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Data-Driven Modeling of Diabetes Progression

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Data-driven Modeling for Diabetes

Part of the book series: Lecture Notes in Bioengineering ((LNBE))

Abstract

A realistic representation of the long-term physiologic adaptation to developing insulin resistance would facilitate the effective design of clinical trials evaluating diabetes prevention or disease modification therapies. In the present work, a realistic, robust description of the evolution of the compensation of the glucose-insulin system in healthy and diabetic individuals, with particular attention to the physiological compensation to worsening insulin resistance is formulated, its physiological assumptions are presented, and its performance over the span of a lifetime is simulated. Model-based simulations of the long-term evolution of the disease and of its response to therapeutic interventions are consistent with the transient benefits observed with conventional therapies, and with promising effects of radical improvement of insulin sensitivity (as by metabolic surgery) or of β-cell protection. The mechanistic Diabetes Progression Model provides a credible tool by which long-term implications of anti-diabetic interventions can be evaluated.

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Authors and Affiliations

  1. Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti” - Laboratorio di Biomatematica, UCSC-Largo A. Gemelli, 8, 00168, Roma, Italy

    Andrea DeGaetano, Simona Panunzi & Claudio Gaz

  2. Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”, Viale Manzoni, 30, Roma, 00185, Italy

    Pasquale Palumbo

  3. Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, USA

    Thomas Hardy

Authors
  1. Andrea DeGaetano
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  2. Simona Panunzi
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  3. Pasquale Palumbo
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  4. Claudio Gaz
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  5. Thomas Hardy
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Corresponding author

Correspondence to Simona Panunzi .

Editor information

Editors and Affiliations

  1. Biomedical Engineering, University of Southern California, Los Angeles, California, USA

    Vasilis Marmarelis

  2. Electrical and Computer Engineering, Greece, University of Cyprus,Nicosia,Greese and McGill University, Montreal QC, Canada

    Georgios Mitsis

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DeGaetano, A., Panunzi, S., Palumbo, P., Gaz, C., Hardy, T. (2014). Data-Driven Modeling of Diabetes Progression. In: Marmarelis, V., Mitsis, G. (eds) Data-driven Modeling for Diabetes. Lecture Notes in Bioengineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54464-4_8

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  • DOI: https://doi.org/10.1007/978-3-642-54464-4_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54463-7

  • Online ISBN: 978-3-642-54464-4

  • eBook Packages: EngineeringEngineering (R0)

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