Artificial neural networks in evaluation and optimization of modified release solid dosage forms
Апстракт
Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of ...modified release solid dosage forms.
Кључне речи:
Artificial neural networks / Modified release / Pharmaceutical developmentИзвор:
Pharmaceutics, 2012, 4, 4, 531-550Издавач:
- MDPI, Basel
Финансирање / пројекти:
Институција/група
PharmacyTY - JOUR AU - Ibrić, Svetlana AU - Đuriš, Jelena AU - Parojčić, Jelena AU - Đurić, Zorica PY - 2012 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1810 AB - Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms. PB - MDPI, Basel T2 - Pharmaceutics T1 - Artificial neural networks in evaluation and optimization of modified release solid dosage forms VL - 4 IS - 4 SP - 531 EP - 550 DO - 10.3390/pharmaceutics4040531 ER -
@article{ author = "Ibrić, Svetlana and Đuriš, Jelena and Parojčić, Jelena and Đurić, Zorica", year = "2012", abstract = "Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms.", publisher = "MDPI, Basel", journal = "Pharmaceutics", title = "Artificial neural networks in evaluation and optimization of modified release solid dosage forms", volume = "4", number = "4", pages = "531-550", doi = "10.3390/pharmaceutics4040531" }
Ibrić, S., Đuriš, J., Parojčić, J.,& Đurić, Z.. (2012). Artificial neural networks in evaluation and optimization of modified release solid dosage forms. in Pharmaceutics MDPI, Basel., 4(4), 531-550. https://doi.org/10.3390/pharmaceutics4040531
Ibrić S, Đuriš J, Parojčić J, Đurić Z. Artificial neural networks in evaluation and optimization of modified release solid dosage forms. in Pharmaceutics. 2012;4(4):531-550. doi:10.3390/pharmaceutics4040531 .
Ibrić, Svetlana, Đuriš, Jelena, Parojčić, Jelena, Đurić, Zorica, "Artificial neural networks in evaluation and optimization of modified release solid dosage forms" in Pharmaceutics, 4, no. 4 (2012):531-550, https://doi.org/10.3390/pharmaceutics4040531 . .