NDLI: Joint use of simulation and nonlinear curve fitting in compartmental models (abstract)

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Joint use of simulation and nonlinear curve fitting in compartmental models (abstract)

Content Provider	ACM Digital Library
Author	Katzper, Meyer
Abstract	Simulation and nonlinear fitting programs allow a greater role for human experience and judgement when used jointly in obtaining the best ranges and fit for the parameters of compartmental models. Currently available software provides graphical interfaces which make a viewing and intervention strategy attractive and efficient. This is especially the case in nonlinear models where required initial estimates can lead to false solution due to local minima. Simulations can be used which provide graphical displays for comparison with experimental data to obtain parameter ranges and initial estimates.This approach was applied to compartmental models which are used in pharmacokinetics. The models provide a useful simplified phenomenological representation of drug disposition and concentration. The resulting nonlinear equations are parameterized by clearance, volume and rate constants. The parametric values are used in making dosing and therapy decisions. The problem of determining the pharmacokinetic parameters from observations is called the identification problem.Nonlinear fitting approaches, with iterative search algorithms, are sensitive to the initial estimates assumed for the parameters. Difference equation simulations can easily represent a wide variety of compartmental models. Their results can be used to provide initial estimates for the nonlinear curve fitting programs. Possibly more importantly, comparing the model output with the experimental data will aid in deciding whether an appropriate compartmental model was specified.Current work has focused on using NONMEM (Nonlinear Mixed Effects Modeling) for population pharmacokinetics and Stella for simulation.
File Format	PDF
ISBN	0897913485
DOI	10.1145/100348.100467
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1990-01-01
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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