title: Use of artificial neural networks to predict drug dissolution profiles and evaluation of network performance using similarity factor.
abstract: OBJECTIVE
  To use artificial neural networks for predicting dissolution profiles of matrix-controlled release theophylline pellet preparation, and to evaluate the network performance by comparing the predicted dissolution profiles with those obtained from physical experiments using similarity factor.
  
  
  METHODS
  The Multi-Layered Perceptron (MLP) neural network was used to predict the dissolution profiles of theophylline pellets containing different ratios of microcrystalline cellulose (MCC) and glyceryl monostearate (GMS). The concepts of leave-one-out as well as a time-point by time-point estimation basis were used to predict the rate of drug release for each matrix ratio. All the data were used for training, except for one set which was selected to compare with the predicted output. The closeness between the predicted and the reference dissolution profiles was investigated using similarity factor (f2).
  
  
  RESULTS
  The f2 values were all above 60, indicating that the predicted dissolution profiles were closely similar to the dissolution profiles obtained from physical experiments.
  
  
  CONCLUSIONS
  The MLP network could be used as a model for predicting the dissolution profiles of matrix-controlled release theophylline pellet preparation in product development.
authors.affiliation: School of Pharmaceutical Sciences, University of Science Malaysia, Penang. kkpeh@usm.my
authors.forename: K K
authors.initials: KK
authors.lastname: Peh
authors.forename: C P
authors.initials: CP
authors.lastname: Lim
authors.forename: S S
authors.initials: SS
authors.lastname: Quek
authors.forename: K H
authors.initials: KH
authors.lastname: Khoh
mesh_terms: D002482:Cellulose / Q000737:chemistry; D002626:Chemistry, Pharmaceutical / Q000379:methods*; D003692:Delayed-Action Preparations; D005079:Excipients / Q000737:chemistry; D005989:Glycerides / Q000737:chemistry; D007700:Kinetics; D008956:Models, Chemical; D016571:Neural Networks, Computer; D012995:Solubility; D013806:Theophylline / Q000737:chemistry*
chemical_list: D003692:Delayed-Action Preparations; D005079:Excipients; D005989:Glycerides; C048159:glyceryl monostearate; D002482:Cellulose; D013806:Theophylline; C109691:microcrystalline cellulose