Investigation of an artificial intelligence technology--Model trees. Novel applications for an immediate release tablet formulation database

Eur J Pharm Sci. 2007 Jun;31(2):137-44. doi: 10.1016/j.ejps.2007.03.004. Epub 2007 Mar 12.


This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Artificial Intelligence*
  • Carboxymethylcellulose Sodium / chemistry
  • Cellulose / chemistry
  • Chemistry, Pharmaceutical
  • Decision Trees*
  • Drug Compounding
  • Excipients / chemistry*
  • Models, Chemical
  • Neural Networks, Computer
  • Pharmaceutical Preparations / chemistry*
  • Reproducibility of Results
  • Silica Gel
  • Silicon Dioxide / chemistry
  • Solubility
  • Stearic Acids / chemistry
  • Tablets
  • Technology, Pharmaceutical / methods*
  • Tensile Strength
  • Time Factors


  • Excipients
  • Pharmaceutical Preparations
  • Stearic Acids
  • Tablets
  • stearic acid
  • Silica Gel
  • Silicon Dioxide
  • Cellulose
  • Carboxymethylcellulose Sodium
  • microcrystalline cellulose