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Metabolic modeling using statistical and spreadsheet software: Application to the glucose minimal model.

D Stefanovski1, P J Moate2, N Frank3

  • 1Department of Clinical Studies - New Bolton Center, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, United States.

Computer Methods and Programs in Biomedicine
|March 1, 2020
PubMed
Summary
This summary is machine-generated.

Statistical and spreadsheet software can accurately fit the Glucose Minimal Model to insulin sensitivity data. This approach offers a viable alternative to specialized software for kinetic non-linear metabolic modeling.

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Area of Science:

  • Metabolic modeling
  • Pharmacokinetics and pharmacodynamics
  • Biostatistics

Background:

  • Kinetic non-linear metabolic models are crucial in medical research and diagnostics.
  • The Glucose Minimal Model, while powerful, is notoriously difficult to fit to data consistently.
  • Specialized software packages are typically required for fitting these complex models.

Purpose of the Study:

  • To demonstrate the utility of statistical and spreadsheet software for fitting the Glucose Minimal Model.
  • To present a novel method of solving differential equations for explicit forms to simplify parameter estimation.
  • To validate the accuracy of this approach by comparing results with industry-standard software.

Main Methods:

  • The Glucose Minimal Model's differential equations were solved into explicit forms.
  • Nonlinear optimization procedures in STATA and Excel were used for parameter estimation.
  • Insulin sensitivity (SI) was calculated using data from insulin-modified intravenous glucose tolerance tests (IM-IVGTT) in horses.

Main Results:

  • Estimates of insulin sensitivity (SI) derived using STATA and Excel showed high concordance with those from MinMod Millennium.
  • The novel explicit-form modeling approach facilitated parameter estimation.
  • The study utilized IM-IVGTT data from 90 horses across two experiments.

Conclusions:

  • Statistical and spreadsheet software can be effectively used for fitting the Glucose Minimal Model.
  • This approach provides a reliable and accessible alternative to specialized modeling software.
  • The findings suggest broader applicability of statistical and spreadsheet tools for kinetic non-linear modeling challenges.