Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96865
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPaclawski, Adamen
dc.contributor.authorLau, Raymonden
dc.contributor.authorJachowicz, Renataen
dc.contributor.authorMendyk, Aleksanderen
dc.contributor.authorSzlk, Jakuben
dc.date.accessioned2014-10-15T02:59:06Zen
dc.date.accessioned2019-12-06T19:35:52Z-
dc.date.available2014-10-15T02:59:06Zen
dc.date.available2019-12-06T19:35:52Z-
dc.date.copyright2013en
dc.date.issued2013en
dc.identifier.citationSzlk, J., Paclawski, A., Lau, R., Jachowicz, R., & Mendyk, A. (2013). Heuristic modeling of macromolecule release from PLGA microspheres. International journal of nanomedicine, 8(1), 4601-4611.en
dc.identifier.issn1178-2013en
dc.identifier.urihttps://hdl.handle.net/10356/96865-
dc.description.abstractDissolution of protein macromolecules from poly(lactic-co-glycolic acid) (PLGA) particles is a complex process and still not fully understood. As such, there are difficulties in obtaining a predictive model that could be of fundamental significance in design, development, and optimization for medical applications and toxicity evaluation of PLGA-based multiparticulate dosage form. In the present study, two models with comparable goodness of fit were proposed for the prediction of the macromolecule dissolution profile from PLGA micro- and nanoparticles. In both cases, heuristic techniques, such as artificial neural networks (ANNs), feature selection, and genetic programming were employed. Feature selection provided by fscaret package and sensitivity analysis performed by ANNs reduced the original input vector from a total of 300 input variables to 21, 17, 16, and eleven; to achieve a better insight into generalization error, two cut-off points for every method was proposed. The best ANNs model results were obtained by monotone multi-layer perceptron neural network (MON-MLP) networks with a root-mean-square error (RMSE) of 15.4, and the input vector consisted of eleven inputs. The complicated classical equation derived from a database consisting of 17 inputs was able to yield a better generalization error (RMSE) of 14.3. The equation was characterized by four parameters, thus feasible (applicable) to standard nonlinear regression techniques. Heuristic modeling led to the ANN model describing macromolecules release profiles from PLGA microspheres with good predictive efficiency. Moreover genetic programming technique resulted in classical equation with comparable predictability to the ANN model.en
dc.format.extent11 p.en
dc.language.isoenen
dc.relation.ispartofseriesInternational journal of nanomedicineen
dc.rights© 2013 Szlęk et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information on how to request permission may be found at: http://www.dovepress.com/permissions.phpen
dc.subjectDRNTU::Science::Medicine::Biomedical engineeringen
dc.titleHeuristic modeling of macromolecule release from PLGA microspheresen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen
dc.identifier.doi10.2147/IJN.S53364en
dc.description.versionPublished versionen
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:SCBE Journal Articles
Files in This Item:
File Description SizeFormat 
IJN-53364-heuristic-modeling-of-macromolecules-release-from-plga-micro_112913.pdf1.17 MBAdobe PDFThumbnail
View/Open

SCOPUSTM   
Citations 10

29
Updated on Mar 5, 2021

PublonsTM
Citations 10

29
Updated on Mar 7, 2021

Page view(s) 20

439
Updated on Jun 16, 2021

Download(s) 20

232
Updated on Jun 16, 2021

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.