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Related Experiment Videos

Iterative least-squares fitting programs in pharmacokinetics for a programmable handheld calculator.

A Messori, G Donati-Cori, E Tendi

    American Journal of Hospital Pharmacy
    |October 1, 1983
    PubMed
    Summary

    This study presents calculator programs for pharmacokinetic modeling. These programs efficiently estimate key variables for one-compartment oral and two-compartment intravenous models using nonlinear least-squares fitting.

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    Area of Science:

    • Pharmacokinetics and computational modeling

    Background:

    • Pharmacokinetic (PK) models are crucial for understanding drug behavior in the body.
    • Accurate estimation of PK variables requires robust fitting methods.
    • Limited accessibility to sophisticated computational tools can hinder PK analysis.

    Purpose of the Study:

    • To develop and describe user-friendly software for pharmacokinetic model fitting.
    • To enable estimation of key variables for one-compartment oral and two-compartment intravenous models.
    • To provide an accessible and inexpensive tool for pharmacokinetic analysis.

    Main Methods:

    • Nonlinear least-squares fitting algorithms, specifically the Gauss-Newton method modified by Hartley.
    • Method of residuals for initial parameter estimation.
    • Implementation on a Hewlett-Packard HP-41 CV programmable calculator with extended memory modules.

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  • Inclusion of a lag-time estimation routine for oral models.
  • Main Results:

    • Successfully developed programs for fitting one-compartment oral and two-compartment intravenous PK models.
    • Demonstrated clinical applicability using previously published data.
    • Provided programming steps and user instructions for practical implementation.
    • Achieved efficient and cost-effective estimation of pharmacokinetic variables.

    Conclusions:

    • The developed calculator programs offer an efficient and inexpensive method for estimating pharmacokinetic variables.
    • These programs enhance the accessibility of PK analysis for researchers with limited resources.
    • The use of a modified Gauss-Newton algorithm minimizes convergence issues in the fitting process.