Rapid and reliable tailoring of the dose of controlled release tablets to suit an individual patient is a major challenge for personalized medicine. The aim of this work was to investigate the feasibility of using a fused deposition modelling (FDM) based 3D printer to fabricate extended release tablet using prednisolone loaded poly(vinyl alcohol) (PVA) filaments and to control its dose. Prednisolone was loaded into a PVA-based (1.75 mm) filament at approximately 1.9% w/w via incubation in a saturated methanolic solution of prednisolone. The physical form of the drug was assessed using differential scanning calorimetry (DSC) and X-ray powder diffraction (XRPD). Dose accuracy and in vitro drug release patterns were assessed using HPLC and pH change flow-through dissolution test. Prednisolone loaded PVA filament demonstrated an ability to be fabricated into regular ellipse-shaped solid tablets using the FDM-based 3D printer. It was possible to control the mass of printed tablet through manipulating the volume of the design (R(2) = 0.9983). On printing tablets with target drug contents of 2, 3, 4, 5, 7.5 and 10mg, a good correlation between target and achieved dose was obtained (R(2) = 0.9904) with a dose accuracy range of 88.7-107%. Thermal analysis and XRPD indicated that the majority of prednisolone existed in amorphous form within the tablets. In vitro drug release from 3D printed tablets was extended up to 24h. FDM based 3D printing is a promising method to produce and control the dose of extended release tablets, providing a highly adjustable, affordable, minimally sized, digitally controlled platform for producing patient-tailored medicines.

Oxidative stress and the excess of free radicals accelerate the ageing process of human skin. The application of skin cream with antioxidant compounds could reduce the damage caused by free radicals. In this work we studied two types of skin creams with extracts from aronia (Aronia melanocarpa), elderberry (Sambucus nigra) and bilberry (Vaccinium myrtillus) because of their high content of anthocyanins, i.e. strong natural antioxidants. The 2,2diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability of the skin creams with berry extracts were studied with ESR spectroscopy. The artificial neural networks were applied to optimize the berry extract concentration and storage time for oil-in-water and water-in-oil creams. Based on experimental results chokeberry and elderberry extracts in oil-in-water cream base revealed higher DPPH radical scavenging ability than in the corresponding water-in-oil. Artificial neural networks predicts maxima of DPPH radical scavenging for 1-week stored elderberry (2.23 mg DPPH/g) and 1-week stored chokeberry (5.84 mg DPPH/g) and bilberry (5.26 mg DPPH/g) 0.76% extracts in oil-in-water creams. The maxima of DPPH radical scavenging for water-in-oil creams were predicted for 6-week stored 0.8% aronia extract, freshly prepared 0.76% bilberry extract and 1-week stored 0.56% elderberry extract. The artificial neural networks predicted values are in good agreement with the experimental values. DPPH-EPR could be combined with artificial neural networks to optimize the extract concentration, and the type of cream base as well as to predict the effect of storage based on a limited number of experiments and samples.