Microsphere based continuous-flow immunoassay in a microfluidic device for determination of clinically relevant insulin levels

Cohen, Noa; Sabhachandani, Pooja; Sarkar, Saheli; Kahanovitz, Lindy; Lautsch, Norman; Russell, Steven; Konry, Tania

doi:10.1007/s00604-017-2072-z

Cited by 10 publications

(6 citation statements)

References 37 publications

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“…The glucagon dosing regimens were stratified in relation to different methods of estimating ambient insulin levels. We included IOB because no real‐time monitors of serum insulin concentrations are currently available . For decades, insulin pumps with bolus calculators have used IOB feedback as standard to prevent insulin stacking.…”

Section: Discussionmentioning

confidence: 99%

Relationship between Optimum Mini‐doses of Glucagon and Insulin Levels when Treating Mild Hypoglycaemia in Patients with Type 1 Diabetes – A Simulation Study

Ranjan

Wendt

Schmidt

et al. 2017

Basic Clin Pharma Tox

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Hypoglycaemia remains the main limiting factor in type 1 diabetes management. We developed an insulin-dependent glucagon dosing regimen for treatment of mild hypoglycaemia based on simulations. A validated glucose-insulin-glucagon model was used to describe seven virtual patients with insulin pump-treated type 1 diabetes. In each simulation, one of ten different and individualized subcutaneous insulin boluses was administered to decrease plasma glucose (PG) from 7.0 to ≤3.9 mmol/l. Insulin levels were estimated as ratio of actual to baseline serum insulin concentration (se/ba-insulin), insulin on board (IOB) or percentage of IOB to total daily insulin dose (IOB/TDD). Insulin bolus sizes were chosen to provide pre-defined insulin levels when PG reached 3.9 mmol/l, where one of 17 subcutaneous glucagon boluses was administered. Optimum glucagon bolus to treat mild hypoglycaemia at varying insulin levels was the lowest dose that in most patients caused PG peak between 5.0 and 10.0 mmol/l and sustained PG ≥ 3.9 mmol/l for 2 hr after the bolus. PG response to glucagon declined with increasing insulin levels. The glucagon dose to optimally treat mild hypoglycaemia depended exponentially on insulin levels, regardless of how insulin was estimated. A 125-μg glucagon dose was needed to optimally treat mild hypoglycaemia when insulin levels were equal to baseline levels. In contrast, glucagon doses >500 μg were needed when se/ba-insulin >2.5, IOB >2.0 U or IOB/TDD >6%. Although the proposed model-based glucagon regimen needs confirmation in clinical trials, this is the first attempt to develop an insulin-dependent glucagon dosing regimen for treatment of insulin-induced mild hypoglycaemia in patients with type 1 diabetes.

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Section: Discussionmentioning

confidence: 99%

Relationship between Optimum Mini‐doses of Glucagon and Insulin Levels when Treating Mild Hypoglycaemia in Patients with Type 1 Diabetes – A Simulation Study

Ranjan

Wendt

Schmidt

et al. 2017

Basic Clin Pharma Tox

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“…Optical methods commonly utilize an immunoassay approach. 42,139,142,143,154 In an optical biosensor, a change in the behavior of a light wave or a chemiluminescent reaction occurs, which can then be detected by an appropriate transducer (Figure 2). Details of each of the three methods are given below, in conjunction with an example of the method being utilized for insulin detection.…”

Section: ■ Biosensorsmentioning

confidence: 99%

“…Cohen et al achieved a linear range of 50 to 180 pM, which includes the upper range of insulin found in blood (Table 3). 142 In another example, Ho et al based their approach on a sandwich immunoassay, which used a microcapillary system for improved separation. Their approach took around 30 minutes and they achieved a linear range of 10 pM to 10 nMwhich includes the levels of insulin found in blood.…”

Section: ■ Biosensorsmentioning

confidence: 99%

“…In the case of optical biosensing, three methods have been used for insulin detectionsurface plasmon resonance (SPR), Förster/fluorescence energy transfer (FRET), and fluorescence (Table ). Optical methods commonly utilize an immunoassay approach. ,,,, In an optical biosensor, a change in the behavior of a light wave or a chemiluminescent reaction occurs, which can then be detected by an appropriate transducer (Figure ). Details of each of the three methods are given below, in conjunction with an example of the method being utilized for insulin detection.…”

Section: Biosensorsmentioning

confidence: 99%

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Towards Point-of-Care Insulin Detection

2018

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Good glucose management through an insulin dose regime based on the metabolism of glucose helps millions of people worldwide manage their diabetes. Since Banting and Best extracted insulin, glucose management has improved due to the introduction of insulin analogues that act from 30 minutes to 28 days, improved insulin dose regimes, and portable glucose meters, with a current focus on alternative sampling sites that are less invasive. However, a piece of the puzzle is still missingthe ability to measure insulin directly in a Point-of-Care device. The ability to measure both glucose and insulin concurrently will enable better glucose control by providing an improved estimate for insulin sensitivity, minimizing variability in control, and maximizing safety from hypoglycaemia. However, direct detection of free insulin has provided a challenge due to the size of the molecule, the low concentration of insulin in blood, and the selectivity against interferants in blood. This review summarizes current insulin detection methods from immunoassays to analytical chemistry, and sensors. We also discuss the challenges and potential of each of the methods towards Point-of-Care insulin detection.

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“…70 This circumvents drawbacks related to excessive backpressure and preferential pathways, also improving the analyte-sorbent interaction. Applications of solid-phase microextractions in flow systems encompass miniaturization, 71,72 bioanalysis, 72 and chemical speciation. 73 Emphasis has been given to selective materials, biosorbents, and nanomaterials, including modified magnetic nanoparticles.…”

Section: Looking Forward: Research Perspectives On Flow Analysismentioning

confidence: 99%

Flow Analysis: Looking Back and Forward

Rocha¹

2018

J. Braz. Chem. Soc.

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Flow analysis changed significantly the way of performing chemical analysis by (i) mechanization of analytical procedures in a continuous flowing stream with minimal sample intercontamination; (ii) analytical measurements without attaining chemical equilibria, thus increasing the applicability of kinetic methods and allowing the exploitation of non-quantitative processes; (iii) exploitation of concentration gradients and (iv) use of unstable reagents or measurement of unstable products. Flow-based procedures are generally characterized by high sample throughput, improved precision, minimized waste generation, and often better selectivity. The performance of detection systems is usually improved because of the in-line sample conditioning and measurements under reproductive dynamic conditions and timing. However, after achieving several innovations, perspectives for further developments have been questioned mainly because of the recent decrease in the number of publications on flow analysis. The aim of this review is then to discuss the impact of flow-based methods on chemical analysis, emphasizing recent applications and developments, including miniaturization, bioanalysis, microextractions, green analytical chemistry and synergic hyphenation with other techniques and processes. The author's personal view about research perspectives in the field is also presented.

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Microsphere based continuous-flow immunoassay in a microfluidic device for determination of clinically relevant insulin levels

Cited by 10 publications

References 37 publications

Relationship between Optimum Mini‐doses of Glucagon and Insulin Levels when Treating Mild Hypoglycaemia in Patients with Type 1 Diabetes – A Simulation Study

Relationship between Optimum Mini‐doses of Glucagon and Insulin Levels when Treating Mild Hypoglycaemia in Patients with Type 1 Diabetes – A Simulation Study

Towards Point-of-Care Insulin Detection

Flow Analysis: Looking Back and Forward

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