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Updated: Oct 4, 2025

Homogeneous Time-resolved Förster Resonance Energy Transfer-based Assay for Detection of Insulin Secretion
Published on: May 10, 2018
Clinical Evaluation of a Novel Insulin Immunosensor
Eleonora M Aiello1,2, Jordan E Pinsker2, Eva Vargas3
1Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA, USA.
Background:
The estimation of available active insulin remains a limitation of automated insulin delivery systems. Currently, insulin pumps calculate active insulin using mathematical decay curves, while quantitative measurements of insulin would explicitly provide person-specific PK insulin dynamics to assess remaining active insulin more accurately, permitting more effective glucose control.
Methods:
We performed the first clinical evaluation of an insulin immunosensor chip, providing near real-time measurements of insulin levels. In this study, we sought to determine the accuracy of the novel insulin sensor and assess its therapeutic risk and benefit by presenting a new tool developed to indicate the potential therapeutic consequences arising from inaccurate insulin measurements.
Results:
Nine adult participants with type-1 diabetes completed the study. The change from baseline in immunosensor-measured insulin levels was compared with values obtained by standard enzyme-linked immunosorbant assay (ELISA) after preprandial injection of insulin. The point-of-care quantification of insulin levels revealed similar temporal trends as those from the laboratory insulin ELISA. The results showed that 70% of the paired immunosensor-reference values were concordant, which suggests that the patient could take action safely based on insulin concentration obtained by the novel sensor.
Conclusions:
This proposed technology and preliminary feasibility evaluation show encouraging results for near real-time evaluation of insulin levels, with the potential to improve diabetes management. Real-time measurements of insulin provide person-specific insulin dynamics that could be used to make more informed decisions regarding insulin dosing, thus helping to prevent hypoglycemia and improve diabetes outcomes.

