TY  - JOUR
AU  - Vidović, Sara
AU  - Horvat, Matej
AU  - Bizjak, Alan
AU  - Planinsek, Odon
AU  - Petek, Bostjan
AU  - Burjak, Matejka
AU  - Peternel, Luka
AU  - Parojčić, Jelena
AU  - Đuriš, Jelena
AU  - Ibrić, Svetlana
AU  - Janković, Biljana
PY  - 2019
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3255
AB  - Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of K-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density. The process parameters identified to control the drug dissolution behavior of pellets were amount of granulation liquid, torque of dry blend, spheronization parameters, and yields after screening. To further scrutinize the dataset, an ANN model was subsequently built, incorporating 29 batches addressing drug particle size and process parameters such as torque during granulation and spheronization time as critical factors. Finally, this study demonstrates the ability of MVDA and ANN to allow prediction of the key performance drivers influencing the drug dissolution of industrially developed capsules filled with pellets and it highlights their complementary relationship.
PB  - Elsevier Science BV, Amsterdam
T2  - International Journal of Pharmaceutics
T1  - Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach
VL  - 566
SP  - 662
EP  - 673
DO  - 10.1016/j.ijpharm.2019.06.016
ER  - 

@article{
author = "Vidović, Sara and Horvat, Matej and Bizjak, Alan and Planinsek, Odon and Petek, Bostjan and Burjak, Matejka and Peternel, Luka and Parojčić, Jelena and Đuriš, Jelena and Ibrić, Svetlana and Janković, Biljana",
year = "2019",
abstract = "Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of K-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density. The process parameters identified to control the drug dissolution behavior of pellets were amount of granulation liquid, torque of dry blend, spheronization parameters, and yields after screening. To further scrutinize the dataset, an ANN model was subsequently built, incorporating 29 batches addressing drug particle size and process parameters such as torque during granulation and spheronization time as critical factors. Finally, this study demonstrates the ability of MVDA and ANN to allow prediction of the key performance drivers influencing the drug dissolution of industrially developed capsules filled with pellets and it highlights their complementary relationship.",
publisher = "Elsevier Science BV, Amsterdam",
journal = "International Journal of Pharmaceutics",
title = "Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach",
volume = "566",
pages = "662-673",
doi = "10.1016/j.ijpharm.2019.06.016"
}

Vidović, S., Horvat, M., Bizjak, A., Planinsek, O., Petek, B., Burjak, M., Peternel, L., Parojčić, J., Đuriš, J., Ibrić, S.,& Janković, B.. (2019). Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach. in International Journal of Pharmaceutics
Elsevier Science BV, Amsterdam., 566, 662-673.
https://doi.org/10.1016/j.ijpharm.2019.06.016

Vidović S, Horvat M, Bizjak A, Planinsek O, Petek B, Burjak M, Peternel L, Parojčić J, Đuriš J, Ibrić S, Janković B. Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach. in International Journal of Pharmaceutics. 2019;566:662-673.
doi:10.1016/j.ijpharm.2019.06.016 .

Vidović, Sara, Horvat, Matej, Bizjak, Alan, Planinsek, Odon, Petek, Bostjan, Burjak, Matejka, Peternel, Luka, Parojčić, Jelena, Đuriš, Jelena, Ibrić, Svetlana, Janković, Biljana, "Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach" in International Journal of Pharmaceutics, 566 (2019):662-673,
https://doi.org/10.1016/j.ijpharm.2019.06.016 . .