Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics
Sovány, Tamás (Author), Papós, Kitty (Author), Kása, Peter jr. (Author), Ilić, Ilija (Author), Srčič, Stanko (Author), Pintyé-Hodi, Klára (Author)

URLURL - Presentation file, Visit http://link.springer.com/article/10.1208%2Fs12249-013-9932-6 This link opens in a new window

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of aneural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Keywords:artificial neural network, mechanical properties, plasticity, surface characteristics, tablet
Work type:Not categorized (r6)
Tipology:1.01 - Original Scientific Article
Organization:FFA - Faculty of Pharmacy
Number of pages:str. 511-516
Numbering:Vol. 14, issue 2
ISSN on article:1530-9932
DOI:10.1208/s12249-013-9932-6 Link is opened in a new window
COBISS.SI-ID:3403889 Link is opened in a new window
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Record is a part of a journal

Title:AAPS PharmSciTech
Shortened title:AAPS PharmSciTech
Publisher:American Association of Pharmaceutical Scientists
COBISS.SI-ID:1247345 This link opens in a new window

Secondary language

Keywords:tablete, farmacevtska industrija, nevronske mreže, površinske značilnosti

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