Article ID Journal Published Year Pages File Type
2085473 European Journal of Pharmaceutics and Biopharmaceutics 2011 7 Pages PDF
Abstract

The aim of this work was to better understand which physicochemical processes are involved in the control of drug release from lipid implants prepared by melting and casting. Lipid implants gain steadily in importance as controlled parenteral drug delivery systems: In contrast to PLGA-based devices, no acidic microclimates are created, which can inactivate incorporated drugs. The melting and casting method offers various advantages over the commonly used direct compression technique. For example, powder de-mixing during manufacturing and highly challenging scale-up due to poor powder flowability are avoided. Importantly, broad spectra of drug release patterns can be easily provided by varying the type of lipid. The resulting drug release rates are generally lower than those of implants prepared by direct compression. This is probably due to the differences in the microstructure of the pore network of the systems. Drug or water diffusion plays a dominant role for the control of drug release, potentially combined with limited drug solubility effects, caused by the low amounts of water available within the implants. In the case of pure diffusion control, a mechanistic realistic mathematical theory is proposed, which allows for quantitative predictions of the effects of formulation parameters on the resulting drug release kinetics. Importantly, these theoretical predictions could be successfully confirmed by independent experiments. Thus, the obtained new insight into the underlying drug release mechanisms can significantly facilitate the optimization of this type of advanced drug delivery systems. This is particularly helpful if long release periods are targeted, requiring time-consuming experimental studies.

Graphical abstractThe drug release mechanisms of cast lipid implants are complex and strongly depend on the systems’ composition. In case of pure diffusion control, drug release can be successfully predicted.Figure optionsDownload full-size imageDownload as PowerPoint slide

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