Gluclas 2.0 - A mobile app for clinical decision support during glucose clamps
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Updated: Oct 31, 2026

Improving IV Insulin Administration in a Community Hospital
Published on: June 11, 2012
Giovanni Tubaro1, Bettina Weber2, Giacomo Cappon1
1Department of Information Engineering, University of Padova, Padova, Italy.
Background And Objective:
Glucose clamps are valuable yet complex experimental techniques used in metabolic research. Among these, ISOglycemic IntraVenous (ISO-IV) clamps are used to assess the incretin effect, that is, the enhanced insulin response following nutrient intake compared to an equivalent glucose increase induced intravenously. ISO-IV clamps require replicating the glucose profile of an oral glucose tolerance test through IV infusion, making them particularly challenging and prone to operator variability. This study presents Gluclas 2.0, a mobile application designed to assist clinicians in modulating glucose infusion rates (GIR) during ISO-IV clamps.
Method:
Gluclas 2.0 integrates a Proportional-Integral-Derivative controller with a personalized feedforward component for proactive GIR control. The system is implemented in a mobile app featuring a user-friendly interface. It was tuned and validated in silico using 87 virtual prediabetic subjects, simulating realistic conditions including measurement noise and sampling delays. Preliminary in vivo testing was also conducted on two human subjects.
Results:
In silico validation yielded a population-wide Mean Absolute Percentage Error (MAPE) of 4.12%, below the 5% threshold for effective clamping. Preliminary in vivo tests produced results within the range observed in silico.
Conclusion:
Gluclas 2.0 achieved satisfactory reference-tracking performance in simulations conducted in silico and showed promising preliminary feasibility in two human ISO-IV clamps. While broader clinical validation is required, these findings support its potential as a low-cost decision-support tool for standardizing ISO-IV clamp procedures and reducing operator-dependent variability.
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