TY  - JOUR
AU  - Madžarević, Marijana
AU  - Medarević, Đorđe
AU  - Vulović, Aleksandra
AU  - Šušteršič, Tijana
AU  - Đuriš, Jelena
AU  - Filipović, Nenad
AU  - Ibrić, Svetlana
PY  - 2019
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3466
AB  - The aim of this work was to investigate eects 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 eects of excipients and printing parameters on drug dissolution rate in DLP printlets two dierent 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 dierence 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.
PB  - MDPI
T2  - Pharmaceutics
T1  - Optimization and prediction of ibuprofen release from 3D DLP printlets using artificial neural networks
VL  - 11
IS  - 10
SP  - 1
EP  - 16
DO  - 10.3390/pharmaceutics11100544
ER  - 

@article{
author = "Madžarević, Marijana and Medarević, Đorđe and Vulović, Aleksandra and Šušteršič, Tijana and Đuriš, Jelena and Filipović, Nenad and Ibrić, Svetlana",
year = "2019",
abstract = "The aim of this work was to investigate eects 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 eects of excipients and printing parameters on drug dissolution rate in DLP printlets two dierent 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 dierence 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.",
publisher = "MDPI",
journal = "Pharmaceutics",
title = "Optimization and prediction of ibuprofen release from 3D DLP printlets using artificial neural networks",
volume = "11",
number = "10",
pages = "1-16",
doi = "10.3390/pharmaceutics11100544"
}

Madžarević, M., Medarević, Đ., Vulović, A., Šušteršič, T., Đuriš, J., Filipović, N.,& Ibrić, S.. (2019). Optimization and prediction of ibuprofen release from 3D DLP printlets using artificial neural networks. in Pharmaceutics
MDPI., 11(10), 1-16.
https://doi.org/10.3390/pharmaceutics11100544

Madžarević M, Medarević Đ, Vulović A, Šušteršič T, Đuriš J, Filipović N, Ibrić S. Optimization and prediction of ibuprofen release from 3D DLP printlets using artificial neural networks. in Pharmaceutics. 2019;11(10):1-16.
doi:10.3390/pharmaceutics11100544 .

Madžarević, Marijana, Medarević, Đorđe, Vulović, Aleksandra, Šušteršič, Tijana, Đuriš, Jelena, Filipović, Nenad, Ibrić, Svetlana, "Optimization and prediction of ibuprofen release from 3D DLP printlets using artificial neural networks" in Pharmaceutics, 11, no. 10 (2019):1-16,
https://doi.org/10.3390/pharmaceutics11100544 . .