Combined application of mixture experimental design and artificial neural networks in the solid dispersion development
Abstract
This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus (R)-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus (R)-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q(10)) and 20 (Q(20)) min, wherein ANN model exhibit better predictability on test da...ta set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.
Source:
Drug Development and Industrial Pharmacy, 2016, 42, 3, 389-402Publisher:
- Taylor & Francis Ltd, Abingdon
Funding / projects:
- Advanced technologies for controlled release from solid drug delivery systems (RS-34007)
- Federal Republic of Germany
DOI: 10.3109/03639045.2015.1054831
ISSN: 0363-9045
PubMed: 26065534
WoS: 000369854600005
Scopus: 2-s2.0-84964228106
Collections
Institution/Community
PharmacyTY - JOUR AU - Medarević, Đorđe AU - Kleinebudde, Peter AU - Đuriš, Jelena AU - Đurić, Zorica AU - Ibrić, Svetlana PY - 2016 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/2568 AB - This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus (R)-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus (R)-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q(10)) and 20 (Q(20)) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged. PB - Taylor & Francis Ltd, Abingdon T2 - Drug Development and Industrial Pharmacy T1 - Combined application of mixture experimental design and artificial neural networks in the solid dispersion development VL - 42 IS - 3 SP - 389 EP - 402 DO - 10.3109/03639045.2015.1054831 ER -
@article{ author = "Medarević, Đorđe and Kleinebudde, Peter and Đuriš, Jelena and Đurić, Zorica and Ibrić, Svetlana", year = "2016", abstract = "This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus (R)-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus (R)-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q(10)) and 20 (Q(20)) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.", publisher = "Taylor & Francis Ltd, Abingdon", journal = "Drug Development and Industrial Pharmacy", title = "Combined application of mixture experimental design and artificial neural networks in the solid dispersion development", volume = "42", number = "3", pages = "389-402", doi = "10.3109/03639045.2015.1054831" }
Medarević, Đ., Kleinebudde, P., Đuriš, J., Đurić, Z.,& Ibrić, S.. (2016). Combined application of mixture experimental design and artificial neural networks in the solid dispersion development. in Drug Development and Industrial Pharmacy Taylor & Francis Ltd, Abingdon., 42(3), 389-402. https://doi.org/10.3109/03639045.2015.1054831
Medarević Đ, Kleinebudde P, Đuriš J, Đurić Z, Ibrić S. Combined application of mixture experimental design and artificial neural networks in the solid dispersion development. in Drug Development and Industrial Pharmacy. 2016;42(3):389-402. doi:10.3109/03639045.2015.1054831 .
Medarević, Đorđe, Kleinebudde, Peter, Đuriš, Jelena, Đurić, Zorica, Ibrić, Svetlana, "Combined application of mixture experimental design and artificial neural networks in the solid dispersion development" in Drug Development and Industrial Pharmacy, 42, no. 3 (2016):389-402, https://doi.org/10.3109/03639045.2015.1054831 . .