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A fluorescence sandwich immunoassay for the real-time continuous detection of glucose and insulin in live animals


Biosensors that continuously measure circulating biomolecules in real time could provide insights into the health status of patients and their response to therapeutics. But biosensors for the continuous real-time monitoring of analytes in vivo have only reached nanomolar sensitivity and can measure only a handful of molecules, such as glucose and blood oxygen. Here we show that multiple analytes can be continuously and simultaneously measured with picomolar sensitivity and sub-second resolution via the integration of aptamers and antibodies into a bead-based fluorescence sandwich immunoassay implemented in a custom microfluidic chip. After an incubation time of 30 s, bead fluorescence is measured using a high-speed camera under spatially multiplexed two-colour laser illumination. We used the assay for continuous quantification of glucose and insulin concentrations in the blood of live diabetic rats to resolve inter-animal differences in the pharmacokinetic response to insulin as well as discriminate pharmacokinetic profiles from different insulin formulations. The assay can be readily modified to continuously and simultaneously measure other blood analytes in vivo.

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Fig. 1: Overview and validation of the RT-ELISA assay strategy.
Fig. 2: Overview of the RT-ELISA technology.
Fig. 3: Testing and optimization of the core components of RT-ELISA.
Fig. 4: Continuous in vitro monitoring of glucose and insulin in whole blood.
Fig. 5: Continuous real-time measurements of glucose and insulin in diabetic rats.
Fig. 6: Glucose and insulin measurements in an awake diabetic rat.
Fig. 7: Comparison of different insulin formulation pharmacokinetics.

Data availability

The data supporting the results in this study are available within the paper and its Supplementary Information. All raw and annotated data generated in this study are available from figshare with the identifier

Code availability

The Python code used to analyse bead images is provided at


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This research was supported by the Chan Zuckerberg Biohub, a Stanford Diabetes Research Center (SDRC) Pilot grant and the Transdisciplinary Initiative Program (TIP) from the Stanford Maternal & Child Health Research Institute (MCHRI). C.L.M. was supported by a NSERC Postgraduate Scholarship and Stanford Bio-X Bowes Graduate Student Fellowship. We thank B. Buckingham and R. Lal for their helpful discussions as well as N. Maganzini and I. Thompson for their review and edits of the manuscript. We thank the Stanford Nanofabrication Facility (NSF) for their cleanroom facilities and the Canary Center at Stanford for Cancer Early Detection for their biolayer interferometry instrument. We thank the Stanford Veterinary Service Center staff for their assistance with animal care and procedures.

Author information




M.P., C.L.M. and H.T.S. conceived the initial concept. M.P. and C.L.M. designed experiments. M.P., C.L.M., E.Y.M., J.P., D.M., Y.H., A.Y. and S.W.B. executed experiments. A.B. developed the imaging analysis algorithm. M.P. and C.L.M. analysed the data. M.P., C.L.M., M.E. and H.T.S. wrote the manuscript. All authors edited, discussed and approved the whole paper.

Corresponding authors

Correspondence to Eric A. Appel or H. Tom Soh.

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Supplementary information

Supplementary Information

Supplementary methods, figures, video captions and references.

Reporting Summary

Supplementary Video 1

Separation, by DLD, of fluorescently labelled microbeads from blood cells and free fluorescently tagged antibodies.

Supplementary Video 2

Glucose and insulin beads passing through the detection window.

Supplementary Video 3

Control experiment showing that glucose beads only fluoresce in their specific region in the upper part of the detection window.

Supplementary Video 4

Control experiment showing that insulin beads only fluoresce in their specific region in the bottom part of the detection window.

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Poudineh, M., Maikawa, C.L., Ma, E.Y. et al. A fluorescence sandwich immunoassay for the real-time continuous detection of glucose and insulin in live animals. Nat Biomed Eng 5, 53–63 (2021).

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