Optimization issues in physiological toxicokinetic modeling: a case study with benzene.
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.
Woodruff
T J
TJ
Institute of Health Policy Studies, University of California, San Francisco 94109.
Bois
F Y
FY
D000818:Animals; D001554:Benzene / Q000493:pharmacokinetics* / Q000633:toxicity; D006801:Humans; D016013:Likelihood Functions; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D014116:Toxicology
D001554:Benzene