TY  - JOUR
AU  - Đuriš, Jelena
AU  - Cirin-Varađan, Slobodanka
AU  - Aleksić, Ivana
AU  - Đuriš, Mihal
AU  - Cvijić, Sandra
AU  - Ibrić, Svetlana
PY  - 2021
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3905
AB  - Co-processing (CP) provides superior properties to excipients and has become a reliable option to facilitated formulation and manufacturing of variety of solid dosage forms. Development of directly compressible formulations with high doses of poorly flowing/compressible active pharmaceutical ingredients, such as paracetamol, remains a great challenge for the pharmaceutical industry due to the lack of understanding of the interplay between the formulation properties, process of compaction, and stages of tablets’ detachment and ejection. The aim of this study was to analyze the influence of the compression load, excipients’ co-processing and the addition of paracetamol on the obtained tablets’ tensile strength and the specific parameters of the tableting process, such as (net) compression work, elastic recovery, detachment, and ejection work, as well as the ejection force. Two types of neural networks were used to analyze the data: classification (Kohonen network) and regression networks (multilayer perceptron and radial basis function), to build prediction models and identify the variables that are predominantly affecting the tableting process and the obtained tablets’ tensile strength. It has been demonstrated that sophisticated data-mining methods are necessary to interpret complex phenomena regarding the effect of co-processing on tableting properties of directly compressible excipients.
PB  - MDPI AG
T2  - Pharmaceutics
T1  - Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients
VL  - 13
IS  - 5
DO  - 10.3390/pharmaceutics13050663
ER  - 

@article{
author = "Đuriš, Jelena and Cirin-Varađan, Slobodanka and Aleksić, Ivana and Đuriš, Mihal and Cvijić, Sandra and Ibrić, Svetlana",
year = "2021",
abstract = "Co-processing (CP) provides superior properties to excipients and has become a reliable option to facilitated formulation and manufacturing of variety of solid dosage forms. Development of directly compressible formulations with high doses of poorly flowing/compressible active pharmaceutical ingredients, such as paracetamol, remains a great challenge for the pharmaceutical industry due to the lack of understanding of the interplay between the formulation properties, process of compaction, and stages of tablets’ detachment and ejection. The aim of this study was to analyze the influence of the compression load, excipients’ co-processing and the addition of paracetamol on the obtained tablets’ tensile strength and the specific parameters of the tableting process, such as (net) compression work, elastic recovery, detachment, and ejection work, as well as the ejection force. Two types of neural networks were used to analyze the data: classification (Kohonen network) and regression networks (multilayer perceptron and radial basis function), to build prediction models and identify the variables that are predominantly affecting the tableting process and the obtained tablets’ tensile strength. It has been demonstrated that sophisticated data-mining methods are necessary to interpret complex phenomena regarding the effect of co-processing on tableting properties of directly compressible excipients.",
publisher = "MDPI AG",
journal = "Pharmaceutics",
title = "Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients",
volume = "13",
number = "5",
doi = "10.3390/pharmaceutics13050663"
}

Đuriš, J., Cirin-Varađan, S., Aleksić, I., Đuriš, M., Cvijić, S.,& Ibrić, S.. (2021). Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients. in Pharmaceutics
MDPI AG., 13(5).
https://doi.org/10.3390/pharmaceutics13050663

Đuriš J, Cirin-Varađan S, Aleksić I, Đuriš M, Cvijić S, Ibrić S. Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients. in Pharmaceutics. 2021;13(5).
doi:10.3390/pharmaceutics13050663 .

Đuriš, Jelena, Cirin-Varađan, Slobodanka, Aleksić, Ivana, Đuriš, Mihal, Cvijić, Sandra, Ibrić, Svetlana, "Application of machine-learning algorithms for better understanding of tableting properties of lactose co-processed with lipid excipients" in Pharmaceutics, 13, no. 5 (2021),
https://doi.org/10.3390/pharmaceutics13050663 . .