Optimization issues in physiological toxicokinetic modeling: a case study with benzene

Toxicol Lett. 1993 Aug;69(2):181-96. doi: 10.1016/0378-4274(93)90103-5.


This paper compares two methods for global optimization of physiologically based toxicokinetic models: Monte Carlo optimization, which searches randomly for the optimum; and the simplex method, which updates systematically an array of parameter values. Two measures of goodness-of-fit are also contrasted: criterion function and likelihood. A 14-parameter model of benzene distribution in rats is used to illustrate these techniques. Simplex optimization yields better fits overall. However, the measurement of uncertainty offered by Monte Carlo simulations is a major argument in favor of their use.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Animals
  • Benzene / pharmacokinetics*
  • Benzene / toxicity
  • Humans
  • Likelihood Functions
  • Models, Biological*
  • Models, Statistical
  • Monte Carlo Method
  • Toxicology*


  • Benzene