Automated Oral Minimal Models for Rapid Estimation of Insulin Sensitivity and Beta-Cell Responsivity in Large-Scale Data Sets: A Validation Study

Simone Perazzolo; Alfonso Galderisi; Alice Carr; Colin Dayan; Claudio Cobelli

doi:10.1177/19322968251365274

Automated Oral Minimal Models for Rapid Estimation of Insulin Sensitivity and Beta-Cell Responsivity in Large-Scale Data Sets: A Validation Study

Simone Perazzolo^*
, Alfonso Galderisi
, Alice Carr
, Colin Dayan
, Claudio Cobelli

^*Corresponding author for this work

Immunology and Immunotherapy

Research output: Contribution to journal › Article › peer-review

Abstract

The Oral Minimal Model (OMM) analysis offers unique measures of glucose–insulin regulation during glucose challenges. However, its manual test-by-test implementation limits scalability in large studies. We introduce the Automated Oral Minimal Model (AOMM), a tool that streamlines and automates the entire OMM workflow while preserving analytical fidelity, enabling efficient batch processing of large datasets. Built on SAAM II software, AOMM was validated against manually extracted results from Sunehag et al (Obesity (Silver Spring), 2008), accurately reproducing key parameters such as insulin sensitivity (Si) and beta-cell responsivity (Φ) with high precision and substantial time savings. AOMM, with its user-friendly interface, facilitates broader application of minimal modeling in research and clinical studies.

Original language	English
Article number	19322968251365274
Number of pages	4
Journal	Journal of Diabetes Science and Technology
Early online date	3 Sept 2025
DOIs	https://doi.org/10.1177/19322968251365274
Publication status	E-pub ahead of print - 3 Sept 2025

Bibliographical note

Publisher Copyright:
© 2025 Diabetes Technology Society

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

beta-cell responsivity
diabetes algorithms
glucose minimal model
insulin sensitivity
oral minimal model
SAAM II

ASJC Scopus subject areas

Internal Medicine
Bioengineering
Endocrinology, Diabetes and Metabolism
Biomedical Engineering

Access to Document

10.1177/19322968251365274Licence: None: All rights reserved

Cite this

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abstract = "The Oral Minimal Model (OMM) analysis offers unique measures of glucose–insulin regulation during glucose challenges. However, its manual test-by-test implementation limits scalability in large studies. We introduce the Automated Oral Minimal Model (AOMM), a tool that streamlines and automates the entire OMM workflow while preserving analytical fidelity, enabling efficient batch processing of large datasets. Built on SAAM II software, AOMM was validated against manually extracted results from Sunehag et al (Obesity (Silver Spring), 2008), accurately reproducing key parameters such as insulin sensitivity (Si) and beta-cell responsivity (Φ) with high precision and substantial time savings. AOMM, with its user-friendly interface, facilitates broader application of minimal modeling in research and clinical studies.",

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AU - Carr, Alice

AU - Dayan, Colin

AU - Cobelli, Claudio

PY - 2025/9/3

Y1 - 2025/9/3

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KW - glucose minimal model

KW - insulin sensitivity

KW - oral minimal model

KW - SAAM II

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Automated Oral Minimal Models for Rapid Estimation of Insulin Sensitivity and Beta-Cell Responsivity in Large-Scale Data Sets: A Validation Study

Abstract

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this