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Mathematical modelling of the drug release from an ensemble of coated pellets
Author(s) -
Caccavo Diego,
Lamberti Gaetano,
Cafaro Maria Margherita,
Barba Anna Angela,
Kazlauske Jurgita,
Larsson Anette
Publication year - 2017
Publication title -
british journal of pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.432
H-Index - 211
eISSN - 1476-5381
pISSN - 0007-1188
DOI - 10.1111/bph.13776
Subject(s) - pellets , dispersity , drug delivery , pellet , diffusion , materials science , particle size , nanotechnology , particle (ecology) , biological system , biochemical engineering , process engineering , computer science , chemical engineering , thermodynamics , physics , engineering , oceanography , geology , biology , polymer chemistry , composite material
Background and Purpose Coated pellets are widely used as oral drug delivery systems, being highly accepted by patients and with several advantages compared to single unit devices. However, their behaviour needs to be elucidated so as to improve the effectiveness of the formulations and reduce production costs. In spite of this important issue, few mathematical modelling studies have been attempted, mostly due to the complexities arising from the system's polydispersity (non‐homogeneous multiple‐unit particulate systems), which has been scarcely investigated using mechanistic models. Experimental approach A mechanistic mathematical model was developed that was able to describe the single pellet behaviour in terms of hydration, drug dissolution, diffusion and release and particle size. This model was then extended to describe and predict the behaviour of mono‐ and polydispersed ensembles of pellets. Key Results The polydispersity arising from the size and distribution of the inert core was shown to have a minimal effect on the drug release profile, whereas the thickness and distribution of the polymeric film was found to be the key parameter determining the drug release. Conclusions and Implications The mechanistic model developed, which is capable of determining the polydispersity of the drug delivery system, was able to predict the release kinetics from ensembles of pellets and to highlight the key parameters that need to be controlled in the production of pellet‐based drug delivery systems, demonstrating its use as a powerful predictive tool.