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Integrating Epidemiological Data into a Mechanistic Model of Type 2 Diabetes: Validating the Prevalence of Virtual Patients

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Abstract

Mathematical models are playing an increasing role in understanding the complexity of multifactorial diseases like type 2 diabetes. The objective of this study was to validate a population of virtual patients against a real population of patients with type 2 diabetes. A population of virtual patients was created that incorporates different underlying pathogenic lesions consistent with a type 2 diabetic phenotype. These virtual patients were created within the Metabolism PhysioLab platform, a non-linear coupled differential algebraic model that incorporates the salient causal mechanisms underlying glucose homeostasis and substrate metabolism. The weights of each individual virtual patient were determined to reproduce the diversity in a real type 2 diabetic population obtained from the NHANES III study. As a validation test, this virtual population reproduced a series of clinical studies that identify less invasive biomarkers for insulin sensitivity. This approach demonstrates how computational bridges can be constructed between statistical approaches common in epidemiology and deterministic approaches common in biomedical engineering.

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Abbreviations

4D-PDF:

4-Dimensional probability density function

NHANES:

National Health and Nutrition Examination Survey

OGTT:

Oral glucose tolerance test

PCA:

Principal component analysis

VP:

Virtual patient

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Acknowledgments

The author would like to acknowledge the contributions of several people to this work. Paul Brazhnik, Kevin Hall, Dave Polidori, Scott Siler, and Jeff Trimmer contributed to creating the Metabolism PhysioLab platform. Dave Polidori, Scott Siler, MariaLuisa Ruiz, and Arthur Lo contributed to creating virtual patients used in this study. Tom Paterson, Leif Wennerberg, and Christina Friedrich contributed to developing concepts related to prevalence assessment of virtual patients populations.

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  1. Department of Chemical Engineering, West Virginia University, P.O. Box 6102, Morgantown, WV, 25606, USA

    David J. Klinke II

  2. Department of Immunology, Microbiology, & Cell Biology, West Virginia University, Morgantown, WV, 25606, USA

    David J. Klinke II

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Correspondence to David J. Klinke II.

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Klinke, D.J. Integrating Epidemiological Data into a Mechanistic Model of Type 2 Diabetes: Validating the Prevalence of Virtual Patients. Ann Biomed Eng 36, 321–334 (2008). https://doi.org/10.1007/s10439-007-9410-y

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  • DOI: https://doi.org/10.1007/s10439-007-9410-y

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