109
Abstrakt: Achieving an even coating distribution on tablets during the coating process can be challenging, not to mention the challenges of accurately measuring and quantifying inter-tablet coating variability. Computer simulations using the Discrete Element Method (DEM) provide a viable pathway towards model-predictive design of coating processes. The purpose of this study was to assess their predictivity accounting for both experimental and simulation input uncertainties. To this end, a comprehensive set of coating experiments covering various process scales, process conditions and tablet shapes were conducted. A water-soluble formulation was developed to enable rapid spectroscopic UV/VIS analysis of coating amounts on a large number of tablets. DEM predictions are found to lie within the experimentally inferred confidence intervals in all cases. A mean absolute comparison error of 0.54 % was found between model predictions of coating variability and respective sample point estimates. Among all simulation inputs the parameterization of spray area sizes is considered the most significant source for prediction errors. However, this error was found significantly smaller in magnitude compared to experimental uncertainties at larger process scales underlining the value of DEM in the design of industrial coating processes.
Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rahul Bharadwaj and Leon White are employees at Ansys Inc. and Ansys do Brasil LTDA, respectively, and contributed to the coating variability prediction worklow. The remaining authors have no conflicts of interest to declare.
(Copyright © 2023 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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