Pharmacokinetic application of fuzzy structure identification and reasoning

  • Authors:

  • Kemal Kilic;Beth A. Sproule;I. Burhan Türksen;Claudio A. Naranjo

  • Affiliations:

  • Faculty of Engineering and Natural Sciences, Sabanci University, Orhanli, Tuzla, Istanbul, Turkey;Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada M5S 3G8 and Faculty of Pharmacy, Univ. of Toronto and Dept. of Psychiatry, Univ. of Toronto, Toronto, ON, Canada ...;Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, ON, Canada M5S 3G8;Dept. of Psychiatry, Psychopharmacology Research Program, Sunnybrook and Women's College Health Sciences Centre, Dept. of Pharmacology, Dept. of Medicine, Univ. of Toronto, Toronto, ON, Canada M5S ...

  • Venue:
  • Information Sciences: an International Journal - Special issue: Medical expert systems
  • Year:
  • 2004

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Abstract

The aim of this paper is to introduce the algorithm proposed in [Fuzzy Sets and System, 2002] and some further modifications. Its applications presented in [ibid: A comparison of five approaches for lithium dose and serum concentration prediction, IFSA-NAFIPS 2001, pp. 104-110] is reviewed as a full collection of its use in pharmacokinetic analysis. First a recently developed fuzzy system modeling algorithm and approximate reasoning tool are introduced along with the modifications. Later the performance of the proposed algorithm is tested in two different data sets and compared with some well-known algorithms from the literature. In the comparison, individualized pharmacokinetic data (i.e., alprazolam data) and population pharmacokinetic data (i.e., lithium data) are used. The comparisons demonstrate that the proposed algorithm can be successfully applied in pharmacokinetic modeling.