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AAPS PharmSciTech

, Volume 14, Issue 2, pp 511–516 | Cite as

Application of Physicochemical Properties and Process Parameters in the Development of a Neural Network Model for Prediction of Tablet Characteristics

  • Tamás Sovány
  • Kitti Papós
  • Péter KásaJr.
  • Ilija Ilič
  • Stane Srčič
  • Klára Pintye-Hódi
Research Article

Abstract

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural 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.

Key words

artificial neural network mechanical properties plasticity surface characteristics tablet 

Notes

ACKNOWLEDGMENTS

The work was supported by the Project named “TÁMOP-4.2.1/B-09/1/KONV-2010-0005, –creating the Center of Excellence at the University of Szeged” is supported by the European Union and co-financed by the European Regional Fund and by the bilateral Hungarian-Slovenian Science and Technology Transfer Project SI-17/2009.

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Copyright information

© American Association of Pharmaceutical Scientists 2013

Authors and Affiliations

  • Tamás Sovány
    • 1
  • Kitti Papós
    • 1
  • Péter KásaJr.
    • 1
  • Ilija Ilič
    • 2
  • Stane Srčič
    • 2
  • Klára Pintye-Hódi
    • 1
  1. 1.Department of Pharmaceutical TechnologyUniversity of SzegedSzegedHungary
  2. 2.Department of Pharmaceutical TechnologyUniversity of LjubljanaLjubljanaSlovenia

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