Abstract

The aim of this study was to investigate the effect of the size of biodegradable microparticles (monolithic dispersions) on the release rate of an incorporated drug in a quantitative way. 5-Fluorouracil-loaded, poly(lactic-co-glycolic acid)-based microparticles were prepared with a solid-in-oil-in-water solvent extraction technique. In vitro drug release from different-sized particle fractions was measured in phosphate buffer pH 7.4. Differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and size exclusion chromatography (SEC) were used to monitor the degradation behavior of the polymer and morphological changes of the microparticles upon exposure to the release medium. Based on these experimental results, an appropriate mathematical theory was identified and used to get further insight into the underlying physical and chemical processes, which are involved in the control of drug release. Interestingly, the relative as well as the absolute release rate of the drug increased with increasing microparticle radius, despite of the increasing diffusion pathways. SEC, DSC and SEM analysis revealed that the degradation behavior of the matrix forming polymer was not significantly affected by the size of the devices and that autocatalytic effects do not seem to play a major role. Importantly, the initial drug loading significantly increased with increasing radius of the drug delivery system. Thus, large microparticles became more porous during drug release than small microparticles, leading to higher apparent diffusivities and drug transport rates. This effect overcompensated the effect of the increasing diffusion pathways with increasing microparticle radius, resulting in increased drug release rates with increasing device dimension. The applied mathematical model, considering drug diffusion with non-constant diffusivities (to account for polymer degradation) was able to quantitatively describe the observed drug release patterns. Importantly, an exponential relationship could be established between the diffusion coefficient and the initial loading of the drug. Based on this dependency, it was possible to predict the resulting drug release kinetics for arbitrary microparticle sizes in a quantitative way.

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