The aim of this work was to investigate effects of the formulation factors on tablet printability as well as to optimize and predict extended drug release from cross-linked polymeric ibuprofen printlets using an artificial neural network (ANN). Printlets were printed using digital light processing (DLP) technology from formulations containing polyethylene glycol diacrylate, polyethylene glycol, and water in concentrations according to D-optimal mixture design and 0.1% w/w riboflavin and 5% w/w ibuprofen. It was observed that with higher water content longer exposure time was required for successful printing. For understanding the effects of excipients and printing parameters on drug dissolution rate in DLP printlets two different neural networks were developed with using two commercially available softwares. After comparison of experimental and predicted values of in vitro dissolution at the corresponding time points for optimized formulation, the R² experimental vs. predicted value was 0.9811 (neural network 1) and 0.9960 (neural network 2). According to difference f₁ and similarity factor f₂ (f₁ = 14.30 and f₂ = 52.15) neural network 1 with supervised multilayer perceptron, backpropagation algorithm, and linear activation function gave a similar dissolution profile to obtained experimental results, indicating that adequate ANN is able to set out an input–output relationship in DLP printing of pharmaceutics.

Selective laser sintering (SLS) is a rapid prototyping technique for the production of three-dimensional objects through selectively sintering powder-based layer materials. The aim of the study was to investigate the effect of energy density (ED) and formulation factors on the printability and characteristics of SLS irbesartan tablets. The correlation between formulation factors, ED, and printability was obtained using a decision tree model with an accuracy of 80%. FT-IR results revealed that there was no interaction between irbesartan and the applied excipients. DSC results indicated that irbesartan was present in an amorphous form in printed tablets. ED had a significant influence on tablets’ physical, mechanical, and morphological characteristics. Adding lactose monohydrate enabled faster drug release while reducing the possibility for printing with different laser speeds. However, formulations with crospovidone were printable with a wider range of laser speeds. The adjustment of formulation and process parameters enabled the production of SLS tablets with hydroxypropyl methylcellulose with complete release in less than 30 min. The results suggest that a decision tree could be a useful tool for predicting the printability of pharmaceutical formulations. Tailoring the characteristics of SLS irbesartan tablets by ED is possible; however, it needs to be governed by the composition of the whole formulation.

Selective laser sintering (SLS) is a rapid prototyping technique for the production of 3D objects through selectively sintering powder-based layers materials by combinations of energy from the laser beam and the heated chamber of the printer. The aim of the study was to investigate the effect of laser speed and formulation factors on printability and characteristics of SLS irbesartan tablets. Physical mixtures of hydroxypropylmethylcellulose (46-91%), Candurin® Gold Sheen (3%), colloidal silicon dioxide (1%), and irbesartan (5%) were prepared. Afterward, crospovidone (1-5%), Kollidon®VA 64 Fine (20%), and/or lactose monohydrate (20-45%) were added. Sintratec Kit SLS printer (Sintratec AG, Switzerland) was used for printing tablets. The decision tree model was applied to classify printability factors. Characterization of tablets was done in terms of physicochemical, mechanical and biopharmaceutical characteristics. Correlation between formulation factors, laser speed, and printability was obtained using decision tree model with an accuracy of 80%. FTIR results revealed that there was no interaction between irbesartan and applied excipients. DSC indicated that irbesartan was present in an amorphous form in printed tablets. It was observed that laser speed had a negative effect on weight. Tuning the drug release by laser speed was possible although lactose monohydrate reduced its impact because it was required higher energy for the sintering process. Results suggest that decision tree could be useful tool for predicting the printability of pharmaceutical formulations. Tailoring characteristics of SLS irbesartan tablets by laser speed is possible, however, it needs to be governed by the composition of the whole formulation.