Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicokinetic model.
Population variability and uncertainty are important features of biological systems that must be considered when developing mathematical models for these systems. In this paper we present probability-based parameter estimation methods that account for such variability and uncertainty. Theoretical results that establish well-posedness and stability for these methods are discussed. A probabilistic parameter estimation technique is then applied to a toxicokinetic model for trichloroethylene using several types of simulated data. Comparison with results obtained using a standard, deterministic parameter estimation method suggests that the probabilistic methods are better able to capture population variability and uncertainty in model parameters.
Banks
H T
HT
Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC 27695-8205, USA. htbanks@eos.ncsu.edu
Potter
Laura K
LK
D000818:Animals; D004785:Environmental Pollutants / Q000493:pharmacokinetics / Q000633:toxicity; D006801:Humans; D008433:Mathematics; D008954:Models, Biological; D015233:Models, Statistical; D010599:Pharmacokinetics; D014241:Trichloroethylene / Q000493:pharmacokinetics / Q000633:toxicity
D004785:Environmental Pollutants; D014241:Trichloroethylene