Clinical Evaluation of a Novel Insulin Immunosensor

Abstract

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.

Concept of the “Universal Slope”: Toward Substantially Shorter Decentralized Insulin Immunoassays

“…The serum insulin concentrations were calculated by extrapolation using the calibration equations obtained from the sensor measurements, estimated by the least-squares linear regression method using Microsoft Excel. The error bars shown in the insulin concentration values quantified by the SA method (shown in Figure ) correspond to the error in the analyte concentration quantification estimated through the typical error of the calibration as indicated previously . In the case of the US-based approach, we estimated the insulin concentrations by dividing the amperometric signal recorded for the serum samples without spiked insulin standard by the average slope, described in detail in the Results and Discussion section below.…”

“…The prospective universality of an averaged slope was assessed with ANOVA. For this analysis, all the subjects were included except for patient HS1-07 as this individual was tested using different experimental assay conditions . An ANOVA test is usually used to determine whether there are any statistically significant differences between the means of three or more independent groups using the F-distribution .…”

“…Full details on the chemicals, instrumentation, and procedures used in the fabrication, bioassays, and amperometric measurements of the insulin immunosensor mentioned in this work have been reported previously. , Briefly, sensors were batch-fabricated in UC San Diego by metal sputtering deposition on plastic substrates, with each sensor consisting of two rectangular gold electrodes acting as working and joint reference/counter electrodes, respectively. The working electrode of each chip was functionalized with an alkanethiol-based self-assembled monolayer for the covalent attachment of the anti-insulin antibody and a deactivation reaction on the capture antibody-modified surface to prevent nonspecific binding was performed.…”

“…The US bioaffinity sensor concept has been demonstrated using an enzyme (HRP)-based sandwich insulin immunosensor, which is commonly relying on SA calibrations with insulin standard-spiked serum samples . Such a sensor was applied for decentralized clinical testing, monitoring serum insulin temporal profiles of individuals with type 1 diabetes and compared with a centralized lab-based ELISA method . In the following sections, we explore the theoretical approach behind the universality of a constant representing the analytical performance of an immunosensor for serum insulin measurements along with the feasibility of using the US to quantify serum insulin in relevant clinical samples using robust statistical analysis to support the significance of the results obtained.…”

“…Such simplified operation would enable insulin measurements to be less susceptible to personnel skills, environmental conditions, or workplace equipment. The US provides an attractive approach to bring closer the implementation of disposable insulin immunostrips, coupled with hand-held readers, toward substantially faster, simpler, and cheaper POC insulin testing (Figure C), along with timely interventions in the management of diabetes. − While the new US concept is demonstrated here in connection to insulin diabetes testing, it can be readily adapted to the rapid decentralized immunoassays of a wide range of clinically relevant biomarkers where fast and timely interventions are critical.…”