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

T J Woodruff·F Y Bois
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Abstract

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.

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AnimalsBenzeneHumansLikelihood FunctionsModels, BiologicalModels, StatisticalMonte Carlo MethodToxicologyJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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T J Woodruff, F Y Bois. 1993. Optimization issues in physiological toxicokinetic modeling: a case study with benzene.. https://doi.org/10.1016/0378-4274(93)90103-5

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